Dictionary-based Map Compression for Sparse Feature Maps

摘要：

Obtaining a compact representation of a largesize feature map built by mapper robots is a critical issue in the context of lightweight information sharing as well as Kolmogorov complexity. 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 proposal of the dictionary-based map compression approach. A map compression system is developed using RANSAC map matching and sparse coding as building blocks. Experiments show promising results in terms of map compression ratio, compression speed as well as the retrieval performance of compressed/decompressed maps.

作者: Nagasaka Tomomi Tanaka Kanji

作者单位: Faculty of Engineering,University of Fukui,Japan

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

会议地点: 上海

会议语种:英文

页码: 2329-2336

在线出版日期: 2011-05-09（万方平台首次上网日期，不代表论文的发表时间）