Abstract
n this paper we present an efficient algorithm for camera tracking applicable for mobile devices. In particular, the work is motivated by the limited computational power and memory, precluding the use of existing methods for estimation of the 6-DoF pose of a mobile device (camera) relative to a previously unknown planar object. Similar to existing methods, we introduce a keypoint based approach. We establish a relationship between the object and its image by selecting keypoints on the object, preferably such with a distinctive appearance, and identifying their location within subsequent images. In contrast to existing works, we solve the problem of re-identifying such feature points by robustly learning their
appearance with an on-line learning algorithm. We demonstrate the proposed algorithm, hence not limited to this application, in the context of AR. In particular, we give several qualitative and quantitative evaluations showing the benefits
of the proposed approach
appearance with an on-line learning algorithm. We demonstrate the proposed algorithm, hence not limited to this application, in the context of AR. In particular, we give several qualitative and quantitative evaluations showing the benefits
of the proposed approach
Original language | English |
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Title of host publication | Proceedings of the Computer Vision Winterworkshop |
Publisher | . |
Pages | 7-14 |
Publication status | Published - 2010 |
Event | Computer Vision Winter Workshop: CVWW 2012 - Mala Nedelja, Slovenia Duration: 1 Feb 2012 → 3 Feb 2012 |
Conference
Conference | Computer Vision Winter Workshop |
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Abbreviated title | CVWW 2012 |
Country/Territory | Slovenia |
City | Mala Nedelja |
Period | 1/02/12 → 3/02/12 |
Treatment code (Nähere Zuordnung)
- Basic - Fundamental (Grundlagenforschung)
- Application