949 lines
30 KiB
C++
949 lines
30 KiB
C++
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//M*//////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of Intel Corporation may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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#undef INFINITY
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#define INFINITY 10000
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#define OCCLUSION_PENALTY 10000
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#define OCCLUSION_PENALTY2 1000
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#define DENOMINATOR 16
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#undef OCCLUDED
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#define OCCLUDED CV_STEREO_GC_OCCLUDED
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#define CUTOFF 1000
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#define IS_BLOCKED(d1, d2) ((d1) > (d2))
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typedef struct GCVtx
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{
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GCVtx *next;
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int parent;
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int first;
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int ts;
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int dist;
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short weight;
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uchar t;
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}
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GCVtx;
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typedef struct GCEdge
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{
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GCVtx* dst;
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int next;
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int weight;
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}
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GCEdge;
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typedef struct CvStereoGCState2
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{
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int Ithreshold, interactionRadius;
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int lambda, lambda1, lambda2, K;
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int dataCostFuncTab[CUTOFF+1];
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int smoothnessR[CUTOFF*2+1];
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int smoothnessGrayDiff[512];
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GCVtx** orphans;
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int maxOrphans;
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}
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CvStereoGCState2;
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// truncTab[x+255] = MAX(x-255,0)
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static uchar icvTruncTab[512];
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// cutoffSqrTab[x] = MIN(x*x, CUTOFF)
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static int icvCutoffSqrTab[256];
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static void icvInitStereoConstTabs()
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{
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static volatile int initialized = 0;
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if( !initialized )
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{
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int i;
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for( i = 0; i < 512; i++ )
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icvTruncTab[i] = (uchar)MIN(MAX(i-255,0),255);
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for( i = 0; i < 256; i++ )
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icvCutoffSqrTab[i] = MIN(i*i, CUTOFF);
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initialized = 1;
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}
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}
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static void icvInitStereoTabs( CvStereoGCState2* state2 )
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{
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int i, K = state2->K;
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for( i = 0; i <= CUTOFF; i++ )
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state2->dataCostFuncTab[i] = MIN(i*DENOMINATOR - K, 0);
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for( i = 0; i < CUTOFF*2 + 1; i++ )
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state2->smoothnessR[i] = MIN(abs(i-CUTOFF), state2->interactionRadius);
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for( i = 0; i < 512; i++ )
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{
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int diff = abs(i - 255);
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state2->smoothnessGrayDiff[i] = diff < state2->Ithreshold ? state2->lambda1 : state2->lambda2;
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}
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}
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static int icvGCResizeOrphansBuf( GCVtx**& orphans, int norphans )
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{
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int i, newNOrphans = MAX(norphans*3/2, 256);
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GCVtx** newOrphans = (GCVtx**)cvAlloc( newNOrphans*sizeof(orphans[0]) );
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for( i = 0; i < norphans; i++ )
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newOrphans[i] = orphans[i];
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cvFree( &orphans );
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orphans = newOrphans;
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return newNOrphans;
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}
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static int64 icvGCMaxFlow( GCVtx* vtx, int nvtx, GCEdge* edges, GCVtx**& _orphans, int& _maxOrphans )
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{
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const int TERMINAL = -1, ORPHAN = -2;
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GCVtx stub, *nilNode = &stub, *first = nilNode, *last = nilNode;
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int i, k;
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int curr_ts = 0;
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int64 flow = 0;
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int norphans = 0, maxOrphans = _maxOrphans;
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GCVtx** orphans = _orphans;
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stub.next = nilNode;
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// initialize the active queue and the graph vertices
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for( i = 0; i < nvtx; i++ )
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{
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GCVtx* v = vtx + i;
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v->ts = 0;
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if( v->weight != 0 )
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{
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last = last->next = v;
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v->dist = 1;
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v->parent = TERMINAL;
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v->t = v->weight < 0;
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}
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else
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v->parent = 0;
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}
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first = first->next;
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last->next = nilNode;
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nilNode->next = 0;
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// run the search-path -> augment-graph -> restore-trees loop
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for(;;)
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{
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GCVtx* v, *u;
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int e0 = -1, ei = 0, ej = 0, min_weight, weight;
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uchar vt;
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// grow S & T search trees, find an edge connecting them
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while( first != nilNode )
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{
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v = first;
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if( v->parent )
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{
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vt = v->t;
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for( ei = v->first; ei != 0; ei = edges[ei].next )
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{
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if( edges[ei^vt].weight == 0 )
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continue;
