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» Integration of Background Modeling and Object Tracking
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ICASSP
2010
IEEE
14 years 10 months ago
Visual localization and segmentation based on foreground/background modeling
In this paper, we propose a novel method to localize (or track) a foreground object and segment the foreground object from the surrounding background with occlusions for a moving ...
Hanzi Wang, Tat-Jun Chin, David Suter
ICMCS
2005
IEEE
201views Multimedia» more  ICMCS 2005»
15 years 4 months ago
Head Tracking Using Particle Filter with Intensity Gradient and Color Histogram
This paper presents a method for tracking human head using a particle filter to naturally integrate two complementary cues: intensity gradient and color histogram. The shape of th...
Xinyu Xu, Baoxin Li
CVPR
2009
IEEE
16 years 5 months ago
Discriminatively Trained Particle Filters for Complex Multi-Object Tracking
This work presents a discriminative training method for particle filters in the context of multi-object tracking. We are motivated by the difficulty of hand-tuning the many mode...
Alan Fern, Robin Hess
JMM2
2007
212views more  JMM2 2007»
14 years 10 months ago
Flux Tensor Constrained Geodesic Active Contours with Sensor Fusion for Persistent Object Tracking
— This paper makes new contributions in motion detection, object segmentation and trajectory estimation to create a successful object tracking system. A new efficient motion det...
Filiz Bunyak, Kannappan Palaniappan, Sumit Kumar N...
ECCV
2002
Springer
16 years 11 days ago
Towards Improved Observation Models for Visual Tracking: Selective Adaptation
Abstract. An important issue in tracking is how to incorporate an appropriate degree of adaptivity into the observation model. Without any adaptivity, tracking fails when object pr...
Andrew Blake, Jaco Vermaak, Michel Gangnet, Patric...