504 lines
18 KiB
ReStructuredText
504 lines
18 KiB
ReStructuredText
Camera Calibration and 3D Reconstruction
|
|
========================================
|
|
|
|
.. highlight:: cpp
|
|
|
|
|
|
|
|
gpu::StereoBM_GPU
|
|
-----------------
|
|
.. ocv:class:: gpu::StereoBM_GPU
|
|
|
|
Class computing stereo correspondence (disparity map) using the block matching algorithm. ::
|
|
|
|
class StereoBM_GPU
|
|
{
|
|
public:
|
|
enum { BASIC_PRESET = 0, PREFILTER_XSOBEL = 1 };
|
|
|
|
enum { DEFAULT_NDISP = 64, DEFAULT_WINSZ = 19 };
|
|
|
|
StereoBM_GPU();
|
|
StereoBM_GPU(int preset, int ndisparities = DEFAULT_NDISP,
|
|
int winSize = DEFAULT_WINSZ);
|
|
|
|
void operator() (const GpuMat& left, const GpuMat& right,
|
|
GpuMat& disparity, Stream& stream = Stream::Null());
|
|
|
|
static bool checkIfGpuCallReasonable();
|
|
|
|
int preset;
|
|
int ndisp;
|
|
int winSize;
|
|
|
|
float avergeTexThreshold;
|
|
|
|
...
|
|
};
|
|
|
|
|
|
The class also performs pre- and post-filtering steps: Sobel pre-filtering (if ``PREFILTER_XSOBEL`` flag is set) and low textureness filtering (if ``averageTexThreshols > 0`` ). If ``avergeTexThreshold = 0`` , low textureness filtering is disabled. Otherwise, the disparity is set to 0 in each point ``(x, y)`` , where for the left image
|
|
|
|
.. math::
|
|
\sum HorizontalGradiensInWindow(x, y, winSize) < (winSize \cdot winSize) \cdot avergeTexThreshold
|
|
|
|
This means that the input left image is low textured.
|
|
|
|
.. note::
|
|
|
|
* A basic stereo matching example can be found at opencv_source_code/samples/gpu/stereo_match.cpp
|
|
* A stereo matching example using several GPU's can be found at opencv_source_code/samples/gpu/stereo_multi.cpp
|
|
* A stereo matching example using several GPU's and driver API can be found at opencv_source_code/samples/gpu/driver_api_stereo_multi.cpp
|
|
|
|
gpu::StereoBM_GPU::StereoBM_GPU
|
|
-----------------------------------
|
|
Enables :ocv:class:`gpu::StereoBM_GPU` constructors.
|
|
|
|
.. ocv:function:: gpu::StereoBM_GPU::StereoBM_GPU()
|
|
|
|
.. ocv:function:: gpu::StereoBM_GPU::StereoBM_GPU(int preset, int ndisparities = DEFAULT_NDISP, int winSize = DEFAULT_WINSZ)
|
|
|
|
:param preset: Parameter presetting:
|
|
|
|
* **BASIC_PRESET** Basic mode without pre-processing.
|
|
|
|
* **PREFILTER_XSOBEL** Sobel pre-filtering mode.
|
|
|
|
:param ndisparities: Number of disparities. It must be a multiple of 8 and less or equal to 256.
|
|
|
|
:param winSize: Block size.
|
|
|
|
|
|
|
|
gpu::StereoBM_GPU::operator ()
|
|
----------------------------------
|
|
Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair.
|
|
|
|
.. ocv:function:: void gpu::StereoBM_GPU::operator ()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null())
|
|
|
|
:param left: Left image. Only ``CV_8UC1`` type is supported.
|
|
|
|
:param right: Right image with the same size and the same type as the left one.
|
|
|
|
:param disparity: Output disparity map. It is a ``CV_8UC1`` image with the same size as the input images.
|
|
|
|
:param stream: Stream for the asynchronous version.