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u = edges[ei].dst;
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if( !u->parent )
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{
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u->t = vt;
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u->parent = ei ^ 1;
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u->ts = v->ts;
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u->dist = v->dist + 1;
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if( !u->next )
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{
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u->next = nilNode;
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last = last->next = u;
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}
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continue;
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}
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if( u->t != vt )
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{
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e0 = ei ^ vt;
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break;
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}
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if( u->dist > v->dist+1 && u->ts <= v->ts )
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{
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// reassign the parent
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u->parent = ei ^ 1;
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u->ts = v->ts;
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u->dist = v->dist + 1;
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}
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}
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if( e0 > 0 )
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break;
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}
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// exclude the vertex from the active list
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first = first->next;
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v->next = 0;
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}
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if( e0 <= 0 )
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break;
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// find the minimum edge weight along the path
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min_weight = edges[e0].weight;
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assert( min_weight > 0 );
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// k = 1: source tree, k = 0: destination tree
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for( k = 1; k >= 0; k-- )
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{
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for( v = edges[e0^k].dst;; v = edges[ei].dst )
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{
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if( (ei = v->parent) < 0 )
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break;
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weight = edges[ei^k].weight;
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min_weight = MIN(min_weight, weight);
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assert( min_weight > 0 );
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}
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weight = abs(v->weight);
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min_weight = MIN(min_weight, weight);
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assert( min_weight > 0 );
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}
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// modify weights of the edges along the path and collect orphans
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edges[e0].weight -= min_weight;
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edges[e0^1].weight += min_weight;
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flow += min_weight;
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// k = 1: source tree, k = 0: destination tree
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for( k = 1; k >= 0; k-- )
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{
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for( v = edges[e0^k].dst;; v = edges[ei].dst )
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{
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if( (ei = v->parent) < 0 )
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break;
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edges[ei^(k^1)].weight += min_weight;
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if( (edges[ei^k].weight -= min_weight) == 0 )
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{
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if( norphans >= maxOrphans )
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maxOrphans = icvGCResizeOrphansBuf( orphans, norphans );
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orphans[norphans++] = v;
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v->parent = ORPHAN;
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}
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}
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v->weight = (short)(v->weight + min_weight*(1-k*2));
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if( v->weight == 0 )
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{
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if( norphans >= maxOrphans )
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maxOrphans = icvGCResizeOrphansBuf( orphans, norphans );
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orphans[norphans++] = v;
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v->parent = ORPHAN;
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}
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}
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// restore the search trees by finding new parents for the orphans
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curr_ts++;
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while( norphans > 0 )
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{
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GCVtx* v = orphans[--norphans];
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int d, min_dist = INT_MAX;
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e0 = 0;
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vt = v->t;
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for( ei = v->first; ei != 0; ei = edges[ei].next )
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{
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if( edges[ei^(vt^1)].weight == 0 )
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continue;
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u = edges[ei].dst;
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if( u->t != vt || u->parent == 0 )
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continue;
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// compute the distance to the tree root
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for( d = 0;; )
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{
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if( u->ts == curr_ts )
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{
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d += u->dist;
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break;
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}
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ej = u->parent;
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d++;
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if( ej < 0 )
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{
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if( ej == ORPHAN )
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d = INT_MAX-1;
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else
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{
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u->ts = curr_ts;
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u->dist = 1;
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}
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break;
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}
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u = edges[ej].dst;
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}
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// update the distance
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if( ++d < INT_MAX )
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{
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if( d < min_dist )
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{
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min_dist = d;
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e0 = ei;
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}
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for( u = edges[ei].dst; u->ts != curr_ts; u = edges[u->parent].dst )
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{
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u->ts = curr_ts;
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u->dist = --d;
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}
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}
