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. 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 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 [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(*ndisp, )`` 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 algortihms. 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:: 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 perfomance. 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 refinining 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* 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.