Spatiotemporal-Memory-Guided Machine Perception for Augmented Reality

被引:0
|
作者
Lin, Jianzhe [1 ]
Chen, Shaoyu
Steers, Bea
Vo, Huy T.
Vo, Huy T.
Silva, Claudio T.
Sun, Qi
机构
[1] NYU, New York, NY 10003 USA
来源
2023 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES ABSTRACTS AND WORKSHOPS, VRW | 2023年
关键词
Perception and cognition; Modeling and Simulation;
D O I
10.1109/VRW58643.2023.00236
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:787 / 788
页数:2
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