The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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Combining Shape and SIFT Features for 3-D Object Detection and Pose Estimation

효과적인 3차원 객체 인식 및 자세 추정을 위한 외형 및 SIFT 특징 정보 결합 기법

  • 탁윤식 (고려대학교 전자컴퓨터공학과) ;
  • 황인준 (고려대학교 전기전자전파공학과)
  • Published : 2010.02.01
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Abstract

Three dimensional (3-D) object detection and pose estimation from a single view query image has been an important issue in various fields such as medical applications, robot vision, and manufacturing automation. However, most of the existing methods are not appropriate in a real time environment since object detection and pose estimation requires extensive information and computation. In this paper, we present a fast 3-D object detection and pose estimation scheme based on surrounding camera view-changed images of objects. Our scheme has two parts. First, we detect images similar to the query image from the database based on the shape feature, and calculate candidate poses. Second, we perform accurate pose estimation for the candidate poses using the scale invariant feature transform (SIFT) method. We earned out extensive experiments on our prototype system and achieved excellent performance, and we report some of the results.

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References

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