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FAB-MAP: Appearance-Based Place Recognition and Mapping using a Learned Visual Vocabulary Model

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FAB-MAP: Appearance-Based Place Recognition and Mapping using a Learned Visual Vocabulary Model
We present an overview of FAB-MAP, an algorithm for place recognition and mapping developed for infrastructure-free mobile robot navigation in large environments. The system allows a robot to identify when it is revisiting a previously seen location, on the basis of imagery captured by the robot's camera. We outline a complete probabilistic framework for the task, which is applicable even in visually repetitive environments where many locations may appear identical. Our work introduces a number of technical innovations - notably we demonstrate that place recognition performance can be improved by learning an approximation to the joint distribution over visual elements. We also investigate several principled approaches to making the system robust in visually repetitive environments, and define an efficient bail-out strategy for multi-hypothesis testing to improve system speed. Our model has been shown to substantially outperform standard tf-idf ranking on our task of interest. We ...
Mark Joseph Cummins, Paul M. Newman
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where ICML
Authors Mark Joseph Cummins, Paul M. Newman
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