Microsaccade-inspired Event Camera for Robotics
Botao He, Ze Wang, Yuan Zhou, Jingxi Chen, Chahat Deep Singh, Haojia, Li, Yuman Gao, Shaojie Shen, Kaiwei Wang, Yanjun Cao, Chao Xu, Yiannis, Aloimonos, Fei Gao, Cornelia Fermuller

TL;DR
Inspired by human microsaccades, the AMI-EV system enhances event camera stability and data quality for robotics perception by integrating a rotating wedge prism to compensate for motion-induced texture fading.
Contribution
This work introduces a novel hardware-software system that mimics microsaccades to improve event camera perception in robotics, addressing intrinsic sensor limitations.
Findings
AMI-EV provides more stable texture perception under motion.
Benchmark results show superior data quality over standard event cameras.
System enables improved low- and high-level robotics vision tasks.
Abstract
Neuromorphic vision sensors or event cameras have made the visual perception of extremely low reaction time possible, opening new avenues for high-dynamic robotics applications. These event cameras' output is dependent on both motion and texture. However, the event camera fails to capture object edges that are parallel to the camera motion. This is a problem intrinsic to the sensor and therefore challenging to solve algorithmically. Human vision deals with perceptual fading using the active mechanism of small involuntary eye movements, the most prominent ones called microsaccades. By moving the eyes constantly and slightly during fixation, microsaccades can substantially maintain texture stability and persistence. Inspired by microsaccades, we designed an event-based perception system capable of simultaneously maintaining low reaction time and stable texture. In this design, a rotating…
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Taxonomy
TopicsMolecular Communication and Nanonetworks · Advanced Memory and Neural Computing · Radiation Effects in Electronics
