From a8f1b8be21976c2bdb7e808022d893d77744197d Mon Sep 17 00:00:00 2001 From: Elena Fedotova Date: Sat, 18 Jun 2011 20:45:35 +0000 Subject: [PATCH] Purpose: 2nd review cycle - see ?? . --- .../camera_calibration_and_3d_reconstruction.rst | 42 +++++++++++----------- 1 file changed, 21 insertions(+), 21 deletions(-) diff --git a/modules/gpu/doc/camera_calibration_and_3d_reconstruction.rst b/modules/gpu/doc/camera_calibration_and_3d_reconstruction.rst index b8174bd..eea023b 100644 --- a/modules/gpu/doc/camera_calibration_and_3d_reconstruction.rst +++ b/modules/gpu/doc/camera_calibration_and_3d_reconstruction.rst @@ -9,7 +9,7 @@ gpu::StereoBM_GPU ----------------- .. ocv:class:: gpu::StereoBM_GPU -This class computes stereo correspondence (disparity map) using the block matching algorithm. +Class computing stereo correspondence (disparity map) using the block matching algorithm. :: class StereoBM_GPU @@ -57,7 +57,7 @@ gpu::StereoBM_GPU::StereoBM_GPU Enables ``StereoBM_GPU`` constructors. - :param preset: Preset: + :param preset: Parameter presetting: * **BASIC_PRESET** Basic mode without pre-processing. @@ -101,7 +101,7 @@ gpu::StereoBeliefPropagation ---------------------------- .. ocv:class:: gpu::StereoBeliefPropagation -This class computes stereo correspondence using the belief propagation algorithm. :: +Class computing stereo correspondence using the belief propagation algorithm. :: class StereoBeliefPropagation { @@ -144,23 +144,23 @@ This class computes stereo correspondence using the belief propagation algorithm ... }; -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 a truncated linear model) or use a user-provided data cost. +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 a truncated linear model) or use a user-provided data cost. -**Note:** +.. note:: - ``StereoBeliefPropagation`` requires a lot of memory for message storage: + ``StereoBeliefPropagation`` requires a lot of memory for message storage: -.. math:: + .. math:: - width \_ step \cdot height \cdot ndisp \cdot 4 \cdot (1 + 0.25) + width \_ step \cdot height \cdot ndisp \cdot 4 \cdot (1 + 0.25) -and for data cost storage: + and for data cost storage: -.. math:: + .. math:: - width\_step \cdot height \cdot ndisp \cdot (1 + 0.25 + 0.0625 + \dotsm + \frac{1}{4^{levels}}) + 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. + ``width_step`` is the number of bytes in a line including padding. .. index:: gpu::StereoBeliefPropagation::StereoBeliefPropagation @@ -198,7 +198,7 @@ gpu::StereoBeliefPropagation::StereoBeliefPropagation DiscTerm = \min (disc \_ single \_ jump \cdot \lvert f_1-f_2 \rvert , max \_ disc \_ term) -For more details, see [Pedro F. Felzenszwalb and Daniel P. Huttenlocher. Efficient belief propagation for early vision. International Journal of Computer Vision, 70(1), October 2006]. +For more details, 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, :ocv:class:`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: @@ -237,7 +237,7 @@ gpu::StereoBeliefPropagation::operator () .. ocv:function:: void gpu::StereoBeliefPropagation::operator()( const GpuMat& data, GpuMat& disparity, Stream& stream) - :param data: The user-specified data cost, a matrix of ``msg_type`` type and ``Size(*ndisp, )`` size. + :param data: User-specified data cost, a matrix of ``msg_type`` type and ``Size(*ndisp, )`` size. :param disparity: Output disparity map. If the matrix is empty, it is created as the ``CV_16SC1`` matrix. Otherwise, the type is retained. @@ -249,7 +249,7 @@ gpu::StereoConstantSpaceBP -------------------------- .. ocv:class:: gpu::StereoConstantSpaceBP -This class computes stereo correspondence using the constant space belief propagation algorithm. :: +Class computing stereo correspondence using the constant space belief propagation algorithm. :: class StereoConstantSpaceBP { @@ -300,7 +300,7 @@ This class computes stereo correspondence using the constant space belief propag }; -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, see the paper. By default, a local algorithm is used. To enable a global algorithm, set ``use_local_init_data_cost`` to ``false``. +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, 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``. .. index:: gpu::StereoConstantSpaceBP::StereoConstantSpaceBP @@ -310,7 +310,7 @@ gpu::StereoConstantSpaceBP::StereoConstantSpaceBP .. 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) - Enables the StereoConstantSpaceBP constructors. + Enables the ``StereoConstantSpaceBP`` constructors. :param ndisp: Number of disparities. @@ -342,7 +342,7 @@ gpu::StereoConstantSpaceBP::StereoConstantSpaceBP DiscTerm = \min (disc \_ single \_ jump \cdot \lvert f_1-f_2 \rvert , max \_ disc \_ term) -For more details, see [Q. Yang, L. Wang, and N. Ahuja. A constant-space belief propagation algorithm for stereo matching. In CVPR, 2010]. +For more details, see [Q. Yang, L. Wang, and N. Ahuja. *A constant-space belief propagation algorithm for stereo matching*. In CVPR, 2010]. 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: @@ -385,7 +385,7 @@ gpu::DisparityBilateralFilter ----------------------------- .. ocv:class:: gpu::DisparityBilateralFilter -This class refines a disparity map using joint bilateral filtering. :: +Class refinining a disparity map using joint bilateral filtering. :: class CV_EXPORTS DisparityBilateralFilter { @@ -410,7 +410,7 @@ This class refines a disparity map using joint bilateral filtering. :: }; -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]. +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 @@ -490,7 +490,7 @@ gpu::reprojectImageTo3D :param stream: Stream for the asynchronous version. -See Also: :ocv:func:`reprojectImageTo3D` . +.. seealso:: :ocv:func:`reprojectImageTo3D` . .. index:: gpu::solvePnPRansac -- 2.7.4