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» Detecting and Tracking Moving Objects for Video Surveillance
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ICPR
2004
IEEE
16 years 2 months ago
Estimation of the Bayesian Network Architecture for Object Tracking in Video Sequences
It was recently proposed the use of Bayesian networks for object tracking. Bayesian networks allow to model the interaction among detected trajectories, in order to obtain a relia...
Arnaldo J. Abrantes, Jorge S. Marques, Pedro Mende...
ICIP
2003
IEEE
16 years 3 months ago
Video object segmentation and tracking in stereo sequences using adaptable neural networks
In this paper, an adaptive neural network architecture is proposed for efficient video object segmentation and tracking of stereoscopic sequences. The scheme includes (a) a retrai...
Nikolaos D. Doulamis, Anastasios D. Doulamis
ECCV
2006
Springer
15 years 5 months ago
Learning Semantic Scene Models by Trajectory Analysis
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...
Xiaogang Wang, Kinh Tieu, Eric Grimson
CVPR
2007
IEEE
15 years 8 months ago
Trajectory Series Analysis based Event Rule Induction for Visual Surveillance
In this paper, a generic rule induction framework based on trajectory series analysis is proposed to learn the event rules. First the trajectories acquired by a tracking system ar...
Zhang Zhang, Kaiqi Huang, Tieniu Tan, Liangsheng W...
ICCV
2011
IEEE
14 years 1 months ago
Trajectory reconstruction from non-overlapping surveillance cameras with relative depth ordering constraints
We present a method for reconstructing a trajectory of an object moving in front of non-overlapping fully or partially calibrated cameras. The non-overlapping setup turns that pro...
Branislav Micusik