|
|
|
|
|
|
|
|
gpu::StereoBM_GPU::checkIfGpuCallReasonable
|
|
-----------------------------------------------
|
|
Uses a heuristic method to estimate whether the current GPU is faster than the CPU in this algorithm. It queries the currently active device.
|
|
|
|
.. ocv:function:: bool gpu::StereoBM_GPU::checkIfGpuCallReasonable()
|
|
|
|
|
|
|
|
gpu::StereoBeliefPropagation
|
|
----------------------------
|
|
.. ocv:class:: gpu::StereoBeliefPropagation
|
|
|
|
Class computing stereo correspondence using the belief propagation algorithm. ::
|
|
|
|
class StereoBeliefPropagation
|
|
{
|
|
public:
|
|
enum { DEFAULT_NDISP = 64 };
|
|
enum { DEFAULT_ITERS = 5 };
|
|
enum { DEFAULT_LEVELS = 5 };
|
|
|
|
static void estimateRecommendedParams(int width, int height,
|
|
int& ndisp, int& iters, int& levels);
|
|
|
|
explicit StereoBeliefPropagation(int ndisp = DEFAULT_NDISP,
|
|
int iters = DEFAULT_ITERS,
|
|
int levels = DEFAULT_LEVELS,
|
|
int msg_type = CV_32F);
|
|
StereoBeliefPropagation(int ndisp, int iters, int levels,
|
|
float max_data_term, float data_weight,
|
|
float max_disc_term, float disc_single_jump,
|
|
int msg_type = CV_32F);
|
|
|
|
void operator()(const GpuMat& left, const GpuMat& right,
|
|
GpuMat& disparity, Stream& stream = Stream::Null());
|
|
void operator()(const GpuMat& data, GpuMat& disparity, Stream& stream = Stream::Null());
|
|
|
|
int ndisp;
|
|
|
|
int iters;
|
|
int levels;
|
|
|
|
float max_data_term;
|
|
float data_weight;
|
|
float max_disc_term;
|
|
float disc_single_jump;
|
|
|
|
int msg_type;
|
|
|
|
...
|
|
};
|
|
|
|
The class implements algorithm described in [Felzenszwalb2006]_ . It can compute own data cost (using a truncated linear model) or use a user-provided data cost.
|
|
|
|
.. note::
|
|
|
|
``StereoBeliefPropagation`` requires a lot of memory for message storage:
|
|
|
|
.. math::
|
|
|
|
width \_ step \cdot height \cdot ndisp \cdot 4 \cdot (1 + 0.25)
|
|
|
|
and for data cost storage:
|
|
|
|
.. math::
|
|
|
|
width\_step \cdot height \cdot ndisp \cdot (1 + 0.25 + 0.0625 + \dotsm + \frac{1}{4^{levels}})
|
|
|
|
``width_step`` is the number of bytes in a line including padding.
|
|
|
|
|
|
|
|
gpu::StereoBeliefPropagation::StereoBeliefPropagation
|
|
---------------------------------------------------------
|
|
Enables the :ocv:class:`gpu::StereoBeliefPropagation` constructors.
|
|
|
|
.. ocv:function:: gpu::StereoBeliefPropagation::StereoBeliefPropagation(int ndisp = DEFAULT_NDISP, int iters = DEFAULT_ITERS, int levels = DEFAULT_LEVELS, int msg_type = CV_32F)
|
|
|
|
.. ocv:function:: gpu::StereoBeliefPropagation::StereoBeliefPropagation(int ndisp, int iters, int levels, float max_data_term, float data_weight, float max_disc_term, float disc_single_jump, int msg_type = CV_32F)
|
|
|
|
:param ndisp: Number of disparities.
|
|
|
|
:param iters: Number of BP iterations on each level.
|
|
|
|
:param levels: Number of levels.
|
|
|
|
:param max_data_term: Threshold for data cost truncation.
|
|
|
|
:param data_weight: Data weight.
