Intelligent substation risk behavior detection based on blob and trajectory

Risk behavior detection based on blob and trajectory is presented in this paper for intelligent substation. The features of substation are extracted and clustered to blobs by K-means algorithm. In order to get the description of the blobs, the blobs are divided into danger area and safety area by Conditional Random Fields (CRF) model. Target is detected by optical flow, and then the trajectory of the object is obtained. The blobs description and the trajectory are combined to feature vector. This feature vector is modeled by Hidden Markov Model (HMM). And use these models to detection risk behavior. The experimental results show that risk behavior in intelligent substation can be described accurately.