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ICMCS
2007
IEEE
124views Multimedia» more  ICMCS 2007»
13 years 11 months ago
Robust Video Object Segmentation Based on K-Means Background Clustering and Watershed in Ill-Conditioned Surveillance Systems
A robust video object segmentation algorithm for complex conditions in surveillance systems is proposed in this paper. This algorithm contains an unsupervised K-Means background c...
Tse-Wei Chen, Shou-Chieh Hsu, Shao-Yi Chien
IWINAC
2011
Springer
12 years 8 months ago
Clustering of Trajectories in Video Surveillance Using Growing Neural Gas
Abstract. One of the more important issues in intelligent video surveillance systems is the ability to handle events from the motion of objects. Thus, the classification of the tr...
Javier Acevedo-Rodríguez, Saturnino Maldona...
ICIAR
2005
Springer
13 years 11 months ago
Real-Time and Robust Background Updating for Video Surveillance and Monitoring
Abstract. Background updating is an important aspect of dynamic scene analysis. Two critical problems: sudden camera perturbation and the sleeping person problem, which arise frequ...
Xingzhi Luo, Suchendra M. Bhandarkar
ICIP
2009
IEEE
13 years 3 months ago
An efficient and robust sequential algorithm for background estimation in video surveillance
Many computer vision algorithms such as object tracking and event detection assume that a background model of the scene under analysis is known. However, in many practical circums...
Vikas Reddy, Conrad Sanderson, Brian C. Lovell
ICPR
2004
IEEE
14 years 6 months ago
Multi Feature Path Modeling for Video Surveillance
This paper proposes a novel method for detecting nonconforming trajectories of objects as they pass through a scene. Existing methods mostly use spatial features to solve this pro...
Imran N. Junejo, Mubarak Shah, Omar Javed