Combining Motion Segmentation and Feature Based Tracking for Object Classification and Anomaly Detection

摘要

We present a novel pipeline for automated visual surveillance system based on utilising conventional adaptive background modelling in-conjunction with optic flow to provide motion sensitive foreground/background segmentation. Furthermore active contours are then used to detect robust motion boundaries within the scene from which PCA is used for object classification. Feature based tracking is then used to build an object and trajectory inventory for the scene from which basic anomaly detection is implemented.