Course Project
Anomaly detection is an important topic in transportation system. Based on traffic video records, this paper compares the difference between sparse models and low rank as well as sparse model to frame the traffic anomaly detection problem. A new feature is proposed to represent trajectories of different car motions. Sparse reconstruction methods were adopted to detect abnormal events. Two methods were tested out in solving the low rank and sparse problem and their efficiency were validated and discussed in the end.