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» Algorithmic Fusion for More Robust Feature Tracking
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AMDO
2004
Springer
15 years 3 months ago
Image Cues Fusion for Object Tracking Based on Particle Filter
Particle filter is a powerful algorithm to deal with non-linear and non-Gaussian tracking problems. However the algorithm relying only upon one image cue often fails in challengin...
Peihua Li, François Chaumette
CVPR
2006
IEEE
15 years 11 months ago
Robust AAM Fitting by Fusion of Images and Disparity Data
Active Appearance Models (AAMs) have been popularly used to represent the appearance and shape variations of human faces. Fitting an AAM to images recovers the face pose as well a...
Joerg Liebelt, Jing Xiao, Jie Yang
COST
2009
Springer
178views Multimedia» more  COST 2009»
15 years 1 months ago
Fusion of Movement Specific Human Identification Experts
Abstract. In this paper a multi-modal method for human identification that exploits the discriminant features derived from several movement types performed from the same human is p...
Nikolaos Gkalelis, Anastasios Tefas, Ioannis Pitas
ICIP
2006
IEEE
15 years 11 months ago
Stereo Tracking and Three-Point/One-Point Algorithms - A Robust Approach in Visual Odometry
In this paper, we present an approach of calculating visual odometry for outdoor robots equipped with a stereo rig. Instead of the typical feature matching or tracking, we use an ...
Kai Ni, Frank Dellaert
PCM
2004
Springer
127views Multimedia» more  PCM 2004»
15 years 2 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...