Camera Calibration and 3d Reconstruction ======================================== .. highlight:: cpp .. index:: gpu::StereoBM_GPU gpu::StereoBM_GPU ----------------- .. cpp:class:: gpu::StereoBM_GPU The class for computing stereo correspondence using 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); void operator() (const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream & stream); static bool checkIfGpuCallReasonable(); int preset; int ndisp; int winSize; float avergeTexThreshold; ... }; This class computes the disparity map using block matching algorithm. The class also performs pre- and post- filtering steps: sobel prefiltering (if ``PREFILTER_XSOBEL`` flag is set) and low textureness filtering (if ``averageTexThreshols`` :math:`>` 0). If ``avergeTexThreshold = 0`` low textureness filtering is disabled, otherwise disparity is set to 0 in each point ``(x, y)`` where for left image .. math:: \sum HorizontalGradiensInWindow(x, y, winSize) < (winSize \cdot winSize) \cdot avergeTexThreshold i.e. input left image is low textured. .. index:: gpu::StereoBM_GPU::StereoBM_GPU gpu::StereoBM_GPU::StereoBM_GPU ----------------------------------- .. cpp:function:: gpu::StereoBM_GPU::StereoBM_GPU() .. cpp:function:: gpu::StereoBM_GPU::StereoBM_GPU(int preset, int ndisparities = DEFAULT_NDISP, int winSize = DEFAULT_WINSZ) ``StereoBM_GPU`` constructors. :param preset: Preset: * **BASIC_PRESET** Without preprocessing. * **PREFILTER_XSOBEL** Sobel prefilter. :param ndisparities: Number of disparities. Must be a multiple of 8 and less or equal then 256. :param winSize: Block size. .. index:: gpu::StereoBM_GPU::operator () gpu::StereoBM_GPU::operator () ---------------------------------- .. cpp:function:: void gpu::StereoBM_GPU::operator() (const GpuMat& left, const GpuMat& right, GpuMat& disparity) .. cpp:function:: void gpu::StereoBM_GPU::operator() (const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream& stream) The stereo correspondence operator. Finds the disparity for the specified rectified stereo pair. :param left: Left image; supports only ``CV_8UC1`` type. :param right: Right image with the same size and the same type as the left one. :param disparity: Output disparity map. It will be ``CV_8UC1`` image with the same size as the input images. :param stream: Stream for the asynchronous version. .. index:: gpu::StereoBM_GPU::checkIfGpuCallReasonable gpu::StereoBM_GPU::checkIfGpuCallReasonable ----------------------------------------------- .. cpp:function:: bool gpu::StereoBM_GPU::checkIfGpuCallReasonable() Some heuristics that tries to estmate if the current GPU will be faster then CPU in this algorithm. It queries current active device. .. index:: gpu::StereoBeliefPropagation gpu::StereoBeliefPropagation ---------------------------- .. cpp:class:: gpu::StereoBeliefPropagation The class for computing stereo correspondence using 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); void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream); void operator()(const GpuMat& data, GpuMat& disparity); void operator()(const GpuMat& data, GpuMat& disparity, Stream& stream); 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 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.]. It can compute own data cost (using truncated linear model) or use user-provided data cost. **Please note:** ``StereoBeliefPropagation`` requires a lot of memory: .. math:: width\_step \cdot height \cdot ndisp \cdot 4 \cdot (1 + 0.25) for message storage and .. math:: width\_step \cdot height \cdot ndisp \cdot (1 + 0.25 + 0.0625 + \dotsm + \frac{1}{4^{levels}} for data cost storage. ``width_step`` is the number of bytes in a line including the padding. .. index:: gpu::StereoBeliefPropagation::StereoBeliefPropagation gpu::StereoBeliefPropagation::StereoBeliefPropagation --------------------------------------------------------- .. cpp:function:: gpu::StereoBeliefPropagation::StereoBeliefPropagation(int ndisp = DEFAULT_NDISP, int iters = DEFAULT_ITERS, int levels = DEFAULT_LEVELS, int msg_type = CV_32F) .. cpp: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) ``StereoBeliefPropagation`` constructors. :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. Supports ``CV_16SC1`` and ``CV_32FC1``. :cpp:class:`StereoBeliefPropagation` uses truncated linear model for the data cost and discontinuity term: .. 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 please see [Pedro F. Felzenszwalb and Daniel P. Huttenlocher. Efficient belief propagation for early vision. International Journal of Computer Vision, 70(1), October 2006.]