Query-based Visual Attention Algorithm for Object Recognition of A Mobile Robot

이동로봇의 물체인식을 위한 질의 기반 시각 집중 알고리즘

  • Ryu, Gwang-Geun (College of Information and Communications, Hanyang University) ;
  • Lee, Sang-Hoon (Advanced IT Education Program on Industrial Demand, a Part of Brain Korea 21 Project at Hanyang University) ;
  • Suh, Il-Hong (College of Information and Communications, Hanyang University)
  • 류광근 (한양대학교 정보통신학과) ;
  • 이상훈 (BK21 수요지향적 정보기술 전문인력양성사업단) ;
  • 서일홍 (한양대학교 정보통신학과)
  • Published : 2007.01.25

Abstract

In this paper, we propose a query-based visual attention algorithm for effective object finding of a vision-based mobile robot. This algorithm is developed by extending conventional bottom-up visual attention algorithms. In our proposed algorithm various conspicuity maps are merged to make a saliency map, where weighting values are determined by query-dependent object properties. The saliency map is then used to find possible attentive location of queried object. To show the validities of our proposed algorithm, several objects are employed to compare performances of our proposed algorithm with those of conventional bottom-up approaches. Here, as one of exemplar query-dependent object property, color property is used.

본 논문에서는 로봇이 태스크와 관련된 부분에 시각 집중을 하도록 하기 위해서 기존의 상향식 주목 알고리즘을 확장한 질의 기반 시각 집중 알고리즘을 제안한다. 질의 기반 시각 집중 알고리즘은 로봇이 수행 할 태스크와 관련한 물체를 질의하면 그 물체의 속성을 분석하여 여러 종류의 도드라짐(Conspicuity) 영상 지도에 적용될 가중치 값을 작성한다. 그리고 가중치를 이용하여 도드라짐 영상 지도를을 합성한 Saliency 영상 지도를 작성하여 기존의 주목 알고리즘과 비교 평가를 수행하였다. 여기서는 일예로서 질의 물체의 속성을 색으로 사용하였다.

Keywords

References

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