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» Adaptive Background Estimation for Object Tracking
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73
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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...
CVPR
2009
IEEE
16 years 2 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...
86
Voted
FSKD
2007
Springer
193views Fuzzy Logic» more  FSKD 2007»
15 years 3 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
113
Voted
CVPR
2005
IEEE
15 years 3 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
ICCV
2007
IEEE
15 years 11 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 ...