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» Adaptive Background Mixture Models for Real-Time Tracking
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NIPS
1997
13 years 9 months ago
A Neural Network Based Head Tracking System
We have constructed an inexpensive, video-based, motorized tracking system that learns to track a head. It uses real time graphical user inputs or an auxiliary infrared detector a...
Daniel D. Lee, H. Sebastian Seung
FGR
1998
IEEE
131views Biometrics» more  FGR 1998»
13 years 12 months ago
Tracking and Segmenting People in Varying Lighting Conditions Using Colour
Colour cues were used to obtain robust detection and tracking of people in relatively unconstrained dynamic scenes. Gaussian mixture models were used to estimate probability densi...
Yogesh Raja, Stephen J. McKenna, Shaogang Gong
ICCV
2007
IEEE
13 years 9 months ago
Probabilistic Fusion Tracking Using Mixture Kernel-Based Bayesian Filtering
Even though sensor fusion techniques based on particle filters have been applied to object tracking, their implementations have been limited to combining measurements from multip...
Bohyung Han, Seong-Wook Joo, Larry S. Davis
FGR
2006
IEEE
122views Biometrics» more  FGR 2006»
14 years 1 months ago
Head and Facial Action Tracking: Comparison of Two Robust Approaches
In this work, we address a method that is able to track simultaneously 3D head movements and facial actions like lip and eyebrow movements in a video sequence. In a baseline frame...
Romain Hérault, Franck Davoine, Yves Grandv...
MOBIHOC
2009
ACM
14 years 8 months ago
Fault tolerant target tracking in sensor networks
In this paper, we present a Gaussian mixture model based approach to capture the spatial characteristics of any target signal in a sensor network, and further propose a temporally...
Min Ding, Xiuzhen Cheng