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}
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if( (v->parent = e0) > 0 )
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{
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v->ts = curr_ts;
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v->dist = min_dist;
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continue;
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}
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/* no parent is found */
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v->ts = 0;
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for( ei = v->first; ei != 0; ei = edges[ei].next )
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{
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u = edges[ei].dst;
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ej = u->parent;
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if( u->t != vt || !ej )
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continue;
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if( edges[ei^(vt^1)].weight && !u->next )
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{
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u->next = nilNode;
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last = last->next = u;
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}
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if( ej > 0 && edges[ej].dst == v )
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{
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if( norphans >= maxOrphans )
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maxOrphans = icvGCResizeOrphansBuf( orphans, norphans );
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orphans[norphans++] = u;
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u->parent = ORPHAN;
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}
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}
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}
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}
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_orphans = orphans;
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_maxOrphans = maxOrphans;
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return flow;
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}
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CvStereoGCState* cvCreateStereoGCState( int numberOfDisparities, int maxIters )
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{
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CvStereoGCState* state = 0;
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state = (CvStereoGCState*)cvAlloc( sizeof(*state) );
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memset( state, 0, sizeof(*state) );
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state->minDisparity = 0;
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state->numberOfDisparities = numberOfDisparities;
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state->maxIters = maxIters <= 0 ? 3 : maxIters;
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state->Ithreshold = 5;
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state->interactionRadius = 1;
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state->K = state->lambda = state->lambda1 = state->lambda2 = -1.f;
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state->occlusionCost = OCCLUSION_PENALTY;
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return state;
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}
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void cvReleaseStereoGCState( CvStereoGCState** _state )
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{
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CvStereoGCState* state;
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if( !_state && !*_state )
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return;
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state = *_state;
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cvReleaseMat( &state->left );
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cvReleaseMat( &state->right );
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cvReleaseMat( &state->ptrLeft );
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cvReleaseMat( &state->ptrRight );
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cvReleaseMat( &state->vtxBuf );
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cvReleaseMat( &state->edgeBuf );
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cvFree( _state );
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}
|
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|
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||
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// ||I(x) - J(x')|| =
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||
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// min(CUTOFF,
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||
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// min(
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// max(
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// max(minJ(x') - I(x), 0),
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||
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// max(I(x) - maxJ(x'), 0)),
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||
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// max(
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// max(minI(x) - J(x'), 0),
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// max(J(x') - maxI(x), 0)))**2) ==
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// min(CUTOFF,
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// min(
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// max(minJ(x') - I(x), 0) +
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// max(I(x) - maxJ(x'), 0),
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//
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// max(minI(x) - J(x'), 0) +
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// max(J(x') - maxI(x), 0)))**2)
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// where (I, minI, maxI) and
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||
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// (J, minJ, maxJ) are stored as interleaved 3-channel images.
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||
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// minI, maxI are computed from I,
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||
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// minJ, maxJ are computed from J - see icvInitGraySubPix.
|
||
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static inline int icvDataCostFuncGraySubpix( const uchar* a, const uchar* b )
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||
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{
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||
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int va = a[0], vb = b[0];
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||
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int da = icvTruncTab[b[1] - va + 255] + icvTruncTab[va - b[2] + 255];
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int db = icvTruncTab[a[1] - vb + 255] + icvTruncTab[vb - a[2] + 255];
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return icvCutoffSqrTab[MIN(da,db)];
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||
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}
|
||
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|
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static inline int icvSmoothnessCostFunc( int da, int db, int maxR, const int* stabR, int scale )
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||
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{
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||
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return da == db ? 0 : (da == OCCLUDED || db == OCCLUDED ? maxR : stabR[da - db])*scale;
|
||
|
}
|
||
|
|
||
|
static void icvInitGraySubpix( const CvMat* left, const CvMat* right,
|
||
|
CvMat* left3, CvMat* right3 )
|
||
|
{
|
||
|
int k, x, y, rows = left->rows, cols = left->cols;
|
||
|
|
||
|
for( k = 0; k < 2; k++ )
|
||
|
{
|
||
|
const CvMat* src = k == 0 ? left : right;
|
||
|
CvMat* dst = k == 0 ? left3 : right3;
|
||
|
int sstep = src->step;
|
||
|
|
||
|
for( y = 0; y < rows; y++ )
|
||
|
{
|
||
|
const uchar* sptr = src->data.ptr + sstep*y;
|
||
|
const uchar* sptr_prev = y > 0 ? sptr - sstep : sptr;
|
||
|
const uchar* sptr_next = y < rows-1 ? sptr + sstep : sptr;
|
||
|
uchar* dptr = dst->data.ptr + dst->step*y;
|
||
|
int v_prev = sptr[0];
|
||
|
|
||
|
for( x = 0; x < cols; x++, dptr += 3 )
|
||
|
{
|
||
|
int v = sptr[x], v1, minv = v, maxv = v;
|
||
|
|
||
|
v1 = (v + v_prev)/2;
|
||
|
minv = MIN(minv, v1); maxv = MAX(maxv, v1);
|
||
|
v1 = (v + sptr_prev[x])/2;
|
||
|
minv = MIN(minv, v1); maxv = MAX(maxv, v1);
|
||
|
v1 = (v + sptr_next[x])/2;
|
||
|
minv = MIN(minv, v1); maxv = MAX(maxv, v1);
|
||
|
if( x < cols-1 )
|
||
|
{
|
||
|
v1 = (v + sptr[x+1])/2;
|
||
|
minv = MIN(minv, v1); maxv = MAX(maxv, v1);
|
||
|
}
|
||
|
v_prev = v;
|
||
|
dptr[0] = (uchar)v;
|
||
|
dptr[1] = (uchar)minv;
|
||
|
dptr[2] = (uchar)maxv;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
// Optimal K is computed as avg_x(k-th-smallest_d(||I(x)-J(x+d)||)),
|
||
|
// where k = number_of_disparities*0.25.
