This is a toolbox that implements rigid object detection by using cascades of nearest convex model classifiers and linear SVM. This toolbox uses LIBOCAS software from http://cmp.felk.cvut.cz/~xfrancv/ocas/html/ for training linear SVM and robust linear hyperplane classifiers. Here you will find two detectors: one for face detection and another for people detection. Our face detector is quite successful (it is much better than Viola&Jones cascade detector in terms of accuracy) although it is slow compared to Viola&Jones face detector since we use sliding window approach and operate in pixel domain. The provided people detector detects standing people and it is not as good as our face detector. We trained it approximately 8000 people images collected from web. Cropped people images are not well-aligned since they are collected by different people. We will provide a more successful people detector soon.
This project was funded by the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant number EEEAG-109E279.
We extended our methodology for multi-pose object detection and still trying to beat state-of-arts in PASCAL VOC databases. Our current detectors are much faster (approx 4 secs per image on images from PASCAL VOC databases without parts detectors). Soon, we will provide the software for multi-pose object detection and a fast state-of-arts pedestrian detector. We will also developing state-of-art profile face detectors. We will provide detectors as well as new profile face detection databases soon. Check our website in 6 months for new software !
Lastly, please read the function descriptions and explanations in demo programs in order to learn their usage. If you find a bug, please send an email to email@example.com