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CVPR
2009
IEEE
1866views Computer Vision» more  CVPR 2009»
17 years 1 months ago
Understanding and evaluating blind deconvolution algorithms
Blind deconvolution is the recovery of a sharp version of a blurred image when the blur kernel is unknown. Recent algorithms have afforded dramatic progress, yet many aspects of...
Anat Levin, Yair Weiss, Frédo Durand, Willi...
ECCV
1996
Springer
16 years 8 months ago
Accuracy vs. Efficiency Trade-offs in Optical Flow Algorithms
There have been two thrusts in the development of optical flow algorithms. One has emphasized higher accuracy; the other faster implementation. These two thrusts, however, have be...
Hongche Liu, Tsai-Hong Hong, Martin Herman, Rama C...
CVPR
2012
IEEE
13 years 8 months ago
Active image clustering: Seeking constraints from humans to complement algorithms
We propose a method of clustering images that combines algorithmic and human input. An algorithm provides us with pairwise image similarities. We then actively obtain selected, mo...
Arijit Biswas, David W. Jacobs
ECCV
2004
Springer
16 years 8 months ago
Dynamic Visual Search Using Inner-Scene Similarity: Algorithms and Inherent Limitations
Abstract. A dynamic visual search framework based mainly on innerscene similarity is proposed. Algorithms as well as measures quantifying the difficulty of search tasks are suggest...
Tamar Avraham, Michael Lindenbaum
ICPR
2006
IEEE
16 years 6 days ago
A Pixel-wise Object Tracking Algorithm with Target and Background Sample
In this paper, we present a clustering-based tracking algorithm for non-rigid object. Non-rigid object tracking is a challenging task because the target often appears as a concave...
Chunsheng Hua, Haiyuan Wu, Qian Chen, Toshikazu Wa...