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» Probabilistic Motion Sequence Generation
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EMMCVPR
2011
Springer
12 years 7 months ago
Data-Driven Importance Distributions for Articulated Tracking
Abstract. We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In ...
Søren Hauberg, Kim Steenstrup Pedersen
EVOW
2010
Springer
13 years 10 months ago
Towards Automated Learning of Object Detectors
Recognizing arbitrary objects in images or video sequences is a difficult task for a computer vision system. We work towards automated learning of object detectors from video seque...
Marc Ebner
IH
2004
Springer
14 years 23 days ago
On the Possibility of Non-invertible Watermarking Schemes
Recently, there are active discussions on the possibility of non-invertible watermarking scheme. A non-invertible scheme prevents an attacker from deriving a valid watermark from a...
Qiming Li, Ee-Chien Chang
ICCV
1999
IEEE
14 years 9 months ago
Removal of Translation Bias when using Subspace Methods
Given estimates of the motion eld optic ow from an image sequence, it is possible to recover translational direction, ~T, using a variety of techniques. One such technique, known ...
W. James MacLean
CVPR
2010
IEEE
14 years 3 months ago
Super-Resolution of Range Data in Dynamic Environments Using a Gaussian Framework
We present a flexible method for fusing information from optical and range sensors based on an accelerated highdimensional filtering approach. Our system takes as input a sequen...
Jennifer Dolson, Jongmin Baek, Christian Plagemann...