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Automatic confidence adjustment of visual cues in model-based camera tracking
- Park, Hanhoon;
- Oh, Jihyun;
- Seo, Byung-Kuk;
- Park, Jong-Il
WEB OF SCIENCE
3SCOPUS
6초록
Model-based camera tracking is a technology that estimates a precise camera pose based on visual cues (e.g., feature points, edges) extracted from camera images given a 3D scene model and a rough camera pose. This paper proposes an automatic method for flexibly adjusting the confidence of visual cues in model-based camera tracking. The adjustment is based on the conditions of the target object/scene and the reliability of the initial or previous camera pose. Under uncontrolled or less-controlled working environments, the proposed object-adaptive tracking method works flexibly at 20 frames per second on an ultra mobile personal computer (UMPC) with an average tracking error within 3 pixels when the camera image resolution is 320 by 240 pixels. This capability enabled the proposed method to be successfully applied to a mobile augmented reality (AR) guidance system for a museum.
키워드
- 제목
- Automatic confidence adjustment of visual cues in model-based camera tracking
- 저자
- Park, Hanhoon; Oh, Jihyun; Seo, Byung-Kuk; Park, Jong-Il
- DOI
- 10.1002/cav.321
- 발행일
- 2010-03
- 유형
- Article; Proceedings Paper
- 권
- 21
- 호
- 2
- 페이지
- 69 ~ 79