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» Learning Object Representations Using Sequential Patterns
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ICPR
2006
IEEE
14 years 8 months ago
An integrated Monte Carlo data association framework for multi-object tracking
We propose a sequential Monte Carlo data association algorithm based on a two-level computational framework for tracking varying number of interacting objects in dynamic scene. Fi...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
ICCV
2003
IEEE
14 years 9 months ago
A New Paradigm for Recognizing 3-D Object Shapes from Range Data
Most of the work on 3-D object recognition from range data has used an alignment-verification approach in which a specific 3-D object is matched to an exact instance of the same o...
Salvador Ruiz-Correa, Linda G. Shapiro, Marina Mei...
SCALESPACE
2005
Springer
14 years 1 months ago
Isometric Embedding of Facial Surfaces into
Abstract. The problem of isometry-invariant representation and comparison of surfaces is of cardinal importance in pattern recognition applications dealing with deformable objects....
Alexander M. Bronstein, Michael M. Bronstein, Ron ...
CVPR
2005
IEEE
14 years 9 months ago
Online Learning of Probabilistic Appearance Manifolds for Video-Based Recognition and Tracking
This paper presents an online learning algorithm to construct from video sequences an image-based representation that is useful for recognition and tracking. For a class of object...
Kuang-Chih Lee, David J. Kriegman
CVPR
2009
IEEE
15 years 2 months ago
Learning to Track with Multiple Observers
We propose a novel approach to designing algorithms for object tracking based on fusing multiple observation models. As the space of possible observation models is too large for...
Björn Stenger, Roberto Cipolla, Thomas Woodle...