Cross-Camera View-Overlap Recognition - Alessio Xompero
Cross-Camera View-Overlap Recognition
Alessio Xompero, Andrea Cavallaro
Centre for Intelligent Sensing, Queen Mary University of London (QMUL), U.K.
Presented online at the 2022 International Workshop on Distributed Smart Cameras (IWDSC22) at the European Confence on Computer Vision (ECCV), Tel-Aviv, Israel, 24 October 2022.
We propose a decentralised view-overlap recognition framework that operates across freely moving cameras without the need of a reference 3D map. Each camera independently extracts, aggregates into a hierarchical structure, and shares feature-point descriptors over time. A view overlap is recognised by view-matching and geometric validation to discard wrongly matched views. The proposed framework is generic and can be used with different descriptors. We conduct the experiments on publicly available sequences as well as new sequences we collected with hand-held cameras. We show that Oriented FAST and Rotated BRIEF (ORB) features with Bags of Binary Words within the proposed framework lead to higher precision and a higher or similar accuracy compared to NetVLAD, RootSIFT, and SuperGlue.
ArXiv: https://doi.org/10.48550/arXiv.2208.1...
Webpage: http://www.eecs.qmul.ac.uk/~ax300/xview/