|
|
|
|
:param max_disc_term: Threshold for discontinuity truncation.
|
|
|
|
:param disc_single_jump: Discontinuity single jump.
|
|
|
|
:param msg_type: Type for messages. ``CV_16SC1`` and ``CV_32FC1`` types are supported.
|
|
|
|
``StereoBeliefPropagation`` uses a truncated linear model for the data cost and discontinuity terms:
|
|
|
|
.. math::
|
|
|
|
DataCost = data \_ weight \cdot \min ( \lvert Img_Left(x,y)-Img_Right(x-d,y) \rvert , max \_ data \_ term)
|
|
|
|
.. math::
|
|
|
|
DiscTerm = \min (disc \_ single \_ jump \cdot \lvert f_1-f_2 \rvert , max \_ disc \_ term)
|
|
|
|
For more details, see [Felzenszwalb2006]_.
|
|
|
|
By default, :ocv:class:`gpu::StereoBeliefPropagation` uses floating-point arithmetics and the ``CV_32FC1`` type for messages. But it can also use fixed-point arithmetics and the ``CV_16SC1`` message type for better performance. To avoid an overflow in this case, the parameters must satisfy the following requirement:
|
|
|
|
.. math::
|
|
|
|
10 \cdot 2^{levels-1} \cdot max \_ data \_ term < SHRT \_ MAX
|
|
|
|
|
|
|
|
gpu::StereoBeliefPropagation::estimateRecommendedParams
|
|
-----------------------------------------------------------
|
|
Uses a heuristic method to compute the recommended parameters ( ``ndisp``, ``iters`` and ``levels`` ) for the specified image size ( ``width`` and ``height`` ).
|
|
|
|
.. ocv:function:: void gpu::StereoBeliefPropagation::estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels)
|
|
|
|
|
|
|
|
gpu::StereoBeliefPropagation::operator ()
|
|
---------------------------------------------
|
|
Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair or data cost.
|
|
|
|
.. ocv:function:: void gpu::StereoBeliefPropagation::operator ()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null())
|
|
|
|
.. ocv:function:: void gpu::StereoBeliefPropagation::operator ()(const GpuMat& data, GpuMat& disparity, Stream& stream = Stream::Null())
|
|
|
|
:param left: Left image. ``CV_8UC1`` , ``CV_8UC3`` and ``CV_8UC4`` types are supported.
|
|
|
|
:param right: Right image with the same size and the same type as the left one.
|
|
|
|
:param data: User-specified data cost, a matrix of ``msg_type`` type and ``Size(<image columns>*ndisp, <image rows>)`` size.
|
|
|
|
:param disparity: Output disparity map. If ``disparity`` is empty, the output type is ``CV_16SC1`` . Otherwise, the type is retained.
|
|
|
|
:param stream: Stream for the asynchronous version.
|
|
|
|
|
|
|
|
gpu::StereoConstantSpaceBP
|
|
--------------------------
|
|
.. ocv:class:: gpu::StereoConstantSpaceBP
|
|
|
|
Class computing stereo correspondence using the constant space belief propagation algorithm. ::
|
|
|
|
class StereoConstantSpaceBP
|
|
{
|
|
public:
|
|
enum { DEFAULT_NDISP = 128 };
|
|
enum { DEFAULT_ITERS = 8 };
|
|
enum { DEFAULT_LEVELS = 4 };
|
|
enum { DEFAULT_NR_PLANE = 4 };
|
|
|
|
static void estimateRecommendedParams(int width, int height,
|
|
int& ndisp, int& iters, int& levels, int& nr_plane);
|
|
|
|
explicit StereoConstantSpaceBP(int ndisp = DEFAULT_NDISP,
|
|
int iters = DEFAULT_ITERS,
|
|
int levels = DEFAULT_LEVELS,
|
|
int nr_plane = DEFAULT_NR_PLANE,
|
|
int msg_type = CV_32F);
|
|
StereoConstantSpaceBP(int ndisp, int iters, int levels, int nr_plane,
|
|
float max_data_term, float data_weight,
|
|
float max_disc_term, float disc_single_jump,
|
|
int min_disp_th = 0,
|
|
int msg_type = CV_32F);
|
|
|
|
void operator()(const GpuMat& left, const GpuMat& right,
|
|
GpuMat& disparity, Stream& stream = Stream::Null());
|
|
|
|
int ndisp;
|
|
|
|
int iters;
|
|
int levels;
|
|
|
|
int nr_plane;
|
|
|
|
float max_data_term;
|
|
float data_weight;
|
|
float max_disc_term;
|
|
float disc_single_jump;
|
|
|
|
int min_disp_th;
|
|
|
|
int msg_type;
|
|
|
|
bool use_local_init_data_cost;
|
|
|
|
...
