Video database system for studying animal behavior

Classification of farm animal behaviors are based upon oral or written descriptions of the activity that an animal is engaged in. The quantification of animal behavior for research requires that an individual recognize and code the behavior of the animal under study. The classification of these behaviors can be subjective and may differ among observers. Illustrated guides to animal behavior do not convey the motion associated with most behaviors. Video based guides offer a subjective method of quantifying behaviors with real time demonstrations of the components that make up a behavior. In this paper, we propose an animal behavior video database system which can automatically extract animal motion information from the input animal activity video clip by a multi-object tracking and reasoning system. The extracted information is then analyzed and described using a set of standard animal behavior terms we are developing. The behavior description is used to automatically annotate the given video clip, and serves as the content-based index. The user of the system is able to use a keywork description of the behavior to retrieve the corresponding video object. The intended applications of the system are animal and veterinary science education, and animal behavior research. The prototype system is built for swine and will be extended to other farm animal species.