Multiple persons´ action recognition by fast human detection

Recognition of the actions of several persons in a scene is gaining importance for human action analysis. Such a kind of system capable of recognizing human actions in a scene is proposed in this paper. We have adopted a fast human detector using Histograms of Oriented Gradients (HOG) and Support Vector Machine (SVM) to robustly trace individual persons. Person-wise bounding blobs are extracted and individual features are tracked in subsequent frames. The recognition is performed individually by comparing with the known motion templates using a high-speed action database. The technique guarantees improved performance in terms of detection and recognition.