This is not Pedro Felzenszwalb's discriminative part-model algorithm. This is simple AdaBoost. The authors have labeled a bunch of datasets (1000s of them) and

This is not Pedro Felzenszwalb's discriminative part-model algorithm. This is simple AdaBoost. The authors have labeled a bunch of datasets (1000s of them) and are able to detect whatever object. AdaBoost (Viola/Jones) is the most popular Yes/No detector, there is an OpenCV api for it. It used for detecting faces and license plates in commercial applications. Full person detector is nothing but a SVM+HOG descriptor. As a computer vision researcher, I am not impressed by this. It is primarily an api for smartphone app makers who want a binary result for detection. It does not help with scene context analysis. For instance, if I have a big picture of a airplane on a wall, it will detect the airplane.. Does it know that this airplane is in the sky? or on a wall? There are a 1000 failure cases.