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» Using Optical Flow for Tracking
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CVPR
2004
IEEE
14 years 10 months ago
Efficient Belief Propagation for Early Vision
Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph...
Pedro F. Felzenszwalb, Daniel P. Huttenlocher
CVPR
2010
IEEE
14 years 5 months ago
Unsupervised Learning of Invariant Features Using Video
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
David Stavens, Sebastian Thrun
ISCA
2008
IEEE
185views Hardware» more  ISCA 2008»
13 years 8 months ago
From Speculation to Security: Practical and Efficient Information Flow Tracking Using Speculative Hardware
Dynamic information flow tracking (also known as taint tracking) is an appealing approach to combat various security attacks. However, the performance of applications can severely...
Haibo Chen, Xi Wu, Liwei Yuan, Binyu Zang, Pen-Chu...
ICIP
2000
IEEE
14 years 10 months ago
A Data Fusion Solution to the Accuracy-Efficiency Trade-Off Problem in Motion Estimation
There is often a trade-off between the accuracy and the speed of optical flow techniques. Given similar computational resources, this trade-off results in some techniques making i...
Andrew M. Peacock, David S. Renshaw, John M. Hanna...
ECCV
2008
Springer
14 years 10 months ago
Continuous Energy Minimization Via Repeated Binary Fusion
Abstract. Variational problems, which are commonly used to solve lowlevel vision tasks, are typically minimized via a local, iterative optimization strategy, e.g. gradient descent....
Werner Trobin, Thomas Pock, Daniel Cremers, Horst ...