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» Novel Observation Model for Probabilistic Object Tracking
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ICASSP
2011
IEEE
12 years 11 months ago
Parametric modeling and linear estimation of elastic deformations
We present a novel method to model and estimate elastic geometric deformations of an observed object, whether they are caused by the object’s own dynamic behavior, or by the dyn...
Nadav Geva, Rami Hagege, Joseph M. Francos
ECCV
2004
Springer
14 years 9 months ago
Novel Skeletal Representation for Articulated Creatures
Abstract. Volumetric structures are frequently used as shape descriptors for 3D data. The capture of such data is being facilitated by developments in multi-view video and range sc...
Gabriel J. Brostow, Irfan A. Essa, Drew Steedly, V...
BMVC
2001
13 years 10 months ago
Adaptive Visual System for Tracking Low Resolution Colour Targets
This paper addresses the problem of using appearance and motion models in classifying and tracking objects when detailed information of the object’s appearance is not available....
Pakorn KaewTrakulPong, Richard Bowden
JMLR
2008
83views more  JMLR 2008»
13 years 7 months ago
Generalization from Observed to Unobserved Features by Clustering
We argue that when objects are characterized by many attributes, clustering them on the basis of a random subset of these attributes can capture information on the unobserved attr...
Eyal Krupka, Naftali Tishby
ICPR
2008
IEEE
14 years 2 months ago
Tracking human body by using particle filter Gaussian process Markov-switching model
The goal of this article is to present an effective and robust tracking algorithm for nonlinear feet motion by deploying particle filter integrated with Gaussian process latent v...
Jing Wang, Hong Man, Yafeng Yin