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» Novel Observation Model for Probabilistic Object Tracking
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CVPR
2010
IEEE
14 years 4 months ago
Toward Coherent Object Detection And Scene Layout Understanding
Detecting objects in complex scenes while recovering the scene layout is a critical functionality in many vision-based applications. Inspired by the work of [18], we advocate the ...
Yingze Bao, Min Sun, Silvio Savarese
AAAI
2012
11 years 10 months ago
An Object-Based Bayesian Framework for Top-Down Visual Attention
We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...
Ali Borji, Dicky N. Sihite, Laurent Itti
CVPR
2006
IEEE
14 years 9 months ago
Escaping local minima through hierarchical model selection: Automatic object discovery, segmentation, and tracking in video
Recently, the generative modeling approach to video segmentation has been gaining popularity in the computer vision community. For example, the flexible sprites framework has been...
Nebojsa Jojic, John M. Winn, Larry Zitnick
UAI
2004
13 years 9 months ago
Factored Latent Analysis for far-field Tracking Data
This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...
Chris Stauffer
CVPR
2001
IEEE
14 years 9 months ago
Tracking and Modeling Non-Rigid Objects with Rank Constraints
This paper presents a novel solution for flow-based tracking and 3D reconstruction of deforming objects in monocular image sequences. A non-rigid 3D object undergoing rotation and...
Lorenzo Torresani, Danny B. Yang, Eugene J. Alexan...