TY - GEN
T1 - Real-time Hand-object Occlusion for Augmented Reality Using Hand Segmentation and Depth Correction
AU - Wu, Yuhui
AU - Liu, Yue
AU - Wang, Jiajun
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Hand-object occlusion is crucial to enhance the realism of Aug-mented Reality, especially for egocentric hand-object interaction scenes. In this paper, a hand segmentation-based depth correction approach is proposed, which can help to realize real-time hand-object occlusion. We introduce a lightweight convolutional neural net-work to quickly obtain real hand segmentation mask. Based on the hand mask, different strategies are adopted to correct the depth data of hand and non-hand regions, which can implement hand-object occlusion and object-object occlusion simultaneously to deal with complex hand situations during interaction. The experimental re-sults demonstrate the feasibility of our approach presenting visually appealing occlusion effects.
AB - Hand-object occlusion is crucial to enhance the realism of Aug-mented Reality, especially for egocentric hand-object interaction scenes. In this paper, a hand segmentation-based depth correction approach is proposed, which can help to realize real-time hand-object occlusion. We introduce a lightweight convolutional neural net-work to quickly obtain real hand segmentation mask. Based on the hand mask, different strategies are adopted to correct the depth data of hand and non-hand regions, which can implement hand-object occlusion and object-object occlusion simultaneously to deal with complex hand situations during interaction. The experimental re-sults demonstrate the feasibility of our approach presenting visually appealing occlusion effects.
KW - Computer graphics
KW - Computing methodologies
KW - Human computer interaction (HCI)
KW - Human-centered computing
KW - Image manipulation
KW - Image processing
KW - Interaction paradigms-Mixed / augmented reality
UR - http://www.scopus.com/inward/record.url?scp=85159705235&partnerID=8YFLogxK
U2 - 10.1109/VRW58643.2023.00158
DO - 10.1109/VRW58643.2023.00158
M3 - Conference contribution
AN - SCOPUS:85159705235
T3 - Proceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023
SP - 631
EP - 632
BT - Proceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023
Y2 - 25 March 2023 through 29 March 2023
ER -