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263 lines
9.5 KiB
263 lines
9.5 KiB
Latent SVM |
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Discriminatively Trained Part Based Models for Object Detection |
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--------------------------------------------------------------- |
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The object detector described below has been initially proposed by |
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P.F. Felzenszwalb in [Felzenszwalb2010]_. It is based on a |
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Dalal-Triggs detector that uses a single filter on histogram of |
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oriented gradients (HOG) features to represent an object category. |
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This detector uses a sliding window approach, where a filter is |
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applied at all positions and scales of an image. The first |
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innovation is enriching the Dalal-Triggs model using a |
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star-structured part-based model defined by a "root" filter |
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(analogous to the Dalal-Triggs filter) plus a set of parts filters |
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and associated deformation models. The score of one of star models |
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at a particular position and scale within an image is the score of |
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the root filter at the given location plus the sum over parts of the |
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maximum, over placements of that part, of the part filter score on |
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its location minus a deformation cost easuring the deviation of the |
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part from its ideal location relative to the root. Both root and |
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part filter scores are defined by the dot product between a filter |
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(a set of weights) and a subwindow of a feature pyramid computed |
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from the input image. Another improvement is a representation of the |
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class of models by a mixture of star models. The score of a mixture |
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model at a particular position and scale is the maximum over |
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components, of the score of that component model at the given |
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location. |
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In OpenCV there are C implementation of Latent SVM and C++ wrapper of it. |
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C version is the structure :ocv:struct:`CvObjectDetection` and a set of functions |
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working with this structure (see :ocv:func:`cvLoadLatentSvmDetector`, |
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:ocv:func:`cvReleaseLatentSvmDetector`, :ocv:func:`cvLatentSvmDetectObjects`). |
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C++ version is the class :ocv:class:`LatentSvmDetector` and has slightly different |
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functionality in contrast with C version - it supports loading and detection |
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of several models. |
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There are two examples of Latent SVM usage: ``samples/c/latentsvmdetect.cpp`` |
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and ``samples/cpp/latentsvm_multidetect.cpp``. |
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.. highlight:: c |
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CvLSVMFilterPosition |
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-------------------- |
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.. ocv:struct:: CvLSVMFilterPosition |
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Structure describes the position of the filter in the feature pyramid. |
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.. ocv:member:: unsigned int l |
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level in the feature pyramid |
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.. ocv:member:: unsigned int x |
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x-coordinate in level l |
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.. ocv:member:: unsigned int y |
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y-coordinate in level l |
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CvLSVMFilterObject |
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------------------ |
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.. ocv:struct:: CvLSVMFilterObject |
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Description of the filter, which corresponds to the part of the object. |
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.. ocv:member:: CvLSVMFilterPosition V |
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ideal (penalty = 0) position of the partial filter |
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from the root filter position (V_i in the paper) |
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.. ocv:member:: float fineFunction[4] |
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vector describes penalty function (d_i in the paper) |
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pf[0] * x + pf[1] * y + pf[2] * x^2 + pf[3] * y^2 |
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.. ocv:member:: int sizeX, sizeY |
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Rectangular map (sizeX x sizeY), |
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every cell stores feature vector (dimension = p) |
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.. ocv:member:: int numFeatures |
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number of features |
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.. ocv:member:: float *H |
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matrix of feature vectors to set and get |
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feature vectors (i,j) used formula H[(j * sizeX + i) * p + k], |
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where k - component of feature vector in cell (i, j) |
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CvLatentSvmDetector |
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------------------- |
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.. ocv:struct:: CvLatentSvmDetector |
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Structure contains internal representation of trained Latent SVM detector. |
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.. ocv:member:: int num_filters |
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total number of filters (root plus part) in model |
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.. ocv:member:: int num_components |
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number of components in model |
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.. ocv:member:: int* num_part_filters |
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array containing number of part filters for each component |
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.. ocv:member:: CvLSVMFilterObject** filters |
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root and part filters for all model components |
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.. ocv:member:: float* b |
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biases for all model components |
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.. ocv:member:: float score_threshold |
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confidence level threshold |
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CvObjectDetection |
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----------------- |
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.. ocv:struct:: CvObjectDetection |
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Structure contains the bounding box and confidence level for detected object. |
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.. ocv:member:: CvRect rect |
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bounding box for a detected object |
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.. ocv:member:: float score |
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confidence level |
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cvLoadLatentSvmDetector |
