Breaking the Frame: Visual Place Recognition by Overlap Prediction

• URL: http://arxiv.org/abs/2406.16204v2
• Date: Mon, 07 Oct 2024 13:11:05 GMT
• Title: Breaking the Frame: Visual Place Recognition by Overlap Prediction
• Authors: Tong Wei, Philipp Lindenberger, Jiri Matas, Daniel Barath,
• Abstract summary: We propose a novel visual place recognition approach based on overlap prediction, called VOP. VOP proceeds co-visible image sections by obtaining patch-level embeddings using a Vision Transformer backbone. Our approach uses a voting mechanism to assess overlap scores for potential database images.
• Score: 53.17564423756082
• License:
• Abstract: Visual place recognition methods struggle with occlusions and partial visual overlaps. We propose a novel visual place recognition approach based on overlap prediction, called VOP, shifting from traditional reliance on global image similarities and local features to image overlap prediction. VOP proceeds co-visible image sections by obtaining patch-level embeddings using a Vision Transformer backbone and establishing patch-to-patch correspondences without requiring expensive feature detection and matching. Our approach uses a voting mechanism to assess overlap scores for potential database images. It provides a nuanced image retrieval metric in challenging scenarios. Experimental results show that VOP leads to more accurate relative pose estimation and localization results on the retrieved image pairs than state-of-the-art baselines on a number of large-scale, real-world indoor and outdoor benchmarks. The code is available at https://github.com/weitong8591/vop.git.

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