Robotics: Science and Systems XI

Monocular SLAM Supported Object Recognition

Sudeep Pillai, John Leonard


In this work, we develop a monocular SLAM-aware object recognition system that is able to achieve considerably stronger recognition performance, as compared to classical object recognition systems that function on a frame-by-frame basis. By incorporating several key ideas including multi-view object proposals and efficient feature encoding methods, our proposed system is able to detect and robustly recognize objects in its environment using a single RGB camera in near-constant time. Through experiments, we illustrate the utility of using such a system to effectively detect and recognize objects, incorporating multiple object viewpoint detections into a unified prediction hypothesis. The performance of the proposed recognition system is evaluated on the UW RGB-D Dataset, showing strong recognition performance and scalable run-time performance compared to current state-of-the-art recognition systems.



    AUTHOR    = {Sudeep Pillai AND John Leonard}, 
    TITLE     = {Monocular SLAM Supported Object Recognition}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2015}, 
    ADDRESS   = {Rome, Italy}, 
    MONTH     = {July},
    DOI       = {10.15607/RSS.2015.XI.034}