MODELING THE DETECTION CAPABILITY OF HIGH-SPEED SPIKING CAMERAS

被引:5
|
作者
Zhao, Junwei [1 ]
Yu, Zhaofei [1 ]
Ma, Lei [1 ,2 ]
Ding, Ziluo [1 ]
Zhang, Shiliang [1 ]
Tian, Yonghong [1 ]
Huang, Tiejun [1 ,2 ]
机构
[1] Peking Univ, Inst Digital Media, Beijing, Peoples R China
[2] Beijing Acad Artificial Intelligence, Beijing, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Neuromorphic Vision Sensing; Spike Signal Processing; Emerging Multimedia Applications;
D O I
10.1109/ICASSP43922.2022.9747018
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
The novel working principle enables spiking cameras to capture high-speed moving objects. However, the applications of spiking cameras can be affected by many factors, such as brightness intensity, detectable distance, and the maximum speed of moving targets. Improper settings such as weak ambient brightness and too short object-camera distance, will lead to failure in the application of such cameras. To address the issue, this paper proposes a modeling algorithm that studies the detection capability of spiking cameras. The algorithm deduces the maximum detectable speed of spiking cameras corresponding to different scenario settings (e.g., brightness intensity, camera lens, and object-camera distance) based on the basic technical parameters of cameras (e.g., pixel size, spatial and temporal resolution). Thereby, the proper camera settings for various applications can be determined. Extensive experiments verify the effectiveness of the modeling algorithm. To our best knowledge, it is the first work to investigate the detection capability of spiking cameras.
引用
收藏
页码:4653 / 4657
页数:5
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