Caged mice mating behavior detection in surveillance videos

Abstract

The purpose of this study is to develop a computer vision-based method to automatically detect the mating behavior of caged mice in surveillance videos. Previously we took advantage of our developed algorithm and analyzed the objects of mating mice in the consecutive frames, we unprecedentedly showed that, to the best of our knowledge, the mice mating behavior can be automatically detected based on video processing (Lo et al., 2009 [13]). In this paper, we proposed an improved method which monitors the distance between two mating objects and more effectively detects the mating behavior. In addition, a more detailed portrayal of the mating behavior can be further elaborated as a function of the distance patterns in the tails of two caged mice. Experimental results show that the current system can effectively detect the mice mating behavior with the highest precision rate of 96.1%, far better than that of our previously proposed method.