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» Probabilistic Object Tracking Using Multiple Features
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SCVMA
2004
Springer
14 years 2 months ago
Segregation of Moving Objects Using Elastic Matching
We present a method for figure-ground segregation of moving objects from monocular video sequences. The approach is based on tracking extracted contour fragments, in contrast to ...
Vishal Jain, Benjamin B. Kimia, Joseph L. Mundy
MMM
2006
Springer
154views Multimedia» more  MMM 2006»
14 years 3 months ago
A robust object shape prediction algorithm in the presence of white Gaussian noise
This paper presents a shape prediction algorithm in a noisy video sequence based on pixel representation in the undecimated wavelet domain. In our algorithm for tracking of user-d...
Mohammad Khansari, Hamid R. Rabiee, M. Asadi, M. G...
CIVR
2007
Springer
157views Image Analysis» more  CIVR 2007»
14 years 3 months ago
Using multiple segmentations for image auto-annotation
Automatic image annotation techniques that try to identify the objects in images usually need the images to be segmented first, especially when specifically annotating image reg...
Jiayu Tang, Paul H. Lewis
ICCS
2007
Springer
14 years 3 months ago
Dynamic Tracking of Facial Expressions Using Adaptive, Overlapping Subspaces
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
Dimitris N. Metaxas, Atul Kanaujia, Zhiguo Li
ICPR
2000
IEEE
14 years 10 months ago
A Parallel Algorithm for Tracking of Segments in Noisy Edge Images
We present a parallel implementation of a probabilistic algorithm for real time tracking of segments in noisy edge images. Given an initial solution ?a set of segments that reason...
Pedro E. López-de-Teruel, Alberto Ruiz, Jos...