基于神经形态时间对比视觉传感器的高速场景动态嵌入轮廓提取

A. Belbachir, M. Hofstätter, Nenad Milosevic, P. Schön
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引用次数: 4

摘要

本文提出了一种用于高速应用的高效轮廓提取的紧凑视觉系统。通过利用超高的时间分辨率和传感器数据的稀疏表示来响应场景动态,该系统为超高速应用培养了高效的嵌入式计算机视觉。本文的结果显示了传感器在大范围的物体速度(5-40 m/s)下的输出质量,并证明了物体数据量与速度无关以及物体质量的稳定性。讨论了目标速度对高性能嵌入式计算机视觉的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Embedded contours extraction for high-speed scene dynamics based on a neuromorphic temporal contrast vision sensor
The paper presents a compact vision system for efficient contours extraction in high-speed applications. By exploiting the ultra high temporal resolution and the sparse representation of the sensorpsilas data in reacting to scene dynamics, the system fosters efficient embedded computer vision for ultra high-speed applications. The results reported in this paper show the sensor output quality for a wide range of object velocity (5-40 m/s), and demonstrate the object data volume independence from the velocity as well as the steadiness of the object quality. The influence of object velocity on high-performance embedded computer vision is also discussed.
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