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ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 11 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
CVPR
1998
IEEE
16 years 8 months ago
Joint Probabilistic Techniques for Tracking Multi-Part Objects
Common objects such as people and cars comprise many visual parts and attributes, yet image-based tracking algorithms are often keyed to only one of a target's identifying ch...
Christopher Rasmussen, Gregory D. Hager
CVPR
2000
IEEE
16 years 8 months ago
Recovering Non-Rigid 3D Shape from Image Streams
This paper addresses the problem of recovering 3D non-rigid shape models from image sequences. For example, given a video recording of a talking person, we would like to estimate ...
Christoph Bregler, Aaron Hertzmann, Henning Bierma...
CVPR
2004
IEEE
16 years 8 months ago
A Probabilistic Framework for Combining Tracking Algorithms
For the past few years researches have been investigating enhancing tracking performance by combining several different tracking algorithms. We propose an analytically justified, ...
Ido Leichter, Michael Lindenbaum, Ehud Rivlin
CVPR
2005
IEEE
16 years 8 months ago
Evaluating Image Retrieval
We present a comprehensive strategy for evaluating image retrieval algorithms. Because automated image retrieval is only meaningful in its service to people, performance character...
Nikhil V. Shirahatti, Kobus Barnard