Dictionary-Based Map Compression for Sparse Feature Maps
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- TANAKA Kanji
- Faculty of Engineering, University of Fukui
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- NAGASAKA Tomomi
- Faculty of Engineering, University of Fukui
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Description
Obtaining a compact representation of a large-size feature map built by mapper robots is a critical issue in recent mobile robotics. This “map compression” problem is explored from a novel perspective of dictionary-based data compression techniques in the paper. The primary contribution of the paper is the proposal of the dictionary-based map compression approach. A map compression system is presented by employing RANSAC map matching and sparse coding as building blocks. The effectiveness levels of the proposed techniques is investigated in terms of map compression ratio, compression speed, the retrieval performance of compressed/decompressed maps, as well as applications to the Kolmogorov complexity.
Journal
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- IEICE Transactions on Information and Systems
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IEICE Transactions on Information and Systems E95-D (2), 604-613, 2012
The Institute of Electronics, Information and Communication Engineers
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Details 詳細情報について
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- CRID
- 1390001204379089664
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- NII Article ID
- 10030611200
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- NII Book ID
- AA10826272
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- ISSN
- 17451361
- 09168532
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
- OpenAIRE
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- Abstract License Flag
- Disallowed