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500 lines
18 KiB
ReStructuredText
500 lines
18 KiB
ReStructuredText
Camera Calibration and 3D Reconstruction
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========================================
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.. highlight:: cpp
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gpu::StereoBM_GPU
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-----------------
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.. ocv:class:: gpu::StereoBM_GPU
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Class computing stereo correspondence (disparity map) using the block matching algorithm. ::
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class StereoBM_GPU
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{
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public:
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enum { BASIC_PRESET = 0, PREFILTER_XSOBEL = 1 };
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enum { DEFAULT_NDISP = 64, DEFAULT_WINSZ = 19 };
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StereoBM_GPU();
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StereoBM_GPU(int preset, int ndisparities = DEFAULT_NDISP,
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int winSize = DEFAULT_WINSZ);
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void operator() (const GpuMat& left, const GpuMat& right,
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GpuMat& disparity, Stream& stream = Stream::Null());
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static bool checkIfGpuCallReasonable();
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int preset;
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int ndisp;
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int winSize;
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float avergeTexThreshold;
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...
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};
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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
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.. math::
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\sum HorizontalGradiensInWindow(x, y, winSize) < (winSize \cdot winSize) \cdot avergeTexThreshold
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This means that the input left image is low textured.
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gpu::StereoBM_GPU::StereoBM_GPU
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-----------------------------------
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Enables :ocv:class:`gpu::StereoBM_GPU` constructors.
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.. ocv:function:: gpu::StereoBM_GPU::StereoBM_GPU()
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.. ocv:function:: gpu::StereoBM_GPU::StereoBM_GPU(int preset, int ndisparities = DEFAULT_NDISP, int winSize = DEFAULT_WINSZ)
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:param preset: Parameter presetting:
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* **BASIC_PRESET** Basic mode without pre-processing.
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* **PREFILTER_XSOBEL** Sobel pre-filtering mode.
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:param ndisparities: Number of disparities. It must be a multiple of 8 and less or equal to 256.
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:param winSize: Block size.
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gpu::StereoBM_GPU::operator ()
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----------------------------------
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Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair.
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.. ocv:function:: void gpu::StereoBM_GPU::operator ()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null())
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:param left: Left image. Only ``CV_8UC1`` type is supported.
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:param right: Right image with the same size and the same type as the left one.
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:param disparity: Output disparity map. It is a ``CV_8UC1`` image with the same size as the input images.
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:param stream: Stream for the asynchronous version.
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gpu::StereoBM_GPU::checkIfGpuCallReasonable
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-----------------------------------------------
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Uses a heuristic method to estimate whether the current GPU is faster than the CPU in this algorithm. It queries the currently active device.
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.. ocv:function:: bool gpu::StereoBM_GPU::checkIfGpuCallReasonable()
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gpu::StereoBeliefPropagation
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----------------------------
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.. ocv:class:: gpu::StereoBeliefPropagation
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Class computing stereo correspondence using the belief propagation algorithm. ::
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class StereoBeliefPropagation
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{
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public:
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enum { DEFAULT_NDISP = 64 };
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enum { DEFAULT_ITERS = 5 };
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enum { DEFAULT_LEVELS = 5 };
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static void estimateRecommendedParams(int width, int height,
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int& ndisp, int& iters, int& levels);
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explicit StereoBeliefPropagation(int ndisp = DEFAULT_NDISP,
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int iters = DEFAULT_ITERS,
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int levels = DEFAULT_LEVELS,
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int msg_type = CV_32F);
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StereoBeliefPropagation(int ndisp, int iters, int levels,
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float max_data_term, float data_weight,
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float max_disc_term, float disc_single_jump,
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int msg_type = CV_32F);
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void operator()(const GpuMat& left, const GpuMat& right,
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GpuMat& disparity, Stream& stream = Stream::Null());
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void operator()(const GpuMat& data, GpuMat& disparity, Stream& stream = Stream::Null());
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int ndisp;
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int iters;
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int levels;
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float max_data_term;
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float data_weight;
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float max_disc_term;
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float disc_single_jump;
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int msg_type;
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...
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};
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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.
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.. note::
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``StereoBeliefPropagation`` requires a lot of memory for message storage:
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.. math::
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width \_ step \cdot height \cdot ndisp \cdot 4 \cdot (1 + 0.25)
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and for data cost storage:
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.. math::
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width\_step \cdot height \cdot ndisp \cdot (1 + 0.25 + 0.0625 + \dotsm + \frac{1}{4^{levels}})
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``width_step`` is the number of bytes in a line including padding.
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gpu::StereoBeliefPropagation::StereoBeliefPropagation
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---------------------------------------------------------
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Enables the :ocv:class:`gpu::StereoBeliefPropagation` constructors.
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.. ocv:function:: gpu::StereoBeliefPropagation::StereoBeliefPropagation(int ndisp = DEFAULT_NDISP, int iters = DEFAULT_ITERS, int levels = DEFAULT_LEVELS, int msg_type = CV_32F)
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.. 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)
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:param ndisp: Number of disparities.
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:param iters: Number of BP iterations on each level.
