Merge branch '2.4'
This commit is contained in:
Andrey Kamaev
@@ -5,109 +5,6 @@ Feature Detection and Description
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gpu::SURF_GPU
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-------------
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.. ocv:class:: gpu::SURF_GPU
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Class used for extracting Speeded Up Robust Features (SURF) from an image. ::
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class SURF_GPU
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{
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public:
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enum KeypointLayout
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{
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X_ROW = 0,
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Y_ROW,
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LAPLACIAN_ROW,
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OCTAVE_ROW,
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SIZE_ROW,
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ANGLE_ROW,
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HESSIAN_ROW,
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ROWS_COUNT
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};
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//! the default constructor
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SURF_GPU();
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//! the full constructor taking all the necessary parameters
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explicit SURF_GPU(double _hessianThreshold, int _nOctaves=4,
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int _nOctaveLayers=2, bool _extended=false, float _keypointsRatio=0.01f);
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//! returns the descriptor size in float's (64 or 128)
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int descriptorSize() const;
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//! upload host keypoints to device memory
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void uploadKeypoints(const vector<KeyPoint>& keypoints,
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GpuMat& keypointsGPU);
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//! download keypoints from device to host memory
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void downloadKeypoints(const GpuMat& keypointsGPU,
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vector<KeyPoint>& keypoints);
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//! download descriptors from device to host memory
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void downloadDescriptors(const GpuMat& descriptorsGPU,
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vector<float>& descriptors);
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void operator()(const GpuMat& img, const GpuMat& mask,
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GpuMat& keypoints);
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void operator()(const GpuMat& img, const GpuMat& mask,
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GpuMat& keypoints, GpuMat& descriptors,
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bool useProvidedKeypoints = false,
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bool calcOrientation = true);
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void operator()(const GpuMat& img, const GpuMat& mask,
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std::vector<KeyPoint>& keypoints);
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void operator()(const GpuMat& img, const GpuMat& mask,
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std::vector<KeyPoint>& keypoints, GpuMat& descriptors,
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bool useProvidedKeypoints = false,
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bool calcOrientation = true);
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void operator()(const GpuMat& img, const GpuMat& mask,
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std::vector<KeyPoint>& keypoints,
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std::vector<float>& descriptors,
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bool useProvidedKeypoints = false,
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bool calcOrientation = true);
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void releaseMemory();
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// SURF parameters
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double hessianThreshold;
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int nOctaves;
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int nOctaveLayers;
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bool extended;
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bool upright;
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//! max keypoints = keypointsRatio * img.size().area()
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float keypointsRatio;
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GpuMat sum, mask1, maskSum, intBuffer;
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GpuMat det, trace;
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GpuMat maxPosBuffer;
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};
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The class ``SURF_GPU`` implements Speeded Up Robust Features descriptor. There is a fast multi-scale Hessian keypoint detector that can be used to find the keypoints (which is the default option). But the descriptors can also be computed for the user-specified keypoints. Only 8-bit grayscale images are supported.
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The class ``SURF_GPU`` can store results in the GPU and CPU memory. It provides functions to convert results between CPU and GPU version ( ``uploadKeypoints``, ``downloadKeypoints``, ``downloadDescriptors`` ). The format of CPU results is the same as ``SURF`` results. GPU results are stored in ``GpuMat``. The ``keypoints`` matrix is :math:`\texttt{nFeatures} \times 7` matrix with the ``CV_32FC1`` type.
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* ``keypoints.ptr<float>(X_ROW)[i]`` contains x coordinate of the i-th feature.
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* ``keypoints.ptr<float>(Y_ROW)[i]`` contains y coordinate of the i-th feature.
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* ``keypoints.ptr<float>(LAPLACIAN_ROW)[i]`` contains the laplacian sign of the i-th feature.
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* ``keypoints.ptr<float>(OCTAVE_ROW)[i]`` contains the octave of the i-th feature.
