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» Clustering Moving Objects via Medoid Clusterings
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SAC
2008
ACM
13 years 7 months ago
A clustering-based approach for discovering interesting places in trajectories
Because of the large amount of trajectory data produced by mobile devices, there is an increasing need for mechanisms to extract knowledge from this data. Most existing works have...
Andrey Tietbohl Palma, Vania Bogorny, Bart Kuijper...
ACIVS
2009
Springer
14 years 11 days ago
Vehicle Tracking Using Geometric Features
Applications such as traffic surveillance require a real-time and accurate method for object tracking. We propose to represent scene observations with parabola segments with an alg...
Francis Deboeverie, Kristof Teelen, Peter Veelaert...
CVPR
2009
IEEE
14 years 2 months ago
Trajectory parsing by cluster sampling in spatio-temporal graph
The objective of this paper is to parse object trajectories in surveillance video against occlusion, interruption, and background clutter. We present a spatio-temporal graph (ST-G...
Xiaobai Liu, Liang Lin, Song Chun Zhu, Hai Jin
JUCS
2010
265views more  JUCS 2010»
13 years 6 months ago
A General Framework for Multi-Human Tracking using Kalman Filter and Fast Mean Shift Algorithms
: The task of reliable detection and tracking of multiple objects becomes highly complex for crowded scenarios. In this paper, a robust framework is presented for multi-Human track...
Ahmed Ali, Kenji Terada
ICTAI
2005
IEEE
14 years 1 months ago
Cellular Ants: Combining Ant-Based Clustering with Cellular Automata
This paper proposes a novel data clustering algorithm, coined ‘cellular ants’, which combines principles of cellular automata and ant colony optimization algorithms to group s...
Andrew Vande Moere, Justin James Clayden