HashHeat: An O(C) Complexity Hashing-based Filter for Dynamic Vision Sensor

被引：0

作者：

Guo, Shasha ^{[1
]}

Kang, Ziyang ^{[1
]}

Wang, Lei ^{[1
]}

Li, Shiming ^{[1
]}

Xu, Weixia ^{[1
]}

机构：

[1] Natl Univ Def Technol, Coll Comp Sci & Technol, Changsha 410073, Hunan, Peoples R China

来源：

2020 25TH ASIA AND SOUTH PACIFIC DESIGN AUTOMATION CONFERENCE, ASP-DAC 2020 | 2020年

基金：

中国国家自然科学基金; 国家重点研发计划;

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Neuromorphic event-based dynamic vision sensors (DVS) have much faster sampling rates and a higher dynamic range than frame-based imagers. However, they are sensitive to background activity (BA) events which are unwanted. We propose HashHeat, a hashing-based BA filter with O(C) complexity. It is the first spatiotemporal filter that doesn't scale with the DVS output size N and doesn't store the 32-bits timestamps. HashHeat consumes 100x less memory and increases the signal to noise ratio by 15x compared to previous designs.

引用

页码：452 / 457

页数：6

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