|
|
};
|
|
|
|
|
|
The class implements algorithm described in [Yang2010]_. ``StereoConstantSpaceBP`` supports both local minimum and global minimum data cost initialization algorithms. For more details, see the paper mentioned above. By default, a local algorithm is used. To enable a global algorithm, set ``use_local_init_data_cost`` to ``false`` .
|
|
|
|
|
|
|
|
gpu::StereoConstantSpaceBP::StereoConstantSpaceBP
|
|
-----------------------------------------------------
|
|
Enables the :ocv:class:`gpu::StereoConstantSpaceBP` constructors.
|
|
|
|
.. ocv:function:: gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int ndisp = DEFAULT_NDISP, int iters = DEFAULT_ITERS, int levels = DEFAULT_LEVELS, int nr_plane = DEFAULT_NR_PLANE, int msg_type = CV_32F)
|
|
|
|
.. ocv:function:: gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int ndisp, int iters, int levels, int nr_plane, float max_data_term, float data_weight, float max_disc_term, float disc_single_jump, int min_disp_th = 0, int msg_type = CV_32F)
|
|
|
|
:param ndisp: Number of disparities.
|
|
|
|
:param iters: Number of BP iterations on each level.
|
|
|
|
:param levels: Number of levels.
|
|
|
|
:param nr_plane: Number of disparity levels on the first level.
|
|
|
|
:param max_data_term: Truncation of data cost.
|
|
|
|
:param data_weight: Data weight.
|
|
|
|
:param max_disc_term: Truncation of discontinuity.
|
|
|
|
:param disc_single_jump: Discontinuity single jump.
|
|
|
|
:param min_disp_th: Minimal disparity threshold.
|
|
|
|
:param msg_type: Type for messages. ``CV_16SC1`` and ``CV_32FC1`` types are supported.
|
|
|
|
``StereoConstantSpaceBP`` uses a truncated linear model for the data cost and discontinuity terms:
|
|
|
|
.. math::
|
|
|
|
DataCost = data \_ weight \cdot \min ( \lvert I_2-I_1 \rvert , max \_ data \_ term)
|
|
|
|
.. math::
|
|
|
|
DiscTerm = \min (disc \_ single \_ jump \cdot \lvert f_1-f_2 \rvert , max \_ disc \_ term)
|
|
|
|
For more details, see [Yang2010]_.
|
|
|
|
By default, ``StereoConstantSpaceBP`` uses floating-point arithmetics and the ``CV_32FC1`` type for messages. But it can also use fixed-point arithmetics and the ``CV_16SC1`` message type for better performance. To avoid an overflow in this case, the parameters must satisfy the following requirement:
|
|
|
|
.. math::
|
|
|
|
10 \cdot 2^{levels-1} \cdot max \_ data \_ term < SHRT \_ MAX
|
|
|
|
|
|
|
|
gpu::StereoConstantSpaceBP::estimateRecommendedParams
|
|
---------------------------------------------------------
|
|
Uses a heuristic method to compute parameters (ndisp, iters, levelsand nrplane) for the specified image size (widthand height).