|
||
|
static float
|
||
|
icvComputeK( CvStereoGCState* state )
|
||
|
{
|
||
|
int x, y, x1, d, i, j, rows = state->left->rows, cols = state->left->cols, n = 0;
|
||
|
int mind = state->minDisparity, nd = state->numberOfDisparities, maxd = mind + nd;
|
||
|
int k = MIN(MAX((nd + 2)/4, 3), nd);
|
||
|
int *arr = (int*)cvStackAlloc(k*sizeof(arr[0])), delta, t, sum = 0;
|
||
|
|
||
|
for( y = 0; y < rows; y++ )
|
||
|
{
|
||
|
const uchar* lptr = state->left->data.ptr + state->left->step*y;
|
||
|
const uchar* rptr = state->right->data.ptr + state->right->step*y;
|
||
|
|
||
|
for( x = 0; x < cols; x++ )
|
||
|
{
|
||
|
for( d = maxd-1, i = 0; d >= mind; d-- )
|
||
|
{
|
||
|
x1 = x - d;
|
||
|
if( (unsigned)x1 >= (unsigned)cols )
|
||
|
continue;
|
||
|
delta = icvDataCostFuncGraySubpix( lptr + x*3, rptr + x1*3 );
|
||
|
if( i < k )
|
||
|
arr[i++] = delta;
|
||
|
else
|
||
|
for( i = 0; i < k; i++ )
|
||
|
if( delta < arr[i] )
|
||
|
CV_SWAP( arr[i], delta, t );
|
||
|
}
|
||
|
delta = arr[0];
|
||
|
for( j = 1; j < i; j++ )
|
||
|
delta = MAX(delta, arr[j]);
|
||
|
sum += delta;
|
||
|
n++;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
return (float)sum/n;
|
||
|
}
|
||
|
|
||
|
static int64 icvComputeEnergy( const CvStereoGCState* state, const CvStereoGCState2* state2,
|
||
|
bool allOccluded )
|
||
|
{
|
||
|
int x, y, rows = state->left->rows, cols = state->left->cols;
|
||
|
int64 E = 0;
|
||
|
const int* dtab = state2->dataCostFuncTab;
|
||
|
int maxR = state2->interactionRadius;
|
||
|
const int* stabR = state2->smoothnessR + CUTOFF;
|
||
|
const int* stabI = state2->smoothnessGrayDiff + 255;
|
||
|
const uchar* left = state->left->data.ptr;
|
||
|
const uchar* right = state->right->data.ptr;
|
||
|
short* dleft = state->dispLeft->data.s;
|
||
|
short* dright = state->dispRight->data.s;
|
||
|
int step = state->left->step;
|
||
|
int dstep = (int)(state->dispLeft->step/sizeof(short));
|
||
|
|
||
|
assert( state->left->step == state->right->step &&
|
||
|
state->dispLeft->step == state->dispRight->step );
|
||
|
|
||
|
if( allOccluded )
|
||
|
return (int64)OCCLUSION_PENALTY*rows*cols*2;
|
||
|
|
||
|
for( y = 0; y < rows; y++, left += step, right += step, dleft += dstep, dright += dstep )
|
||
|
{
|
||
|
for( x = 0; x < cols; x++ )
|
||
|
{
|
||
|
int d = dleft[x], x1, d1;
|
||
|
if( d == OCCLUDED )
|
||
|
E += OCCLUSION_PENALTY;
|
||
|
else
|
||
|
{
|
||
|
x1 = x + d;
|
||
|
if( (unsigned)x1 >= (unsigned)cols )
|
||
|
continue;
|
||
|
d1 = dright[x1];
|
||
|
if( d == -d1 )
|
||
|
E += dtab[icvDataCostFuncGraySubpix( left + x*3, right + x1*3 )];
|
||
|
}
|
||
|
|
||
|
if( x < cols-1 )
|
||
|
{
|
||
|
d1 = dleft[x+1];
|
||
|
E += icvSmoothnessCostFunc(d, d1, maxR, stabR, stabI[left[x*3] - left[x*3+3]] );
|
||
|
}
|
||
|
if( y < rows-1 )
|
||
|
{
|
||
|
d1 = dleft[x+dstep];
|
||
|
E += icvSmoothnessCostFunc(d, d1, maxR, stabR, stabI[left[x*3] - left[x*3+step]] );
|
||
|
}
|
||
|
|
||
|
d = dright[x];
|
||
|
if( d == OCCLUDED )
|
||
|
E += OCCLUSION_PENALTY;
|
||
|
|
||
|
if( x < cols-1 )
|
||
|
{
|
||
|
d1 = dright[x+1];
|
||
|
E += icvSmoothnessCostFunc(d, d1, maxR, stabR, stabI[right[x*3] - right[x*3+3]] );
|
||
|
}
|
||
|
if( y < rows-1 )
|
||
|
{
|
||
|
d1 = dright[x+dstep];
|
||
|
E += icvSmoothnessCostFunc(d, d1, maxR, stabR, stabI[right[x*3] - right[x*3+step]] );
|
||
|
}
|
||
|
assert( E >= 0 );
|
||
|
}
|
||
|
}
|
||
|
|
||
|
return E;
|
||
|
}
|
||
|
|
||
|
static inline void icvAddEdge( GCVtx *x, GCVtx* y, GCEdge* edgeBuf, int nedges, int w, int rw )
|
||
|
{
|
||
|
GCEdge *xy = edgeBuf + nedges, *yx = xy + 1;
|
||
|
|
||
|
assert( x != 0 && y != 0 );
|
||
|
xy->dst = y;
|
||
|
xy->next = x->first;
