Event Detection from Video Surveillance Data Based on Optical Flow Histogram and High-level Feature Extraction

This paper presents a new approach for event detection from video surveillance data based on optical fow histogram with no prior knowledge of the motion nature. First,we start by estimating the motion from images sequence using optical flow technique. Second, we perform a classification using the histogram of the optical flow vectors and we use a chain coding algorithm that we applied to each class for the spatial segmentation. Finally, we extract a high-level feature from any frame for use in the learning and search events by SVM and HMM. We have tested the developed method on real image sequences, our results are very promising.