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» Using Optical Flow for Tracking
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ECCV
2002
Springer
14 years 10 months ago
Resolution Selection Using Generalized Entropies of Multiresolution Histograms
The performances of many image analysis tasks depend on the image resolution at which they are applied. Traditionally, resolution selection methods rely on spatial derivatives of i...
Efstathios Hadjidemetriou, Michael D. Grossberg, S...
ECCV
2002
Springer
14 years 10 months ago
Face Identification by Fitting a 3D Morphable Model Using Linear Shape and Texture Error Functions
Abstract This paper presents a novel algorithm aiming at analysis and identification of faces viewed from different poses and illumination conditions. Face analysis from a single i...
Sami Romdhani, Volker Blanz, Thomas Vetter
ICPR
2010
IEEE
14 years 3 months ago
Continuous Markov Random Field Optimization using Fusion Move Driven Markov Chain Monte Carlo Technique
Many vision applications have been formulated as Markov Random Field (MRF) problems. Although many of them are discrete labeling problems, continuous formulation often achieves gre...
Wonsik Kim (Seoul National University), Kyoung Mu ...
APVIS
2009
13 years 9 months ago
Interactive feature extraction and tracking by utilizing region coherency
The ability to extract and follow time-varying flow features in volume data generated from large-scale numerical simulations enables scientists to effectively see and validate mod...
Chris Muelder, Kwan-Liu Ma
CVPR
2005
IEEE
14 years 10 months ago
Multiscale Segmentation by Combining Motion and Intensity Cues
We present a multiscale method for motion segmentation. Our method begins with local, ambiguous optical flow measurements. It uses a process of aggregation to resolve the ambiguit...
Meirav Galun, Alexander Apartsin, Ronen Basri