Abstract
Non-line-of-sight (NLOS) sensing is an emerging technique that is capable of detecting objects hidden behind a wall, around corners, or behind other obstacles. However, NLOS tracking of moving objects is challenging due to signal redundancy and background interference. Here, we demonstrate computational neuromorphic imaging with an event camera for NLOS tracking, unaffected by the relay surface, which can efficiently obtain non-redundant information. We show how this sensor, which responds to changes in luminance within dynamic speckle fields, allows us to capture the most relevant events for direct motion estimation. The experimental results confirm that our method has superior performance in terms of efficiency, and accuracy, which greatly benefits from focusing on well-defined NLOS object tracking.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
