DocumentCode :
2461233
Title :
Synthetic Aperture Tracking: Tracking through Occlusions
Author :
Joshi, Neel ; Avidan, Shai ; Matusik, Wojciech ; Kriegman, David J.
Author_Institution :
Adobe Syst. Inc, San Diego
fYear :
2007
fDate :
14-21 Oct. 2007
Firstpage :
1
Lastpage :
8
Abstract :
Occlusion is a significant challenge for many tracking algorithms. Most current methods can track through transient occlusion, but cannot handle significant extended occlusion when the object´s trajectory may change significantly. We present a method to track a 3D object through significant occlusion using multiple nearby cameras (e.g., a camera array). When an occluder and object are at different depths, different parts of the object are visible or occluded in each view due to parallax. By aggregating across these views, the method can track even when any individual camera observes very little of the target object. Implementation- wise, the methods are straightforward and build upon established single-camera algorithms. They do not require explicit modeling or reconstruction of the scene and enable tracking in complex, dynamic scenes with moving cameras. Analysis of accuracy and robustness shows that these methods are successful when upwards of ´70% of the object is occluded in every camera view. To the best of our knowledge, this system is the first capable of tracking in the presence of such significant occlusion.
Keywords :
cameras; image reconstruction; object detection; video signal processing; 3D object tracking; occlusions; parallax; scene modeling; scene reconstruction; single-camera algorithms; synthetic aperture tracking:; Application software; Cameras; Computer vision; Layout; Object detection; Photography; Robustness; Target tracking; Trajectory; Video sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location :
Rio de Janeiro
ISSN :
1550-5499
Print_ISBN :
978-1-4244-1630-1
Electronic_ISBN :
1550-5499
Type :
conf
DOI :
10.1109/ICCV.2007.4409032
Filename :
4409032
Link To Document :
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