Vehicles detection using sensor fusion

Hiroomi Takizawa, Kenichi Yamada, Toshio Ito

研究成果: Paper査読

22 被引用数 (Scopus)

抄録

The sensor fusion method is more robust than the method by using a single sensor. So sensor fusion is effective to vehicle recognition at complex scene. But, if each sensing data processed individually for most stage, recognition performance is not always good. In this paper, we propose the extensible and generalized fusion method. First, fusion vector which is combined between image sensor data and laser radar data at primitive level is prepared. We regard fusion vector as sensing data by one robust sensor. Next, fusion vector is compared with discriminated dictionary. We report efficiency of our method at complex scene which recognition error tend to occur by using a single sensor.

本文言語English
ページ238-243
ページ数6
出版ステータスPublished - 2004
外部発表はい
イベント2004 IEEE Intelligent Vehicles Symposium - Parma, Italy
継続期間: 2004 6 142004 6 17

Conference

Conference2004 IEEE Intelligent Vehicles Symposium
CountryItaly
CityParma
Period04/6/1404/6/17

ASJC Scopus subject areas

  • Modelling and Simulation
  • Automotive Engineering
  • Computer Science Applications

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