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» Probabilistic Object Tracking Using Multiple Features
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BMVC
1998
13 years 9 months ago
Detection and Tracking of Very Small Low Contrast Objects
We present a Kalman tracking algorithm that can track a number of very small, low contrast objects through an image sequence taken from a static camera. The issues that we have ad...
D. Davies, Phil L. Palmer, Majid Mirmehdi
CVPR
2012
IEEE
11 years 10 months ago
Two-person interaction detection using body-pose features and multiple instance learning
Human activity recognition has potential to impact a wide range of applications from surveillance to human computer interfaces to content based video retrieval. Recently, the rapi...
Kiwon Yun, Jean Honorio, Debaleena Chattopadhyay, ...
ICRA
2009
IEEE
165views Robotics» more  ICRA 2009»
14 years 2 months ago
Robust servo-control for underwater robots using banks of visual filters
—We present an application of machine learning to the semi-automatic synthesis of robust servo-trackers for underwater robotics. In particular, we investigate an approach based o...
Junaed Sattar, Gregory Dudek
ICIP
2000
IEEE
14 years 9 months ago
Object Tracking by Adaptive Modeling
This paper addresses the problem of object tracking in image sequences. The approach taken is based upon adaptive statistical models. An object selected in a frame by a user is tr...
Andrei Rares, Marcel J. T. Reinders
ICMCS
2006
IEEE
111views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Integration of Background Modeling and Object Tracking
Background model and tracking became critical components for many vision-based applications. Typically, background modeling and object tracking are mutually independent in many ap...
Yu-Ting Chen, Chu-Song Chen, Yi-Ping Hung