|
||
|
xy->weight = (short)w;
|
||
|
x->first = nedges;
|
||
|
|
||
|
yx->dst = x;
|
||
|
yx->next = y->first;
|
||
|
yx->weight = (short)rw;
|
||
|
y->first = nedges+1;
|
||
|
}
|
||
|
|
||
|
static inline int icvAddTWeights( GCVtx* vtx, int sourceWeight, int sinkWeight )
|
||
|
{
|
||
|
int w = vtx->weight;
|
||
|
if( w > 0 )
|
||
|
sourceWeight += w;
|
||
|
else
|
||
|
sinkWeight -= w;
|
||
|
vtx->weight = (short)(sourceWeight - sinkWeight);
|
||
|
return MIN(sourceWeight, sinkWeight);
|
||
|
}
|
||
|
|
||
|
static inline int icvAddTerm( GCVtx* x, GCVtx* y, int A, int B, int C, int D,
|
||
|
GCEdge* edgeBuf, int& nedges )
|
||
|
{
|
||
|
int dE = 0, w;
|
||
|
|
||
|
assert(B - A + C - D >= 0);
|
||
|
if( B < A )
|
||
|
{
|
||
|
dE += icvAddTWeights(x, D, B);
|
||
|
dE += icvAddTWeights(y, 0, A - B);
|
||
|
if( (w = B - A + C - D) != 0 )
|
||
|
{
|
||
|
icvAddEdge( x, y, edgeBuf, nedges, 0, w );
|
||
|
nedges += 2;
|
||
|
}
|
||
|
}
|
||
|
else if( C < D )
|
||
|
{
|
||
|
dE += icvAddTWeights(x, D, A + D - C);
|
||
|
dE += icvAddTWeights(y, 0, C - D);
|
||
|
if( (w = B - A + C - D) != 0 )
|
||
|
{
|
||
|
icvAddEdge( x, y, edgeBuf, nedges, w, 0 );
|
||
|
nedges += 2;
|
||
|
}
|
||
|
}
|
||
|
else
|
||
|
{
|
||
|
dE += icvAddTWeights(x, D, A);
|
||
|
if( B != A || C != D )
|
||
|
{
|
||
|
icvAddEdge( x, y, edgeBuf, nedges, B - A, C - D );
|
||
|
nedges += 2;
|
||
|
}
|
||
|
}
|
||
|
return dE;
|
||
|
}
|
||
|
|
||
|
static int64 icvAlphaExpand( int64 Eprev, int alpha, CvStereoGCState* state, CvStereoGCState2* state2 )
|
||
|
{
|
||
|
GCVtx *var, *var1;
|
||
|
int64 E = 0;
|
||
|
int delta, E00=0, E0a=0, Ea0=0, Eaa=0;
|
||
|
int k, a, d, d1, x, y, x1, y1, rows = state->left->rows, cols = state->left->cols;
|
||
|
int nvtx = 0, nedges = 2;
|
||
|
GCVtx* vbuf = (GCVtx*)state->vtxBuf->data.ptr;
|
||
|
GCEdge* ebuf = (GCEdge*)state->edgeBuf->data.ptr;
|
||
|
int maxR = state2->interactionRadius;
|
||
|
const int* dtab = state2->dataCostFuncTab;
|
||
|
const int* stabR = state2->smoothnessR + CUTOFF;
|
||
|
const int* stabI = state2->smoothnessGrayDiff + 255;
|
||
|
const uchar* left0 = state->left->data.ptr;
|
||
|
const uchar* right0 = state->right->data.ptr;
|
||
|
short* dleft0 = state->dispLeft->data.s;
|
||
|
short* dright0 = state->dispRight->data.s;
|
||
|
GCVtx** pleft0 = (GCVtx**)state->ptrLeft->data.ptr;
|
||
|
GCVtx** pright0 = (GCVtx**)state->ptrRight->data.ptr;
|
||
|
int step = state->left->step;
|
||
|
int dstep = (int)(state->dispLeft->step/sizeof(short));
|
||
|
int pstep = (int)(state->ptrLeft->step/sizeof(GCVtx*));
|
||
|
int aa[] = { alpha, -alpha };
|
||
|
|
||
|
//double t = (double)cvGetTickCount();
|
||
|
|
||
|
assert( state->left->step == state->right->step &&
|
||
|
state->dispLeft->step == state->dispRight->step &&
|
||
|
state->ptrLeft->step == state->ptrRight->step );
|
||
|
for( k = 0; k < 2; k++ )
|
||
|
{
|
||
|
ebuf[k].dst = 0;
|
||
|
ebuf[k].next = 0;
|
||
|
ebuf[k].weight = 0;
|
||
|
}
|
||
|
|
||
|
for( y = 0; y < rows; y++ )
|
||
|
{
|
||
|
const uchar* left = left0 + step*y;
|
||
|
const uchar* right = right0 + step*y;
|
||
|
const short* dleft = dleft0 + dstep*y;
|
||
|
const short* dright = dright0 + dstep*y;
|
||
|
GCVtx** pleft = pleft0 + pstep*y;
|
||
|
GCVtx** pright = pright0 + pstep*y;
|
||
|
const uchar* lr[] = { left, right };
|
||
|
const short* dlr[] = { dleft, dright };
|
||
|
GCVtx** plr[] = { pleft, pright };
|
||
|
|
||
|
for( k = 0; k < 2; k++ )
|
||
|
{
|
||
|
a = aa[k];
|
||
|
for( y1 = y+(y>0); y1 <= y+(y<rows-1); y1++ )
|
||
|
{
|
||
|
const short* disp = (k == 0 ? dleft0 : dright0) + y1*dstep;
|
||
|
GCVtx** ptr = (k == 0 ? pleft0 : pright0) + y1*pstep;
|
||
|
