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

Min Liu, Wei-Tse Kao, Tobi Delbruck; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019, pp. 0-0

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.

Related Material


[pdf]
[bibtex]
@InProceedings{Liu_2019_CVPR_Workshops,
author = {Liu, Min and Kao, Wei-Tse and Delbruck, Tobi},
title = {Live Demonstration: A Real-Time Event-Based Fast Corner Detection Demo Based on FPGA},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}