Sensors, Vol. 24, Pages 2589: ST-TGR: Spatio-Temporal Representation Learning for Skeleton-Based Teaching Gesture Recognition

Sensors, Vol. 24, Pages 2589: ST-TGR: Spatio-Temporal Representation Learning for Skeleton-Based Teaching Gesture Recognition Sensors doi: 10.3390/s24082589 Authors: Zengzhao Chen Wenkai Huang Hai Liu Zhuo Wang Yuqun Wen Shengming Wang Teaching gesture recognition is a technique used to recognize the hand movements of teachers in classroom teaching scenarios. This technology is widely used in education, including for classroom teaching evaluation, enhancing online teaching, and assisting special education. However, current research on gesture recognition in teaching mainly focuses on detecting the static gestures of individual students and analyzing their classroom behavior. To analyze the teacher’s gestures and mitigate the difficulty of single-target dynamic gesture recognition in multi-person teaching scenarios, this paper proposes skeleton-based teaching gesture recognition (ST-TGR), which learns through spatio-temporal representation. This method mainly uses the human pose estimation technique RTMPose to extract the coordinates of the keypoints of the teacher’s skeleton and then inputs the recognized sequence of the teacher’s skeleton into the MoGRU action recognition network for classifying gesture actions. The MoGRU action recognition module mainly learns the spatio-temporal representation of target actions by stacking a multi-scale bidirectional gated recurrent unit (BiGRU) and using improved attention mechan...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research