Camera Calibration and 3D Reconstruction ======================================== .. highlight:: cpp ocl::StereoBM_OCL --------------------- .. ocv:class:: ocl::StereoBM_OCL Class computing stereo correspondence (disparity map) using the block matching algorithm. :: class CV_EXPORTS StereoBM_OCL { public: enum { BASIC_PRESET = 0, PREFILTER_XSOBEL = 1 }; enum { DEFAULT_NDISP = 64, DEFAULT_WINSZ = 19 }; //! the default constructor StereoBM_OCL(); //! the full constructor taking the camera-specific preset, number of disparities and the SAD window size. ndisparities must be multiple of 8. StereoBM_OCL(int preset, int ndisparities = DEFAULT_NDISP, int winSize = DEFAULT_WINSZ); //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair //! Output disparity has CV_8U type. void operator() ( const oclMat &left, const oclMat &right, oclMat &disparity); //! Some heuristics that tries to estmate // if current GPU will be faster then CPU in this algorithm. // It queries current active device. static bool checkIfGpuCallReasonable(); int preset; int ndisp; int winSize; // If avergeTexThreshold == 0 => post procesing is disabled // If avergeTexThreshold != 0 then disparity is set 0 in each point (x,y) where for left image // SumOfHorizontalGradiensInWindow(x, y, winSize) < (winSize * winSize) * avergeTexThreshold // i.e. input left image is low textured. float avergeTexThreshold; private: /* hidden */ }; 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. ocl::StereoBM_OCL::StereoBM_OCL ----------------------------------- Enables :ocv:class:`ocl::StereoBM_OCL` constructors. .. ocv:function:: ocl::StereoBM_OCL::StereoBM_OCL() .. ocv:function:: ocl::StereoBM_OCL::StereoBM_OCL(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. ocl::StereoBM_OCL::operator () ---------------------------------- Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair. .. ocv:function:: void ocl::StereoBM_OCL::operator ()(const oclMat& left, const oclMat& right, oclMat& disparity) :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. ocl::StereoBM_OCL::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 ocl::StereoBM_OCL::checkIfGpuCallReasonable() ocl::StereoBeliefPropagation -------------------------------- .. ocv:class:: ocl::StereoBeliefPropagation Class computing stereo correspondence using the belief propagation algorithm. :: class CV_EXPORTS 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_16S); 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 oclMat &left, const oclMat &right, oclMat &disparity); void operator()(const oclMat &data, oclMat &disparity); int ndisp; int iters; int levels; float max_data_term; float data_weight; float max_disc_term; float disc_single_jump; int msg_type; private: /* hidden */ }; 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. ocl::StereoBeliefPropagation::StereoBeliefPropagation --------------------------------------------------------- Enables the :ocv:class:`ocl::StereoBeliefPropagation` constructors. .. ocv:function:: ocl::StereoBeliefPropagation::StereoBeliefPropagation(int ndisp = DEFAULT_NDISP, int iters = DEFAULT_ITERS, int levels = DEFAULT_LEVELS, int msg_type = CV_16S) .. ocv:function:: ocl::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:`ocl::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 ocl::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 ocl::StereoBeliefPropagation::estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels) ocl::StereoBeliefPropagation::operator () --------------------------------------------- Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair or data cost. .. ocv:function:: void ocl::StereoBeliefPropagation::operator ()(const oclMat& left, const oclMat& right, oclMat& disparity) .. ocv:function:: void ocl::StereoBeliefPropagation::operator ()(const oclMat& data, oclMat& disparity) :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(*ndisp, )`` size. :param disparity: Output disparity map. If ``disparity`` is empty, the output type is ``CV_16SC1`` . Otherwise, the type is retained. ocl::StereoConstantSpaceBP ------------------------------ .. ocv:class:: ocl::StereoConstantSpaceBP Class computing stereo correspondence using the constant space belief propagation algorithm. :: class CV_EXPORTS 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 oclMat &left, const oclMat &right, oclMat &disparity); 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; private: /* hidden */ }; 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`` . ocl::StereoConstantSpaceBP::StereoConstantSpaceBP ----------------------------------------------------- Enables the :ocv:class:`ocl::StereoConstantSpaceBP` constructors. .. ocv:function:: ocl::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:: ocl::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 ocl::StereoConstantSpaceBP::estimateRecommendedParams --------------------------------------------------------- Uses a heuristic method to compute parameters (ndisp, iters, levelsand nrplane) for the specified image size (widthand height). .. ocv:function:: void ocl::StereoConstantSpaceBP::estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane) ocl::StereoConstantSpaceBP::operator () ------------------------------------------- Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair. .. ocv:function:: void ocl::StereoConstantSpaceBP::operator ()(const oclMat& left, const oclMat& right, oclMat& disparity) :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()`` .