. By default :cpp:class:`StereoBeliefPropagation` uses floating-point arithmetics and ``CV_32FC1`` type for messages. But also it can use fixed-point arithmetics and ``CV_16SC1`` type for messages for better perfomance. To avoid overflow in this case, the parameters must satisfy .. math:: 10 \cdot 2^{levels-1} \cdot max\_data\_term < SHRT\_MAX .. index:: gpu::StereoBeliefPropagation::estimateRecommendedParams gpu::StereoBeliefPropagation::estimateRecommendedParams ----------------------------------------------------------- .. cpp:function:: void gpu::StereoBeliefPropagation::estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels) Some heuristics that tries to compute recommended parameters (``ndisp``, ``iters`` and ``levels``) for specified image size (``width`` and ``height``). .. index:: gpu::StereoBeliefPropagation::operator () gpu::StereoBeliefPropagation::operator () --------------------------------------------- .. cpp:function:: void gpu::StereoBeliefPropagation::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity) .. cpp:function:: void gpu::StereoBeliefPropagation::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream) The stereo correspondence operator. Finds the disparity for the specified rectified stereo pair or data cost. :param left: Left image; supports ``CV_8UC1``, ``CV_8UC3`` and ``CV_8UC4`` types. :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 output type will be ``CV_16SC1``, otherwise output type will be ``disparity.type()``. :param stream: Stream for the asynchronous version. .. cpp:function:: void StereoBeliefPropagation::operator()(const GpuMat& data, GpuMat& disparity) .. cpp:function:: void StereoBeliefPropagation::operator()(const GpuMat& data, GpuMat& disparity, Stream& stream) :param data: The user specified data cost. It must have ``msg_type`` type and :math:`\texttt{imgRows} \cdot \texttt{ndisp} \times \texttt{imgCols}` size. :param disparity: Output disparity map. If ``disparity`` is empty output type will be ``CV_16SC1``, otherwise output type will be ``disparity.type()``. :param stream: Stream for the asynchronous version. .. index:: gpu::StereoConstantSpaceBP gpu::StereoConstantSpaceBP -------------------------- .. cpp:class:: gpu::StereoConstantSpaceBP The class for computing stereo correspondence using 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); void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream); 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 Q. Yang algorithm [Q. Yang, L. Wang, and N. Ahuja. A constant-space belief propagation algorithm for stereo matching. In CVPR, 2010]. ``StereoConstantSpaceBP`` supports both local minimum and global minimum data cost initialization algortihms. For more details please see the paper. By default local algorithm is used, and to enable global algorithm set ``use_local_init_data_cost`` to false. .. index:: gpu::StereoConstantSpaceBP::StereoConstantSpaceBP gpu::StereoConstantSpaceBP::StereoConstantSpaceBP ----------------------------------------------------- .. cpp: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) .. cpp: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) ``StereoConstantSpaceBP`` constructors. :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. Supports ``CV_16SC1`` and ``CV_32FC1``. :cpp:class:`StereoConstantSpaceBP` uses truncated linear model for the data cost and discontinuity term: .. 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 please see [Q. Yang, L. Wang, and N. Ahuja. A constant-space belief propagation algorithm for stereo matching. In CVPR, 2010]. By default :cpp:class:`StereoConstantSpaceBP` uses floating-point arithmetics and ``CV_32FC1`` type for messages. But also it can use fixed-point arithmetics and ``CV_16SC1`` type for messages for better perfomance. To avoid overflow in this case, the parameters must satisfy .. math:: 10 \cdot 2^{levels-1} \cdot max\_data\_term < SHRT\_MAX .. index:: gpu::StereoConstantSpaceBP::estimateRecommendedParams gpu::StereoConstantSpaceBP::estimateRecommendedParams --------------------------------------------------------- .. cpp:function:: void gpu::StereoConstantSpaceBP::estimateRecommendedParams( int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane) Some heuristics that tries to compute parameters (``ndisp``, ``iters``, ``levels`` and ``nr_plane``) for specified image size (``width`` and ``height``). .. index:: gpu::StereoConstantSpaceBP::operator () gpu::StereoConstantSpaceBP::operator () ------------------------------------------- .. cpp:function:: void gpu::StereoConstantSpaceBP::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity) .. cpp:function:: void