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» A New Method for Auto-calibrated Object Tracking
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ICIP
2006
IEEE
14 years 9 months ago
Effects of Parameters Variations in Particle Filter Tracking
Many implementations of visual tracking have been proposed since many years. The lack of standard evaluation process has prevented fair comparison between them. In this paper, we ...
Céline Mancas-Thillou, Caroline Machy, Dere...
ICCV
2003
IEEE
14 years 9 months ago
Dense Shape Reconstruction of a Moving Object under Arbitrary, Unknown Lighting
We present a method for shape reconstruction from several images of a moving object. The reconstruction is dense (up to image resolution). The method assumes that the motion is kn...
Denis Simakov, Darya Frolova, Ronen Basri
CVPR
2012
IEEE
11 years 9 months ago
Batch mode Adaptive Multiple Instance Learning for computer vision tasks
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu
ECCV
2008
Springer
14 years 9 months ago
Shape Matching by Segmentation Averaging
We use segmentations to match images by shape. To address the unreliability of segmentations, we give a closed form approximation to an average over all segmentations. Our techniqu...
Hongzhi Wang, John Oliensis
CVPR
2007
IEEE
14 years 9 months ago
Monocular and Stereo Methods for AAM Learning from Video
The active appearance model (AAM) is a powerful method for modeling deformable visual objects. One of the major drawbacks of the AAM is that it requires a training set of pseudo-d...
Jason Saragih, Roland Göcke