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CVPR
2004
IEEE
16 years 6 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
TCSV
2008
202views more  TCSV 2008»
15 years 4 months ago
Probabilistic Object Tracking With Dynamic Attributed Relational Feature Graph
Object tracking is one of the fundamental problems in computer vision and has received considerable attention in the past two decades. The success of a tracking algorithm relies on...
Feng Tang, Hai Tao
ECCV
2002
Springer
16 years 6 months ago
Automatic Detection and Tracking of Human Motion with a View-Based Representation
Abstract. This paper proposes a solution for the automatic detection and tracking of human motion in image sequences. Due to the complexity of the human body and its motion, automa...
Ronan Fablet, Michael J. Black
CVPR
2008
IEEE
16 years 6 months ago
Combining appearance models and Markov Random Fields for category level object segmentation
Object models based on bag-of-words representations can achieve state-of-the-art performance for image classification and object localization tasks. However, as they consider obje...
Diane Larlus, Frédéric Jurie
ECCV
2002
Springer
16 years 6 months ago
Learning the Topology of Object Views
A visual representation of an object must meet at least three basic requirements. First, it must allow identification of the object in the presence of slight but unpredictable chan...
Christoph von der Malsburg, Jan Wieghardt, Rolf P....