gpu::StereoConstantSpaceBP::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream) The stereo correspondence operator. Finds the disparity for the specified rectified stereo pair. :param left: Left image; supports ``CV_8UC1``, ``CV_8UC3`` and ``CV_8UC4`` types. :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 output type will be ``CV_16SC1``, otherwise output type will be ``disparity.type()``. :param stream: Stream for the asynchronous version. .. index:: gpu::DisparityBilateralFilter gpu::DisparityBilateralFilter ----------------------------- .. cpp:class:: gpu::DisparityBilateralFilter The class for disparity map refinement using joint bilateral filtering. :: class 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); void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst, Stream& stream); ... }; The class implements Q. Yang algorithm [Q. Yang, L. Wang, and N. Ahuja. A constant-space belief propagation algorithm for stereo matching. In CVPR, 2010]. .. index:: gpu::DisparityBilateralFilter::DisparityBilateralFilter gpu::DisparityBilateralFilter::DisparityBilateralFilter ----------------------------------------------------------- .. cpp:function:: gpu::DisparityBilateralFilter::DisparityBilateralFilter(int ndisp = DEFAULT_NDISP, int radius = DEFAULT_RADIUS, int iters = DEFAULT_ITERS) .. cpp:function:: gpu::DisparityBilateralFilter::DisparityBilateralFilter(int ndisp, int radius, int iters, float edge_threshold, float max_disc_threshold, float sigma_range) ``DisparityBilateralFilter`` constructors. :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. .. index:: gpu::DisparityBilateralFilter::operator () gpu::DisparityBilateralFilter::operator () ---------------------------------------------- .. cpp:function:: void gpu::DisparityBilateralFilter::operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst) .. cpp:function:: void gpu::DisparityBilateralFilter::operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst, Stream& stream) Refines disparity map using joint bilateral filtering. :param disparity: Input disparity map; supports ``CV_8UC1`` and ``CV_16SC1`` types. :param image: Input image; supports ``CV_8UC1`` and ``CV_8UC3`` types. :param dst: Destination disparity map; will have the same size and type as ``disparity``. :param stream: Stream for the asynchronous version. .. index:: gpu::drawColorDisp gpu::drawColorDisp ---------------------- .. cpp:function:: void gpu::drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp) .. cpp:function:: void gpu::drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp, const Stream& stream) Does coloring of disparity image. :param src_disp: Source disparity image. Supports ``CV_8UC1`` and ``CV_16SC1`` types. :param dst_disp: Output disparity image. Will have the same size as ``src_disp`` and ``CV_8UC4`` type in ``BGRA`` format (alpha = 255). :param ndisp: Number of disparities. :param stream: Stream for the asynchronous version. This function converts :math:`[0..ndisp)` interval to :math:`[0..240, 1, 1]` in ``HSV`` color space, than convert ``HSV`` color space to ``RGB``. .. index:: gpu::reprojectImageTo3D gpu::reprojectImageTo3D --------------------------- .. cpp:function:: void gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q) .. cpp:function:: void gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, const Stream& stream) Reprojects disparity image to 3D space. :param disp: Input disparity image; supports ``CV_8U`` and ``CV_16S`` types. :param xyzw: Output 4-channel floating-point image of the same size as ``disp``. Each element of ``xyzw(x,y)`` will contain the 3D coordinates ``(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 :c:func:`stereoRectify`. :param stream: Stream for the asynchronous version. See also: :c:func:`reprojectImageTo3D`. .. index:: gpu::solvePnPRansac gpu::solvePnPRansac ------------------- .. cpp: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* inliers=NULL) Finds the object pose from the 3D-2D point correspondences. :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 :c:func:`undistortPoints` for details. :param rvec: Output 3D rotation vector. :param tvec: Output 3D translation vector. :param use_extrinsic_guess: Indicates the function must use ``rvec`` and ``tvec`` as initial transformation guess. It isn't 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: Indicates the function must stop if greater or equal number of inliers is achieved. It isn't supported for now. :param inliers: Output vector of inlier indices. See also :c:func:`solvePnPRansac`.