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Live Demonstration: A Real-Time Event-Based Fast Corner Detection Demo Based on FPGA

Liu, Min; Kao, Wei-Tse; Delbruck, Tobi (2019). Live Demonstration: A Real-Time Event-Based Fast Corner Detection Demo Based on FPGA. In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Long Beach, CA, USA, 16 July 2019 - 17 July 2019, IEEE.

Abstract

Corner detection is widely used as a pre-processing step for many computer vision (CV) problems. It is well studied in the conventional CV community and many popular methods are still used nowadays such as Harris, FAST, and SIFT. For event cameras like Dynamic Vision Sensors (DVS), similar approaches also have been proposed in recent years. Two of them are event-based Harris (eHARRIS) and event-based FAST (eFAST). This demo presents our recent work in which we implement eFAST on MiniZed FPGA. The power consumption of the whole system is less than 4W and the hardware eFAST consumes about 0.9W. This demo processes at least 5M events per second, and achieves a power-speed improvement factor product of more than 30X compared with CPU implementation of eFAST. This embedded component could be suitable for integration to applications such as drones and autonomous cars that produce high event rates.

Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Scopus Subject Areas:Physical Sciences > Computer Vision and Pattern Recognition
Physical Sciences > Electrical and Electronic Engineering
Language:English
Event End Date:17 July 2019
Deposited On:14 Feb 2020 07:02
Last Modified:16 Jun 2022 07:04
Publisher:IEEE
OA Status:Green
Publisher DOI:https://doi.org/10.1109/CVPRW.2019.00212
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