Automated recognition of social behavior in rats: The role of feature quality

Abstract

We investigate how video-based recognition of rat social behavior is affected by the quality of the tracking data and the derived feature set. We look at the impact of two common tracking errors – animal misidentification and inaccurate localization of body parts. We further examine how the complexity of representing the articulated body in the features influences the recognition accuracy. Our analyses show that correct identification of the rats is required to accurately recognize their interactions. Precise localization of multiple body points is beneficial for recognizing interactions that are described by a distinct pose. Including pose features only leads to improvement if the tracking algorithm can provide that data reliably.