Combining distance measures to classify terrain image sequence based on dynamic texture model

Koki Fujita, Naoyuki Ichimura

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

2 被引用数 (Scopus)

抄録

Utilizing image sequences obtained from onboard cameras is important to improve autonomous mobility for planetary rovers. In this paper, we propose a method based on a linear dynamical system model called a Dynamic Texture to classify terrain image sequences which contain different types of properties. Among some physical properties included in image sequences, we focus on static properties such as a soil texture and dynamic properties such as a constant image velocity. Distance measures based on an observability space and a time-series model called an autoregressive (AR) model are used for classifying the properties. A cross-validation test using real image sequences shows that the latter distance measures are more advantageous than the former measures with respect to the dynamic properties. Thus we combine two distance measures specific to different properties to gain the classification performance. Experimental results demonstrate the effectiveness of combining distance measures.

本文言語英語
ホスト出版物のタイトルAIAA Guidance, Navigation, and Control Conference 2012
出版ステータス出版済み - 12 1 2012
イベントAIAA Guidance, Navigation, and Control Conference 2012 - Minneapolis, MN, 米国
継続期間: 8 13 20128 16 2012

その他

その他AIAA Guidance, Navigation, and Control Conference 2012
国/地域米国
CityMinneapolis, MN
Period8/13/128/16/12

All Science Journal Classification (ASJC) codes

  • 航空宇宙工学
  • 制御およびシステム工学
  • 電子工学および電気工学

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