ObjectDet software - learning and detection of visual object classes
Participant : Ivan Laptev.
ObjectDet is an open source efficient c++ implementation of object detection that extends our previous method  . The software achieves object detection at the approximate rate of 10 frames per second on 320×240 images on a modest pc . The accuracy of the method was ranked among the top ones in The PASCAL Visual Object Classes Challenges 2006 and 2007 (voc 2006, voc 2007). The detection is achieved with a “scanning window” classifier applied to different positions and scales of the image. The underlying AdaBoost classifier is trained from histogram features computed on rectangle-annotated object images. Variations in object views can be handled by training separate classifiers for different views of the object. Different types of histogram features including Histograms of Oriented Gradient (hog ), second-order derivative histograms and color histograms are implemented and can be used in a complementary way for increased performance.
Earlier version of the software with pre-trained classifiers is available for download from http://www.irisa.fr/vista/Equipe/People/Laptev/download.html . An updated release including the module for object training is planed to be made available before the end of 2007. Linux and Windows platforms are supported.