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/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2013-, Open Perception, Inc.
*
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of the copyright holder(s) nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
* person_classifier.h
* Created on: Nov 30, 2012
* Author: Matteo Munaro
*/
#ifndef PCL_PEOPLE_PERSON_CLASSIFIER_H_
#define PCL_PEOPLE_PERSON_CLASSIFIER_H_
#include <pcl/people/person_cluster.h>
#include <pcl/people/hog.h>
namespace pcl
{
namespace people
{
template <typename PointT> class PersonClassifier;
template <typename PointT>
class PersonClassifier
{
protected:
/** \brief Height of the image patch to classify. */
int window_height_;
/** \brief Width of the image patch to classify. */
int window_width_;
/** \brief SVM offset. */
float SVM_offset_;
/** \brief SVM weights vector. */
std::vector<float> SVM_weights_;
public:
typedef pcl::PointCloud<PointT> PointCloud;
typedef boost::shared_ptr<PointCloud> PointCloudPtr;
/** \brief Constructor. */
PersonClassifier ();
/** \brief Destructor. */
virtual ~PersonClassifier ();
/** \brief Load SVM parameters from a text file.
*
* \param[in] svm_filename Filename containing SVM parameters.
*
* \return true if SVM has been correctly set, false otherwise.
*/
bool
loadSVMFromFile (std::string svm_filename);
/**
* \brief Set trained SVM for person confidence estimation.
*
* \param[in] window_height Detection window height.
* \param[in] window_width Detection window width.
* \param[in] SVM_weights SVM weights vector.
* \param[in] SVM_offset SVM offset.
*/
void
setSVM (int window_height, int window_width, std::vector<float> SVM_weights, float SVM_offset);
/**
* \brief Get trained SVM for person confidence estimation.
*
* \param[out] window_height Detection window height.
* \param[out] window_width Detection window width.
* \param[out] SVM_weights SVM weights vector.
* \param[out] SVM_offset SVM offset.
*/
void
getSVM (int& window_height, int& window_width, std::vector<float>& SVM_weights, float& SVM_offset);
/**
* \brief Resize an image represented by a pointcloud containing RGB information.
*
* \param[in] input_image A pointer to a pointcloud containing RGB information.
* \param[out] output_image A pointer to the output pointcloud.
* \param[in] width Output width.
* \param[in] height Output height.
*/
void
resize (PointCloudPtr& input_image, PointCloudPtr& output_image,
int width, int height);
/**
* \brief Copies an image and makes a black border around it, where the source image is not present.
*
* \param[in] input_image A pointer to a pointcloud containing RGB information.
* \param[out] output_image A pointer to the output pointcloud.
* \param[in] xmin x coordinate of the top-left point of the bbox to copy from the input image.
* \param[in] ymin y coordinate of the top-left point of the bbox to copy from the input image.
* \param[in] width Output width.
* \param[in] height Output height.
*/
void
copyMakeBorder (PointCloudPtr& input_image, PointCloudPtr& output_image,
int xmin, int ymin, int width, int height);
/**
* \brief Classify the given portion of image.
*
* \param[in] height The height of the image patch to classify, in pixels.
* \param[in] xc The x-coordinate of the center of the image patch to classify, in pixels.
* \param[in] yc The y-coordinate of the center of the image patch to classify, in pixels.
* \param[in] image The whole image (pointer to a point cloud containing RGB information) containing the object to classify.
* \return The classification score given by the SVM.
*/
double
evaluate (float height, float xc, float yc, PointCloudPtr& image);
/**
* \brief Compute person confidence for a given PersonCluster.
*
* \param[in] image The input image (pointer to a point cloud containing RGB information).
* \param[in] bottom Theoretical bottom point of the cluster projected to the image.
* \param[in] top Theoretical top point of the cluster projected to the image.
* \param[in] centroid Theoretical centroid point of the cluster projected to the image.
* \param[in] vertical If true, the sensor is considered to be vertically placed (portrait mode).
* \return The person confidence.
*/
double
evaluate (PointCloudPtr& image, Eigen::Vector3f& bottom, Eigen::Vector3f& top, Eigen::Vector3f& centroid,
bool vertical);
};
} /* namespace people */
} /* namespace pcl */
#include <pcl/people/impl/person_classifier.hpp>
#endif /* PCL_PEOPLE_PERSON_CLASSIFIER_H_ */