This paper proposes a new method for estimating and maintaining over time the pose of a single Pan-Tilt-Zoom camera (PTZ). This is achieved firstly by building offline a keypoints database of the scene; then, in the online step, a coarse localization is obtained from camera odometry and finally refined by visual landmarks matching. A maintenance step is also performed at runtime to keep updated the geometry and appearance of the map. At the present state-of-the-art, there are no methods addressing the problem of being operative for a long period of time. Also, differently from our proposal these methods do not take into account for variations in focal length. Experimental evaluation shows that the proposed approach makes it possible to deliver stable camera pose tracking over time with hundreds of thousand landmarks, which can be kept updated at runtime.

Device tagged feature based localization and mapping of wide areas with a PTZ camera / Alberto Del Bimbo; Giuseppe Lisanti; Iacopo Masi; Federico Pernici. - ELETTRONICO. - (2010), pp. 39-44. (Intervento presentato al convegno International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) SISM tenutosi a San Francisco (USA) nel 13/06/2010-18/06/2010) [10.1109/CVPRW.2010.5543172].

Device tagged feature based localization and mapping of wide areas with a PTZ camera

DEL BIMBO, ALBERTO;LISANTI, GIUSEPPE;MASI, IACOPO;PERNICI, FEDERICO
2010

Abstract

This paper proposes a new method for estimating and maintaining over time the pose of a single Pan-Tilt-Zoom camera (PTZ). This is achieved firstly by building offline a keypoints database of the scene; then, in the online step, a coarse localization is obtained from camera odometry and finally refined by visual landmarks matching. A maintenance step is also performed at runtime to keep updated the geometry and appearance of the map. At the present state-of-the-art, there are no methods addressing the problem of being operative for a long period of time. Also, differently from our proposal these methods do not take into account for variations in focal length. Experimental evaluation shows that the proposed approach makes it possible to deliver stable camera pose tracking over time with hundreds of thousand landmarks, which can be kept updated at runtime.
2010
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) SISM
San Francisco (USA)
13/06/2010-18/06/2010
Alberto Del Bimbo; Giuseppe Lisanti; Iacopo Masi; Federico Pernici
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/427327
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