for( x = 0; x < cols; x++ )
|
||
|
{
|
||
|
GCVtx* v = ptr[x] = &vbuf[nvtx++];
|
||
|
v->first = 0;
|
||
|
v->weight = disp[x] == (short)(OCCLUDED ? -OCCLUSION_PENALTY2 : 0);
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
for( x = 0; x < cols; x++ )
|
||
|
{
|
||
|
d = dleft[x];
|
||
|
x1 = x + d;
|
||
|
var = pleft[x];
|
||
|
|
||
|
// (left + x, right + x + d)
|
||
|
if( d != alpha && d != OCCLUDED && (unsigned)x1 < (unsigned)cols )
|
||
|
{
|
||
|
var1 = pright[x1];
|
||
|
d1 = dright[x1];
|
||
|
if( d == -d1 )
|
||
|
{
|
||
|
assert( var1 != 0 );
|
||
|
delta = IS_BLOCKED(alpha, d) ? INFINITY : 0;
|
||
|
//add inter edge
|
||
|
E += icvAddTerm( var, var1,
|
||
|
dtab[icvDataCostFuncGraySubpix( left + x*3, right + x1*3 )],
|
||
|
delta, delta, 0, ebuf, nedges );
|
||
|
}
|
||
|
else if( IS_BLOCKED(alpha, d) )
|
||
|
E += icvAddTerm( var, var1, 0, INFINITY, 0, 0, ebuf, nedges );
|
||
|
}
|
||
|
|
||
|
// (left + x, right + x + alpha)
|
||
|
x1 = x + alpha;
|
||
|
if( (unsigned)x1 < (unsigned)cols )
|
||
|
{
|
||
|
var1 = pright[x1];
|
||
|
d1 = dright[x1];
|
||
|
|
||
|
E0a = IS_BLOCKED(d, alpha) ? INFINITY : 0;
|
||
|
Ea0 = IS_BLOCKED(-d1, alpha) ? INFINITY : 0;
|
||
|
Eaa = dtab[icvDataCostFuncGraySubpix( left + x*3, right + x1*3 )];
|
||
|
E += icvAddTerm( var, var1, 0, E0a, Ea0, Eaa, ebuf, nedges );
|
||
|
}
|
||
|
|
||
|
// smoothness
|
||
|
for( k = 0; k < 2; k++ )
|
||
|
{
|
||
|
GCVtx** p = plr[k];
|
||
|
const short* disp = dlr[k];
|
||
|
const uchar* img = lr[k] + x*3;
|
||
|
int scale;
|
||
|
var = p[x];
|
||
|
d = disp[x];
|
||
|
a = aa[k];
|
||
|
|
||
|
if( x < cols - 1 )
|
||
|
{
|
||
|
var1 = p[x+1];
|
||
|
d1 = disp[x+1];
|
||
|
scale = stabI[img[0] - img[3]];
|
||
|
E0a = icvSmoothnessCostFunc( d, a, maxR, stabR, scale );
|
||
|
Ea0 = icvSmoothnessCostFunc( a, d1, maxR, stabR, scale );
|
||
|
E00 = icvSmoothnessCostFunc( d, d1, maxR, stabR, scale );
|
||
|
E += icvAddTerm( var, var1, E00, E0a, Ea0, 0, ebuf, nedges );
|
||
|
}
|
||
|
|
||
|
if( y < rows - 1 )
|
||
|
{
|
||
|
var1 = p[x+pstep];
|
||
|
d1 = disp[x+dstep];
|
||
|
scale = stabI[img[0] - img[step]];
|
||
|
E0a = icvSmoothnessCostFunc( d, a, maxR, stabR, scale );
|
||
|
Ea0 = icvSmoothnessCostFunc( a, d1, maxR, stabR, scale );
|
||
|
E00 = icvSmoothnessCostFunc( d, d1, maxR, stabR, scale );
|
||
|
E += icvAddTerm( var, var1, E00, E0a, Ea0, 0, ebuf, nedges );
|
||
|
}
|
||
|
}
|
||
|
|
||
|
// visibility term
|
||
|
if( d != OCCLUDED && IS_BLOCKED(alpha, -d))
|
||
|
{
|
||
|
x1 = x + d;
|
||
|
if( (unsigned)x1 < (unsigned)cols )
|
||
|
{
|
||
|
if( d != -dleft[x1] )
|
||
|
{
|
||
|
var1 = pleft[x1];
|
||
|
E += icvAddTerm( var, var1, 0, INFINITY, 0, 0, ebuf, nedges );
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
//t = (double)cvGetTickCount() - t;
|
||
|
ebuf[0].weight = ebuf[1].weight = 0;
|
||
|
E += icvGCMaxFlow( vbuf, nvtx, ebuf, state2->orphans, state2->maxOrphans );
|
||
|
|
||
|
if( E < Eprev )
|
||
|
{
|
||
|
for( y = 0; y < rows; y++ )
|
||
|
{
|
||
|
short* dleft = dleft0 + dstep*y;
|
||
|
short* dright = dright0 + dstep*y;
|
||
|
GCVtx** pleft = pleft0 + pstep*y;
|
||
|
GCVtx** pright = pright0 + pstep*y;
|
||
|
for( x = 0; x < cols; x++ )
|
||
|
{
|
||
|
GCVtx* var = pleft[x];
|
||
|
if( var && var->parent && var->t )
|
||
|
dleft[x] = (short)alpha;
|
||
|
|
||
|
var = pright[x];
|
||
|
if( var && var->parent && var->t )
|
||
|
dright[x] = (short)-alpha;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
return MIN(E, Eprev);
|
||
|
}
|
||
|
|
||
|
|
||
|
CV_IMPL void cvFindStereoCorrespondenceGC( const CvArr* _left, const CvArr* _right,
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CvArr* _dispLeft, CvArr* _dispRight, CvStereoGCState* state, int useDisparityGuess )
