Canine Behavior Interpretation Framework Using Deep Graph Model

Humans have long aspired to understand dog behavior. While research on the Calming signal has achieved substantial progress in understanding dog behavior, it remains an unfamiliar concept to non-expertise. Therefore, in this paper, we introduce a framework for analyzing dog behavior, which defines the interrelationship between dog postures through a graph model without any additional devices but a camera. First of all, our framework classifies the dog posture in frame units, using a machine learning model based on the position information of the dog’s body part in the video captured by the camera. We then analyze dog behavior using graph models that define interrelationships among classified dog postures. We expect that our approach will help non-expertise to understand dog behavior.