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----------------------- |
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Loads trained detector from a file. |
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.. ocv:function:: CvLatentSvmDetector* cvLoadLatentSvmDetector(const char* filename) |
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:param filename: Name of the file containing the description of a trained detector |
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cvReleaseLatentSvmDetector |
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-------------------------- |
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Release memory allocated for CvLatentSvmDetector structure. |
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.. ocv:function:: void cvReleaseLatentSvmDetector(CvLatentSvmDetector** detector) |
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:param detector: CvLatentSvmDetector structure to be released |
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cvLatentSvmDetectObjects |
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------------------------ |
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Find rectangular regions in the given image that are likely to contain objects |
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and corresponding confidence levels. |
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.. ocv:function:: CvSeq* cvLatentSvmDetectObjects(IplImage* image, CvLatentSvmDetector* detector, CvMemStorage* storage, float overlap_threshold, int numThreads) |
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:param image: image |
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:param detector: LatentSVM detector in internal representation |
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:param storage: Memory storage to store the resultant sequence of the object candidate rectangles |
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:param overlap_threshold: Threshold for the non-maximum suppression algorithm |
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:param numThreads: Number of threads used in parallel version of the algorithm |
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.. highlight:: cpp |
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LatentSvmDetector |
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----------------- |
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.. ocv:class:: LatentSvmDetector |
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This is a C++ wrapping class of Latent SVM. It contains internal representation of several |
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trained Latent SVM detectors (models) and a set of methods to load the detectors and detect objects |
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using them. |
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LatentSvmDetector::ObjectDetection |
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---------------------------------- |
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.. ocv:class:: LatentSvmDetector::ObjectDetection |
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Structure contains the detection information. |
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.. ocv:member:: Rect rect |
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bounding box for a detected object |
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.. ocv:member:: float score |
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confidence level |
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.. ocv:member:: int classID |
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class (model or detector) ID that detect an object |
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LatentSvmDetector::LatentSvmDetector |
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------------------------------------ |
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Two types of constructors. |
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.. ocv:function:: LatentSvmDetector::LatentSvmDetector() |
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.. ocv:function:: LatentSvmDetector::LatentSvmDetector(const vector<string>& filenames, const vector<string>& classNames=vector<string>()) |
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:param filenames: A set of filenames storing the trained detectors (models). Each file contains one model. See examples of such files here /opencv_extra/testdata/cv/latentsvmdetector/models_VOC2007/. |
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:param classNames: A set of trained models names. If it's empty then the name of each model will be constructed from the name of file containing the model. E.g. the model stored in "/home/user/cat.xml" will get the name "cat". |
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LatentSvmDetector::~LatentSvmDetector |
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------------------------------------ |
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Destructor. |
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.. ocv:function:: LatentSvmDetector::~LatentSvmDetector() |
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LatentSvmDetector::~clear |
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------------------------- |
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Clear all trained models and their names stored in an class object. |
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.. ocv:function:: void LatentSvmDetector::clear() |
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LatentSvmDetector::load |
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----------------------- |
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Load the trained models from given ``.xml`` files and return ``true`` if at least one model was loaded. |
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.. ocv:function:: bool LatentSvmDetector::load(const vector<string>& filenames, const vector<string>& classNames) |
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:param filenames: A set of filenames storing the trained detectors (models). Each file contains one model. See examples of such files here /opencv_extra/testdata/cv/latentsvmdetector/models_VOC2007/. |
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:param classNames: A set of trained models names. If it's empty then the name of each model will be constructed from the name of file containing the model. E.g. the model stored in "/home/user/cat.xml" will get the name "cat". |
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LatentSvmDetector::detect |
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------------------------- |
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Find rectangular regions in the given image that are likely to contain objects of loaded classes (models) |
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and corresponding confidence levels. |
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.. ocv:function:: void LatentSvmDetector::detect( const Mat& image, vector<ObjectDetection>& objectDetections, float overlapThreshold=0.5, int numThreads=-1 ) |
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:param image: An image. |
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:param objectDetections: The detections: rectangulars, scores and class IDs. |
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:param overlapThreshold: Threshold for the non-maximum suppression algorithm. |
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:param numThreads: Number of threads used in parallel version of the algorithm. |
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LatentSvmDetector::getClassNames |
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-------------------------------- |
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Return the class (model) names that were passed in constructor or method ``load`` or extructed from models filenames in those methods. |
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.. ocv:function:: const vector<string>& LatentSvmDetector::getClassNames() const |
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LatentSvmDetector::getClassCount |
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-------------------------------- |
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Return a count of loaded models (classes). |
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.. ocv:function:: size_t getClassCount() const |
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.. [Felzenszwalb2010] Felzenszwalb, P. F. and Girshick, R. B. and McAllester, D. and Ramanan, D. *Object Detection with Discriminatively Trained Part Based Models*. PAMI, vol. 32, no. 9, pp. 1627-1645, September 2010 |
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