Fight detection based on Hidden Markov Model
Dejian Liu, Jinyong Wu, Yike Wang, Jun Wang, Zhuo Gong · 2012
This paper presents a novel approach to detect human fights based on Hidden Markov Model (HMM). We present two HMM models to the problem. The first one is Fight Model, the second is Ordinary Model. According to the motion analysis between people in the scene, features for human behavior have been proposed. Given the observation value of features in time sequence, the probability can be evaluated by two Models. The larger value means that the Model is the suitable one to describe what happens in the scene. Experimental result demonstrats that the method is robust and efficient in detecting human fight behaviors.