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» Adaptive Background Estimation for Object Tracking
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114
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PCM
2004
Springer
127views Multimedia» more  PCM 2004»
15 years 7 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...
179
Voted
CVPR
2009
IEEE
16 years 7 months ago
Tracking of a Non-Rigid Object via Patch-based Dynamic Appearance Modeling and Adaptive Basin Hopping Monte Carlo Sampling
We propose a novel tracking algorithm for the target of which geometric appearance changes drastically over time. To track it, we present a local patch-based appearance model and p...
Junseok Kwon (Seoul National University), Kyoung M...
FSKD
2007
Springer
193views Fuzzy Logic» more  FSKD 2007»
15 years 8 months ago
Panoramic Background Model under Free Moving Camera
segmentation of moving regions in outdoor environment under a moving camera is a fundamental step in many vision systems including automated visual surveillance, human-machine int...
Naveed I. Rao, Huijun Di, Guangyou Xu
CVPR
2005
IEEE
15 years 8 months ago
Online Selecting Discriminative Tracking Features Using Particle Filter
The paper proposes a method to keep the tracker robust to background clutters by online selecting discriminative features from a large feature space. Furthermore, the feature sele...
Jianyu Wang, Xilin Chen, Wen Gao
146
Voted
ICCV
2007
IEEE
16 years 4 months ago
Graph Based Discriminative Learning for Robust and Efficient Object Tracking
Object tracking is viewed as a two-class 'one-versusrest' classification problem, in which the sample distribution of the target is approximately Gaussian while the back...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...