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
This means that the input left image is low textured.
Enables ocl::StereoBM_OCL constructors.
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Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair.
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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.
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:
and for data cost storage:
width_step is the number of bytes in a line including padding.
Enables the ocl::StereoBeliefPropagation constructors.
Parameters: |
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StereoBeliefPropagation uses a truncated linear model for the data cost and discontinuity terms:
For more details, see [Felzenszwalb2006].
By default, 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:
Uses a heuristic method to compute the recommended parameters ( ndisp, iters and levels ) for the specified image size ( width and height ).
Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair or data cost.
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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 .
Enables the ocl::StereoConstantSpaceBP constructors.
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StereoConstantSpaceBP uses a truncated linear model for the data cost and discontinuity terms:
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:
Uses a heuristic method to compute parameters (ndisp, iters, levelsand nrplane) for the specified image size (widthand height).
Enables the stereo correspondence operator that finds the disparity for the specified rectified stereo pair.
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