Place recognition from disparate views

Rob Frampton, Andrew D Calway

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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We use detected objects as basic features in a semantic place recognition system with the aim of allowing recognition when views are disparate. This is achieved by constructing a 2D place model of object positions and then using training examples to compute the probability that a pair depict the same place. We also generate an estimate of the relative pose of the cameras. Results on a dataset of 40 urban locations show good recognition performance and pose estimation, even for highly disparate views.
Original languageEnglish
Title of host publicationProceedings of the British Machine Vision Conference (BMVC)
Publication statusPublished - Sept 2013


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