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{
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CvStereoGCState2 state2;
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state2.orphans = 0;
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state2.maxOrphans = 0;
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CvMat lstub, *left = cvGetMat( _left, &lstub );
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CvMat rstub, *right = cvGetMat( _right, &rstub );
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CvMat dlstub, *dispLeft = cvGetMat( _dispLeft, &dlstub );
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CvMat drstub, *dispRight = cvGetMat( _dispRight, &drstub );
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CvSize size;
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int iter, i, nZeroExpansions = 0;
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CvRNG rng = cvRNG(-1);
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int* disp;
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CvMat _disp;
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int64 E;
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CV_Assert( state != 0 );
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CV_Assert( CV_ARE_SIZES_EQ(left, right) && CV_ARE_TYPES_EQ(left, right) &&
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CV_MAT_TYPE(left->type) == CV_8UC1 );
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CV_Assert( !dispLeft ||
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(CV_ARE_SIZES_EQ(dispLeft, left) && CV_MAT_CN(dispLeft->type) == 1) );
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CV_Assert( !dispRight ||
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(CV_ARE_SIZES_EQ(dispRight, left) && CV_MAT_CN(dispRight->type) == 1) );
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size = cvGetSize(left);
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if( !state->left || state->left->width != size.width || state->left->height != size.height )
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{
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int pcn = (int)(sizeof(GCVtx*)/sizeof(int));
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int vcn = (int)(sizeof(GCVtx)/sizeof(int));
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int ecn = (int)(sizeof(GCEdge)/sizeof(int));
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cvReleaseMat( &state->left );
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cvReleaseMat( &state->right );
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cvReleaseMat( &state->ptrLeft );
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cvReleaseMat( &state->ptrRight );
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cvReleaseMat( &state->dispLeft );
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cvReleaseMat( &state->dispRight );
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state->left = cvCreateMat( size.height, size.width, CV_8UC3 );
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state->right = cvCreateMat( size.height, size.width, CV_8UC3 );
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state->dispLeft = cvCreateMat( size.height, size.width, CV_16SC1 );
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state->dispRight = cvCreateMat( size.height, size.width, CV_16SC1 );
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state->ptrLeft = cvCreateMat( size.height, size.width, CV_32SC(pcn) );
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state->ptrRight = cvCreateMat( size.height, size.width, CV_32SC(pcn) );
