Semi-Supervised Joint Learning for Hand Gesture Recognition from a Single Color Image

• Main Authors: Chi Xu, Yunkai Jiang, Jun Zhou, Yi Liu
• Format: Article
• Language: English
• Published: MDPI AG 2021-02-01
• Series: Sensors
• Subjects: hand gesture recognition; hand pose estimation; joint learning; shared feature
• Online Access: https://www.mdpi.com/1424-8220/21/3/1007

Hand gesture recognition and hand pose estimation are two closely correlated tasks. In this paper, we propose a deep-learning based approach which jointly learns an intermediate level shared feature for these two tasks, so that the hand gesture recognition task can be benefited from the hand pose estimation task. In the training process, a semi-supervised training scheme is designed to solve the problem of lacking proper annotation. Our approach detects the foreground hand, recognizes the hand gesture, and estimates the corresponding 3D hand pose simultaneously. To evaluate the hand gesture recognition performance of the state-of-the-arts, we propose a challenging hand gesture recognition dataset collected in unconstrained environments. Experimental results show that, the gesture recognition accuracy of ours is significantly boosted by leveraging the knowledge learned from the hand pose estimation task.