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:param levels: Number of levels.
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:param max_data_term: Threshold for data cost truncation.
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:param data_weight: Data weight.
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:param max_disc_term: Threshold for discontinuity truncation.
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:param disc_single_jump: Discontinuity single jump.
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:param msg_type: Type for messages. ``CV_16SC1`` and ``CV_32FC1`` types are supported.
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``StereoBeliefPropagation`` uses a truncated linear model for the data cost and discontinuity terms:
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.. math::
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DataCost = data \_ weight \cdot \min ( \lvert I_2-I_1 \rvert , max \_ data \_ term)
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.. math::
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DiscTerm = \min (disc \_ single \_ jump \cdot \lvert f_1-f_2 \rvert , max \_ disc \_ term)
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For more details, see [Felzenszwalb2006]_.
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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:
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.. math::
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10 \cdot 2^{levels-1} \cdot max \_ data \_ term < SHRT \_ MAX
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gpu::StereoBeliefPropagation::estimateRecommendedParams
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-----------------------------------------------------------
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Uses a heuristic method to compute the recommended parameters ( ``ndisp``, ``iters`` and ``levels`` ) for the specified image size ( ``width`` and ``height`` ).
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.. ocv:function:: void gpu::StereoBeliefPropagation::estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels)
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gpu::StereoBeliefPropagation::operator ()
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---------------------------------------------
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Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair or data cost.
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.. ocv:function:: void gpu::StereoBeliefPropagation::operator ()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null())
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.. ocv:function:: void gpu::StereoBeliefPropagation::operator ()(const GpuMat& data, GpuMat& disparity, Stream& stream = Stream::Null())
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:param left: Left image. ``CV_8UC1`` , ``CV_8UC3`` and ``CV_8UC4`` types are supported.
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:param right: Right image with the same size and the same type as the left one.
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:param data: User-specified data cost, a matrix of ``msg_type`` type and ``Size(<image columns>*ndisp, <image rows>)`` size.
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:param disparity: Output disparity map. If ``disparity`` is empty, the output type is ``CV_16SC1`` . Otherwise, the type is retained.
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:param stream: Stream for the asynchronous version.
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gpu::StereoConstantSpaceBP
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--------------------------
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.. ocv:class:: gpu::StereoConstantSpaceBP
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Class computing stereo correspondence using the constant space belief propagation algorithm. ::
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class StereoConstantSpaceBP
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{
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public:
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enum { DEFAULT_NDISP = 128 };
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enum { DEFAULT_ITERS = 8 };
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enum { DEFAULT_LEVELS = 4 };
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enum { DEFAULT_NR_PLANE = 4 };
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static void estimateRecommendedParams(int width, int height,
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int& ndisp, int& iters, int& levels, int& nr_plane);
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explicit StereoConstantSpaceBP(int ndisp = DEFAULT_NDISP,
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int iters = DEFAULT_ITERS,
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int levels = DEFAULT_LEVELS,
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int nr_plane = DEFAULT_NR_PLANE,
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int msg_type = CV_32F);
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StereoConstantSpaceBP(int ndisp, int iters, int levels, int nr_plane,
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float max_data_term, float data_weight,
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float max_disc_term, float disc_single_jump,
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int min_disp_th = 0,
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int msg_type = CV_32F);
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void operator()(const GpuMat& left, const GpuMat& right,
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GpuMat& disparity, Stream& stream = Stream::Null());
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int ndisp;
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int iters;
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int levels;
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int nr_plane;
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float max_data_term;
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float data_weight;
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float max_disc_term;
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float disc_single_jump;
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int min_disp_th;
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int msg_type;
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bool use_local_init_data_cost;
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...
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};
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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`` .
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gpu::StereoConstantSpaceBP::StereoConstantSpaceBP
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-----------------------------------------------------
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Enables the :ocv:class:`gpu::StereoConstantSpaceBP` constructors.
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.. 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)
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.. 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)
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:param ndisp: Number of disparities.
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:param iters: Number of BP iterations on each level.
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:param levels: Number of levels.
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:param nr_plane: Number of disparity levels on the first level.
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:param max_data_term: Truncation of data cost.
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:param data_weight: Data weight.
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:param max_disc_term: Truncation of discontinuity.
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:param disc_single_jump: Discontinuity single jump.
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:param min_disp_th: Minimal disparity threshold.
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:param msg_type: Type for messages. ``CV_16SC1`` and ``CV_32FC1`` types are supported.
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``StereoConstantSpaceBP`` uses a truncated linear model for the data cost and discontinuity terms:
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.. math::
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DataCost = data \_ weight \cdot \min ( \lvert I_2-I_1 \rvert , max \_ data \_ term)
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.. math::
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DiscTerm = \min (disc \_ single \_ jump \cdot \lvert f_1-f_2 \rvert , max \_ disc \_ term)
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For more details, see [Yang2010]_.
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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:
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.. math::
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10 \cdot 2^{levels-1} \cdot max \_ data \_ term < SHRT \_ MAX
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gpu::StereoConstantSpaceBP::estimateRecommendedParams
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---------------------------------------------------------
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Uses a heuristic method to compute parameters (ndisp, iters, levelsand nrplane) for the specified image size (widthand height).
