Coresets for visual summarization with applications to loop closure
Name
Rus_Coresets for visual.pdf
Size
1.28 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Volkov, Mikhail
Rosman, Guy
Feldman, Dan
Fisher III, John W.
Rus, Daniela L.
Date Issued
May 2015
Journal
Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Volkov, Mikhail, Guy Rosman, Dan Feldman, John W. Fisher, and Daniela Rus. “Coresets for Visual Summarization with Applications to Loop Closure.” 2015 IEEE International Conference on Robotics and Automation (ICRA) (May 2015).
Version
Author's final manuscript
Abstract
In continuously operating robotic systems, efficient representation of the previously seen camera feed is crucial. Using a highly efficient compression coreset method, we formulate a new method for hierarchical retrieval of frames from large video streams collected online by a moving robot. We demonstrate how to utilize the resulting structure for efficient loop-closure by a novel sampling approach that is adaptive to the structure of the video. The same structure also allows us to create a highly-effective search tool for large-scale videos, which we demonstrate in this paper. We show the efficiency of proposed approaches for retrieval and loop closure on standard datasets, and on a large-scale video from a mobile camera.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICRA.2015.7139704
