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» Probabilistic Motion Sequence Generation
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EMMCVPR
2011
Springer
13 years 11 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
103
Voted
EVOW
2010
Springer
15 years 3 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
15 years 5 months 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
16 years 1 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
111
Voted
CVPR
2010
IEEE
15 years 8 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...