|
|
|
|
.. ocv:function:: void gpu::StereoConstantSpaceBP::estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane)
|
|
|
|
|
|
|
|
gpu::StereoConstantSpaceBP::operator ()
|
|
-------------------------------------------
|
|
Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair.
|
|
|
|
.. ocv:function:: void gpu::StereoConstantSpaceBP::operator ()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null())
|
|
|
|
:param left: Left image. ``CV_8UC1`` , ``CV_8UC3`` and ``CV_8UC4`` types are supported.
|
|
|
|
:param right: Right image with the same size and the same type as the left one.
|
|
|
|
:param disparity: Output disparity map. If ``disparity`` is empty, the output type is ``CV_16SC1`` . Otherwise, the output type is ``disparity.type()`` .
|
|
|
|
:param stream: Stream for the asynchronous version.
|
|
|
|
|
|
|
|
gpu::DisparityBilateralFilter
|
|
-----------------------------
|
|
.. ocv:class:: gpu::DisparityBilateralFilter
|
|
|
|
Class refining a disparity map using joint bilateral filtering. ::
|
|
|
|
class CV_EXPORTS DisparityBilateralFilter
|
|
{
|
|
public:
|
|
enum { DEFAULT_NDISP = 64 };
|
|
enum { DEFAULT_RADIUS = 3 };
|
|
enum { DEFAULT_ITERS = 1 };
|
|
|
|
explicit DisparityBilateralFilter(int ndisp = DEFAULT_NDISP,
|
|
int radius = DEFAULT_RADIUS, int iters = DEFAULT_ITERS);
|
|
|
|
DisparityBilateralFilter(int ndisp, int radius, int iters,
|
|
float edge_threshold, float max_disc_threshold,
|
|
float sigma_range);
|
|
|
|
void operator()(const GpuMat& disparity, const GpuMat& image,
|
|
GpuMat& dst, Stream& stream = Stream::Null());
|
|
|
|
...
|
|
};
|
|
|
|
|
|
The class implements [Yang2010]_ algorithm.
|
|
|
|
|
|
|
|
gpu::DisparityBilateralFilter::DisparityBilateralFilter
|
|
-----------------------------------------------------------
|
|
Enables the :ocv:class:`gpu::DisparityBilateralFilter` constructors.
|
|
|
|
.. ocv:function:: gpu::DisparityBilateralFilter::DisparityBilateralFilter(int ndisp = DEFAULT_NDISP, int radius = DEFAULT_RADIUS, int iters = DEFAULT_ITERS)
|
|
|
|
.. ocv:function:: gpu::DisparityBilateralFilter::DisparityBilateralFilter(int ndisp, int radius, int iters, float edge_threshold, float max_disc_threshold, float sigma_range)
|
|
|
|
:param ndisp: Number of disparities.
|
|
|
|
:param radius: Filter radius.
|
|
|
|
:param iters: Number of iterations.
|
|
|
|
:param edge_threshold: Threshold for edges.
|
|
|
|
:param max_disc_threshold: Constant to reject outliers.
|
|
|
|
:param sigma_range: Filter range.
|
|
|
|
|
|
|
|
gpu::DisparityBilateralFilter::operator ()
|
|
----------------------------------------------
|
|
Refines a disparity map using joint bilateral filtering.
|
|
|
|
.. ocv:function:: void gpu::DisparityBilateralFilter::operator ()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst, Stream& stream = Stream::Null())
|
|
|
|
:param disparity: Input disparity map. ``CV_8UC1`` and ``CV_16SC1`` types are supported.
|
|
|
|
:param image: Input image. ``CV_8UC1`` and ``CV_8UC3`` types are supported.
|
|
|
|
:param dst: Destination disparity map. It has the same size and type as ``disparity`` .
|
|
|
|
:param stream: Stream for the asynchronous version.
|
|
|
|
|
|
|
|
gpu::drawColorDisp
|
|
----------------------
|
|
Colors a disparity image.
