Paper: Aug 09,2024
cs.CV
ID:2408.04633
LiDAR-Event Stereo Fusion with Hallucinations
Event stereo matching is an emerging technique to estimate depth from
neuromorphic cameras; however, events are unlikely to trigger in the absence of
motion or the presence of large, untextured regions, making the correspondence
problem extremely challenging. Purposely, we propose integrating a stereo event
camera with a fixed-frequency active sensor -- e.g., a LiDAR -- collecting
sparse depth measurements, overcoming the aforementioned limitations. Such
depth hints are used by hallucinating -- i.e., inserting fictitious events --
the stacks or raw input streams, compensating for the lack of information in
the absence of brightness changes. Our techniques are general, can be adapted
to any structured representation to stack events and outperform
state-of-the-art fusion methods applied to event-based stereo.
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Paper Author: Luca Bartolomei,Matteo Poggi,Andrea Conti,Stefano Mattoccia
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