Sensors, Vol. 19, Pages 4266: Target-Specific Action Classification for Automated Assessment of Human Motor Behavior from Video

Sensors, Vol. 19, Pages 4266: Target-Specific Action Classification for Automated Assessment of Human Motor Behavior from Video Sensors doi: 10.3390/s19194266 Authors: Behnaz Rezaei Yiorgos Christakis Bryan Ho Kevin Thomas Kelley Erb Sarah Ostadabbas Shyamal Patel Objective monitoring and assessment of human motor behavior can improve the diagnosis and management of several medical conditions. Over the past decade, significant advances have been made in the use of wearable technology for continuously monitoring human motor behavior in free-living conditions. However, wearable technology remains ill-suited for applications which require monitoring and interpretation of complex motor behaviors (e.g., involving interactions with the environment). Recent advances in computer vision and deep learning have opened up new possibilities for extracting information from video recordings. In this paper, we present a hierarchical vision-based behavior phenotyping method for classification of basic human actions in video recordings performed using a single RGB camera. Our method addresses challenges associated with tracking multiple human actors and classification of actions in videos recorded in changing environments with different fields of view. We implement a cascaded pose tracker that uses temporal relationships between detections for short-term tracking and appearance based tracklet fusion for long-term tracking. Furthermore, for action classification, we use pose...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research