|
|
|
|
.. ocv:function:: void gpu::drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp, Stream& stream = Stream::Null())
|
|
|
|
:param src_disp: Source disparity image. ``CV_8UC1`` and ``CV_16SC1`` types are supported.
|
|
|
|
:param dst_disp: Output disparity image. It has the same size as ``src_disp`` . The type is ``CV_8UC4`` in ``BGRA`` format (alpha = 255).
|
|
|
|
:param ndisp: Number of disparities.
|
|
|
|
:param stream: Stream for the asynchronous version.
|
|
|
|
This function draws a colored disparity map by converting disparity values from ``[0..ndisp)`` interval first to ``HSV`` color space (where different disparity values correspond to different hues) and then converting the pixels to ``RGB`` for visualization.
|
|
|
|
|
|
|
|
gpu::reprojectImageTo3D
|
|
---------------------------
|
|
Reprojects a disparity image to 3D space.
|
|
|
|
.. ocv:function:: void gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, int dst_cn = 4, Stream& stream = Stream::Null())
|
|
|
|
:param disp: Input disparity image. ``CV_8U`` and ``CV_16S`` types are supported.
|
|
|
|
:param xyzw: Output 3- or 4-channel floating-point image of the same size as ``disp`` . Each element of ``xyzw(x,y)`` contains 3D coordinates ``(x,y,z)`` or ``(x,y,z,1)`` of the point ``(x,y)`` , computed from the disparity map.
|
|
|
|
:param Q: :math:`4 \times 4` perspective transformation matrix that can be obtained via :ocv:func:`stereoRectify` .
|
|
|
|
:param dst_cn: The number of channels for output image. Can be 3 or 4.
|
|
|
|
:param stream: Stream for the asynchronous version.
|
|
|
|
.. seealso:: :ocv:func:`reprojectImageTo3D`
|
|
|
|
|
|
|
|
gpu::solvePnPRansac
|
|
-------------------
|
|
Finds the object pose from 3D-2D point correspondences.
|
|
|
|
.. ocv:function:: void gpu::solvePnPRansac(const Mat& object, const Mat& image, const Mat& camera_mat, const Mat& dist_coef, Mat& rvec, Mat& tvec, bool use_extrinsic_guess=false, int num_iters=100, float max_dist=8.0, int min_inlier_count=100, vector<int>* inliers=NULL)
|
|
|
|
:param object: Single-row matrix of object points.
|
|
|
|
:param image: Single-row matrix of image points.
|
|
|
|
:param camera_mat: 3x3 matrix of intrinsic camera parameters.
|
|
|
|
:param dist_coef: Distortion coefficients. See :ocv:func:`undistortPoints` for details.
|
|
|
|
:param rvec: Output 3D rotation vector.
|
|
|
|
:param tvec: Output 3D translation vector.
|
|
|
|
:param use_extrinsic_guess: Flag to indicate that the function must use ``rvec`` and ``tvec`` as an initial transformation guess. It is not supported for now.
|
|
|
|
:param num_iters: Maximum number of RANSAC iterations.
|
|
|
|
:param max_dist: Euclidean distance threshold to detect whether point is inlier or not.
|
|
|
|
:param min_inlier_count: Flag to indicate that the function must stop if greater or equal number of inliers is achieved. It is not supported for now.
|
|
|
|
:param inliers: Output vector of inlier indices.
|
|
|
|
.. seealso:: :ocv:func:`solvePnPRansac`
|
|
|
|
|
|
|
|
.. [Felzenszwalb2006] Pedro F. Felzenszwalb algorithm [Pedro F. Felzenszwalb and Daniel P. Huttenlocher. *Efficient belief propagation for early vision*. International Journal of Computer Vision, 70(1), October 2006
|
|
|
|
.. [Yang2010] Q. Yang, L. Wang, and N. Ahuja. *A constant-space belief propagation algorithm for stereo matching*. In CVPR, 2010.
|