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* ``keypoints.ptr<float>(SIZE_ROW)[i]`` contains the size of the i-th feature.
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* ``keypoints.ptr<float>(ANGLE_ROW)[i]`` contain orientation of the i-th feature.
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* ``keypoints.ptr<float>(HESSIAN_ROW)[i]`` contains the response of the i-th feature.
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The ``descriptors`` matrix is :math:`\texttt{nFeatures} \times \texttt{descriptorSize}` matrix with the ``CV_32FC1`` type.
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The class ``SURF_GPU`` uses some buffers and provides access to it. All buffers can be safely released between function calls.
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.. seealso:: :ocv:class:`SURF`
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gpu::FAST_GPU
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-------------
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.. ocv:class:: gpu::FAST_GPU
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@@ -579,76 +579,6 @@ Releases all inner buffer's memory.
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gpu::VIBE_GPU
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-------------
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.. ocv:class:: gpu::VIBE_GPU
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Class used for background/foreground segmentation. ::
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class VIBE_GPU
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{
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public:
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explicit VIBE_GPU(unsigned long rngSeed = 1234567);
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void initialize(const GpuMat& firstFrame, Stream& stream = Stream::Null());
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void operator()(const GpuMat& frame, GpuMat& fgmask, Stream& stream = Stream::Null());
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void release();
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...
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};
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The class discriminates between foreground and background pixels by building and maintaining a model of the background. Any pixel which does not fit this model is then deemed to be foreground. The class implements algorithm described in [VIBE2011]_.
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gpu::VIBE_GPU::VIBE_GPU
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-----------------------
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The constructor.
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.. ocv:function:: gpu::VIBE_GPU::VIBE_GPU(unsigned long rngSeed = 1234567)
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:param rngSeed: Value used to initiate a random sequence.
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Default constructor sets all parameters to default values.
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gpu::VIBE_GPU::initialize
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-------------------------
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Initialize background model and allocates all inner buffers.
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.. ocv:function:: void gpu::VIBE_GPU::initialize(const GpuMat& firstFrame, Stream& stream = Stream::Null())
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:param firstFrame: First frame from video sequence.
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:param stream: Stream for the asynchronous version.
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gpu::VIBE_GPU::operator()
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-------------------------
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Updates the background model and returns the foreground mask
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.. ocv:function:: void gpu::VIBE_GPU::operator()(const GpuMat& frame, GpuMat& fgmask, Stream& stream = Stream::Null())
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:param frame: Next video frame.
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:param fgmask: The output foreground mask as an 8-bit binary image.
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:param stream: Stream for the asynchronous version.
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gpu::VIBE_GPU::release
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----------------------
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Releases all inner buffer's memory.
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.. ocv:function:: void gpu::VIBE_GPU::release()
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gpu::GMG_GPU
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------------
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.. ocv:class:: gpu::GMG_GPU
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@@ -1209,5 +1139,4 @@ Parse next video frame. Implementation must call this method after new frame was
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.. [MOG2001] P. KadewTraKuPong and R. Bowden. *An improved adaptive background mixture model for real-time tracking with shadow detection*. Proc. 2nd European Workshop on Advanced Video-Based Surveillance Systems, 2001
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.. [MOG2004] Z. Zivkovic. *Improved adaptive Gausian mixture model for background subtraction*. International Conference Pattern Recognition, UK, August, 2004
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.. [ShadowDetect2003] Prati, Mikic, Trivedi and Cucchiarra. *Detecting Moving Shadows...*. IEEE PAMI, 2003
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.. [VIBE2011] O. Barnich and M. Van D Roogenbroeck. *ViBe: A universal background subtraction algorithm for video sequences*. IEEE Transactions on Image Processing, 20(6) :1709-1724, June 2011
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.. [GMG2012] A. Godbehere, A. Matsukawa and K. Goldberg. *Visual Tracking of Human Visitors under Variable-Lighting Conditions for a Responsive Audio Art Installation*. American Control Conference, Montreal, June 2012
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