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» Probabilistic Object Tracking Using Multiple Features
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CVPR
2007
IEEE
14 years 9 months ago
3D Probabilistic Feature Point Model for Object Detection and Recognition
This paper presents a novel statistical shape model that can be used to detect and localise feature points of a class of objects in images. The shape model is inspired from the 3D...
Sami Romdhani, Thomas Vetter
CVPR
2010
IEEE
14 years 1 months ago
Novel Observation Model for Probabilistic Object Tracking
Treating visual object tracking as foreground and background classification problem has attracted much attention in the past decade. Most methods adopt mean shift or brute force s...
Dawei Liang, Qingming Huang, Hongxun Yao, Shuqiang...
ICIP
2006
IEEE
14 years 9 months ago
Video-Based Rendering using Feature Point Evolution
1 We propose a novel video-based rendering algorithm with a single moving camera. We reconstruct a dynamic 3D model of the scene with a feature point set that "evolves" o...
Wende Zhang, Tsuhan Chen
ROBOCUP
2004
Springer
117views Robotics» more  ROBOCUP 2004»
14 years 1 months ago
Map-Based Multiple Model Tracking of a Moving Object
In this paper we propose an approach for tracking a moving target using Rao-Blackwellised particle filters. Such filters represent posteriors over the target location by a mixtur...
Cody C. T. Kwok, Dieter Fox
CVPR
2001
IEEE
14 years 9 months ago
3D Object Recognition from Range Images using Local Feature Histograms
This paper explores a view-based approach to recognize free-form objects in range images. We are using a set of local features that are easy to calculate and robust to partial occ...
Bastian Leibe, Bernt Schiele, Günter Hetzel, ...