TY - GEN
T1 - Spatiotemporal-Memory-Guided Machine Perception for Augmented Reality
AU - Lin, Jianzhe
AU - Chen, Shaoyu
AU - Steers, Bea
AU - Vo, Huy T.
AU - Silva, Claudio T.
AU - Sun, Qi
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Augmented Reality (AR) devices are equipped with advanced sensors such as panoramic cameras. They can see or hear what humans cannot. The superior sensing capabilities - together with machine perception models - enable promising AR-based human assistants in daily tasks. Human task performance progressively enhances with accumulated memory, such as with observed objects' location in working memory, and training in long-term memory. We transform this cognitive nature into real-time machine perception models tailored for human-assisting AR applications. Instead of running machine perception models on each consecutive frame, we leverage the egocentric AR cameras to reconstruct a '4D memory map', which mimics the human spatiotemporal memory.
AB - Augmented Reality (AR) devices are equipped with advanced sensors such as panoramic cameras. They can see or hear what humans cannot. The superior sensing capabilities - together with machine perception models - enable promising AR-based human assistants in daily tasks. Human task performance progressively enhances with accumulated memory, such as with observed objects' location in working memory, and training in long-term memory. We transform this cognitive nature into real-time machine perception models tailored for human-assisting AR applications. Instead of running machine perception models on each consecutive frame, we leverage the egocentric AR cameras to reconstruct a '4D memory map', which mimics the human spatiotemporal memory.
KW - Modeling and Simulation
KW - Perception and cognition
KW - cognitive nature
KW - memory
KW - real time machine perception
UR - http://www.scopus.com/inward/record.url?scp=85159700013&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85159700013&partnerID=8YFLogxK
U2 - 10.1109/VRW58643.2023.00236
DO - 10.1109/VRW58643.2023.00236
M3 - Conference contribution
AN - SCOPUS:85159700013
T3 - Proceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023
SP - 787
EP - 788
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 -