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state->vtxBuf = cvCreateMat( 1, size.height*size.width*2, CV_32SC(vcn) );
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state->edgeBuf = cvCreateMat( 1, size.height*size.width*12 + 16, CV_32SC(ecn) );
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}
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if( !useDisparityGuess )
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{
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cvSet( state->dispLeft, cvScalarAll(OCCLUDED));
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cvSet( state->dispRight, cvScalarAll(OCCLUDED));
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}
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else
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{
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CV_Assert( dispLeft && dispRight );
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cvConvert( dispLeft, state->dispLeft );
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cvConvert( dispRight, state->dispRight );
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}
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state2.Ithreshold = state->Ithreshold;
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state2.interactionRadius = state->interactionRadius;
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state2.lambda = cvRound(state->lambda*DENOMINATOR);
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state2.lambda1 = cvRound(state->lambda1*DENOMINATOR);
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state2.lambda2 = cvRound(state->lambda2*DENOMINATOR);
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|
state2.K = cvRound(state->K*DENOMINATOR);
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icvInitStereoConstTabs();
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icvInitGraySubpix( left, right, state->left, state->right );
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|
disp = (int*)cvStackAlloc( state->numberOfDisparities*sizeof(disp[0]) );
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_disp = cvMat( 1, state->numberOfDisparities, CV_32S, disp );
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cvRange( &_disp, state->minDisparity, state->minDisparity + state->numberOfDisparities );
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|
cvRandShuffle( &_disp, &rng );
|
||
|
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|
if( state2.lambda < 0 && (state2.K < 0 || state2.lambda1 < 0 || state2.lambda2 < 0) )
|
||
|
{
|
||
|
float L = icvComputeK(state)*0.2f;
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||
|
state2.lambda = cvRound(L*DENOMINATOR);
|
||
|
}
|
||
|
|
||
|
if( state2.K < 0 )
|
||
|
state2.K = state2.lambda*5;
|
||
|
if( state2.lambda1 < 0 )
|
||
|
state2.lambda1 = state2.lambda*3;
|
||
|
if( state2.lambda2 < 0 )
|
||
|
state2.lambda2 = state2.lambda;
|
||
|
|
||
|
icvInitStereoTabs( &state2 );
|
||
|
|
||
|
E = icvComputeEnergy( state, &state2, !useDisparityGuess );
|
||
|
for( iter = 0; iter < state->maxIters; iter++ )
|
||
|
{
|
||
|
for( i = 0; i < state->numberOfDisparities; i++ )
|
||
|
{
|
||
|
int alpha = disp[i];
|
||
|
int64 Enew = icvAlphaExpand( E, -alpha, state, &state2 );
|
||
|
if( Enew < E )
|
||
|
{
|
||
|
nZeroExpansions = 0;
|
||
|
E = Enew;
|
||
|
}
|
||
|
else if( ++nZeroExpansions >= state->numberOfDisparities )
|
||
|
break;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
if( dispLeft )
|
||
|
cvConvert( state->dispLeft, dispLeft );
|
||
|
if( dispRight )
|
||
|
cvConvert( state->dispRight, dispRight );
|
||
|
|
||
|
cvFree( &state2.orphans );
|
||
|
}
|