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» Probabilistic Object Tracking Using Multiple Features
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ICML
2006
IEEE
14 years 8 months ago
Combining discriminative features to infer complex trajectories
We propose a new model for the probabilistic estimation of continuous state variables from a sequence of observations, such as tracking the position of an object in video. This ma...
David A. Ross, Simon Osindero, Richard S. Zemel
PCM
2004
Springer
127views Multimedia» more  PCM 2004»
14 years 1 months ago
Using a Non-prior Training Active Feature Model
This paper presents a feature point tracking algorithm using optical flow under the non-prior training active feature model (NPTAFM) framework. The proposed algorithm mainly focus...
Sangjin Kim, Jinyoung Kang, Jeongho Shin, Seongwon...
CVPR
2003
IEEE
14 years 28 days ago
Continuous Tracking Within and Across Camera Streams
This paper presents a new approach for continuous tracking of moving objects observed by multiple, heterogeneous cameras. Our approach simultaneously processes video streams from ...
Jinman Kang, Isaac Cohen, Gérard G. Medioni
CVPR
2007
IEEE
14 years 9 months ago
A Probabilistic Model for Object Recognition, Segmentation, and Non-Rigid Correspondence
We describe a method for fully automatic object recognition and segmentation using a set of reference images to specify the appearance of each object. Our method uses a generative...
Ian Simon, Steven M. Seitz
TIP
2008
124views more  TIP 2008»
13 years 7 months ago
Robust Shape Tracking With Multiple Models in Ultrasound Images
This paper addresses object tracking in ultrasound images using a robust multiple model tracker. The proposed tracker has the following features: 1) it uses multiple dynamic models...
Jacinto C. Nascimento, Jorge S. Marques