May 8, 2024, 4:46 a.m. | Junkai Niu, Sheng Zhong, Yi Zhou

cs.CV updates on arXiv.org arxiv.org

arXiv:2405.04071v1 Announce Type: cross
Abstract: Direct methods for event-based visual odometry solve the mapping and camera pose tracking sub-problems by establishing implicit data association in a way that the generative model of events is exploited. The main bottlenecks faced by state-of-the-art work in this field include the high computational complexity of mapping and the limited accuracy of tracking. In this paper, we improve our previous direct pipeline \textit{Event-based Stereo Visual Odometry} in terms of accuracy and efficiency. To speed up …

abstract art arxiv association bottlenecks complexity computational cs.cv cs.ro data event events generative mapping solve state tracking type visual work

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