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.. ocv:function:: void gpu::StereoConstantSpaceBP::estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane)
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gpu::StereoConstantSpaceBP::operator ()
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-------------------------------------------
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Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair.
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.. ocv:function:: void gpu::StereoConstantSpaceBP::operator ()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null())
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:param left: Left image. ``CV_8UC1`` , ``CV_8UC3`` and ``CV_8UC4`` types are supported.
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:param right: Right image with the same size and the same type as the left one.
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:param disparity: Output disparity map. If ``disparity`` is empty, the output type is ``CV_16SC1`` . Otherwise, the output type is ``disparity.type()`` .
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:param stream: Stream for the asynchronous version.
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gpu::DisparityBilateralFilter
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-----------------------------
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.. ocv:class:: gpu::DisparityBilateralFilter
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Class refining a disparity map using joint bilateral filtering. ::
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class CV_EXPORTS DisparityBilateralFilter
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{
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public:
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enum { DEFAULT_NDISP = 64 };
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enum { DEFAULT_RADIUS = 3 };
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enum { DEFAULT_ITERS = 1 };
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explicit DisparityBilateralFilter(int ndisp = DEFAULT_NDISP,
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int radius = DEFAULT_RADIUS, int iters = DEFAULT_ITERS);
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DisparityBilateralFilter(int ndisp, int radius, int iters,
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float edge_threshold, float max_disc_threshold,
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float sigma_range);
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void operator()(const GpuMat& disparity, const GpuMat& image,
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GpuMat& dst, Stream& stream = Stream::Null());
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...
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};
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The class implements [Yang2010]_ algorithm.
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gpu::DisparityBilateralFilter::DisparityBilateralFilter
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-----------------------------------------------------------
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Enables the :ocv:class:`gpu::DisparityBilateralFilter` constructors.
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.. ocv:function:: gpu::DisparityBilateralFilter::DisparityBilateralFilter(int ndisp = DEFAULT_NDISP, int radius = DEFAULT_RADIUS, int iters = DEFAULT_ITERS)
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.. ocv:function:: gpu::DisparityBilateralFilter::DisparityBilateralFilter(int ndisp, int radius, int iters, float edge_threshold, float max_disc_threshold, float sigma_range)
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:param ndisp: Number of disparities.
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:param radius: Filter radius.
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:param iters: Number of iterations.
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:param edge_threshold: Threshold for edges.
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:param max_disc_threshold: Constant to reject outliers.
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:param sigma_range: Filter range.
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gpu::DisparityBilateralFilter::operator ()
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----------------------------------------------
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Refines a disparity map using joint bilateral filtering.
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.. ocv:function:: void gpu::DisparityBilateralFilter::operator ()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst, Stream& stream = Stream::Null())
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:param disparity: Input disparity map. ``CV_8UC1`` and ``CV_16SC1`` types are supported.
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:param image: Input image. ``CV_8UC1`` and ``CV_8UC3`` types are supported.
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:param dst: Destination disparity map. It has the same size and type as ``disparity`` .
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:param stream: Stream for the asynchronous version.
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gpu::drawColorDisp
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----------------------
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Colors a disparity image.
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.. ocv:function:: void gpu::drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp, Stream& stream = Stream::Null())
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:param src_disp: Source disparity image. ``CV_8UC1`` and ``CV_16SC1`` types are supported.
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:param dst_disp: Output disparity image. It has the same size as ``src_disp`` . The type is ``CV_8UC4`` in ``BGRA`` format (alpha = 255).
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:param ndisp: Number of disparities.
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:param stream: Stream for the asynchronous version.
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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.
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gpu::reprojectImageTo3D
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---------------------------
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Reprojects a disparity image to 3D space.
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.. ocv:function:: void gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, int dst_cn = 4, Stream& stream = Stream::Null())
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:param disp: Input disparity image. ``CV_8U`` and ``CV_16S`` types are supported.
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: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.
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:param Q: :math:`4 \times 4` perspective transformation matrix that can be obtained via :ocv:func:`stereoRectify` .
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:param dst_cn: The number of channels for output image. Can be 3 or 4.
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:param stream: Stream for the asynchronous version.
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.. seealso:: :ocv:func:`reprojectImageTo3D`
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gpu::solvePnPRansac
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-------------------
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Finds the object pose from 3D-2D point correspondences.
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.. 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)
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:param object: Single-row matrix of object points.
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:param image: Single-row matrix of image points.
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:param camera_mat: 3x3 matrix of intrinsic camera parameters.
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:param dist_coef: Distortion coefficients. See :ocv:func:`undistortPoints` for details.
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:param rvec: Output 3D rotation vector.
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:param tvec: Output 3D translation vector.
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: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.
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:param num_iters: Maximum number of RANSAC iterations.
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:param max_dist: Euclidean distance threshold to detect whether point is inlier or not.
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: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.
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:param inliers: Output vector of inlier indices.
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.. seealso:: :ocv:func:`solvePnPRansac`
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