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» Modeling Moving Objects for Location Based Services
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ICCV
2009
IEEE
1190views Computer Vision» more  ICCV 2009»
16 years 9 months ago
You'll never walk alone: modeling social behavior for multi-target tracking
Object tracking typically relies on a dynamic model to predict the object’s location from its past trajectory. In crowded scenarios a strong dynamic model is particularly impo...
S. Pellegrini, A. Ess, K. Schindler, L. van Gool
ETS
2006
IEEE
119views Hardware» more  ETS 2006»
15 years 4 months ago
An Ontology-Based Framework for Bridging Learning Design and Learning Content
The paper describes an ontology-based framework for bridging learning design and learning object content. In present solutions, researchers have proposed conceptual models and dev...
Colin Knight, Dragan Gasevic, Griff Richards
ICIP
2004
IEEE
16 years 5 months ago
Adaptive eigen-backgrounds for object detection
Most tracking algorithms detect moving objects by comparing incoming images against a reference frame. Crucially, this reference image must adapt continuously to the current light...
Jonathan D. Rymel, John-Paul Renno, Darrel Greenhi...
CAIP
2003
Springer
176views Image Analysis» more  CAIP 2003»
15 years 9 months ago
Evaluation of an Adaptive Composite Gaussian Model in Video Surveillance
Video surveillance systems seek to automatically identify events of interest in a variety of situations. Extracting a moving object from background is the most important step of t...
Qi Zang, Reinhard Klette
134
Voted
ICCV
2009
IEEE
15 years 1 months ago
Storyboard sketches for Content Based Video Retrieval
We present a novel Content Based Video Retrieval (CBVR) system, driven by free-hand sketch queries depicting both objects and their movement (via dynamic cues; streak-lines and ar...
John P. Collomosse, Graham McNeill, Yu Qian