Ultrafast vision perception by neuromorphic optical flow

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Opis bibliograficzny
Wydane w:	arXiv.org (Sep 10, 2024), p. n/a
1. autor:	Wang, Shengbo
Kolejni autorzy:	Gao, Shuo, Pu, Tongming, Zhao, Liangbing, Arokia Nathan
Wydane:	Cornell University Library, arXiv.org
Hasła przedmiotowe:	Time domain analysis Visual tasks Three dimensional flow Two dimensional flow Optical data processing Data processing Algorithms Visual perception Optical flow (image analysis) Three dimensional motion Visual perception driven algorithms Two dimensional analysis
Dostęp online:	Citation/Abstract Full text outside of ProQuest
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Opis
Streszczenie:	Optical flow is crucial for robotic visual perception, yet current methods primarily operate in a 2D format, capturing movement velocities only in horizontal and vertical dimensions. This limitation results in incomplete motion cues, such as missing regions of interest or detailed motion analysis of different regions, leading to delays in processing high-volume visual data in real-world settings. Here, we report a 3D neuromorphic optical flow method that leverages the time-domain processing capability of memristors to embed external motion features directly into hardware, thereby completing motion cues and dramatically accelerating the computation of movement velocities and subsequent task-specific algorithms. In our demonstration, this approach reduces visual data processing time by an average of 0.3 seconds while maintaining or improving the accuracy of motion prediction, object tracking, and object segmentation. Interframe visual processing is achieved for the first time in UAV scenarios. Furthermore, the neuromorphic optical flow algorithm's flexibility allows seamless integration with existing algorithms, ensuring broad applicability. These advancements open unprecedented avenues for robotic perception, without the trade-off between accuracy and efficiency.
ISSN:	2331-8422
Źródło:	Engineering Database