generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Purpose: completed the feature2d chapter

Browse Source
This commit is contained in:
Elena Fedotova
2011-05-08 15:30:00 +00:00
parent 4f335d18fb
commit 12d98a7d18
7 changed files with 121 additions and 121 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
modules/features2d/doc/object_categorization.rst
View File

@@ -3,7 +3,7 @@ Object Categorization
.. highlight:: cpp
This section describes some approaches based on local 2D features and used to categorize objects.
This section describes approaches based on local 2D features and used to categorize objects.
.. index:: BOWTrainer
@@ -13,7 +13,7 @@ BOWTrainer
----------
.. c:type:: BOWTrainer
Abstract base class for training the ''bag of visual words'' vocabulary from a set of descriptors.
Abstract base class for training the *bag of visual words* vocabulary from a set of descriptors.
For details, see, for example, *Visual Categorization with Bags of Keypoints* by Gabriella Csurka, Christopher R. Dance,
Lixin Fan, Jutta Willamowski, Cedric Bray, 2004. ::
@@ -43,7 +43,7 @@ BOWTrainer::add
-------------------
.. c:function:: void BOWTrainer::add( const Mat\& descriptors )
Adds descriptors to a training set. The training set ise clustered using ``clustermethod`` to construct the vocabulary.
Adds descriptors to a training set. The training set is clustered using ``clustermethod`` to construct the vocabulary.
:param descriptors: Descriptors to add to a training set. Each row of the ``descriptors`` matrix is a descriptor.
@@ -83,7 +83,7 @@ BOWKMeansTrainer
----------------
.. c:type:: BOWKMeansTrainer
:ref:`kmeans` -based class to train visual vocabulary using the ''bag of visual words'' approach ::
:ref:`kmeans` -based class to train visual vocabulary using the *bag of visual words* approach ::
class BOWKMeansTrainer : public BOWTrainer
{
@@ -178,11 +178,11 @@ BOWImgDescriptorExtractor::compute
Computes an image descriptor using the set visual vocabulary.
:param image: Image. Image descriptor is computed for this.
:param image: Image. Descriptor is computed for each image.??
:param keypoints: Keypoints detected in the input image.
:param imgDescriptor: Output computed image descriptor.
:param imgDescriptor: Computed output image descriptor.
:param pointIdxsOfClusters: Indices of keypoints that belong to the cluster. This means that ``pointIdxsOfClusters[i]`` are keypoint indices that belong to the ``i`` -th cluster (word of vocabulary) returned if it is non-zero.