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ICCV
2005
IEEE
14 years 6 months ago
Integration of Conditionally Dependent Object Features for Robust Figure/Background Segmentation
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and p...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
ICRA
2006
IEEE
113views Robotics» more  ICRA 2006»
13 years 10 months ago
Integration of Dependent Bayesian Filters for Robust Tracking
— Robotics applications based on computer vision algorithms are highly constrained to indoor environments where conditions may be controlled. The development of robust visual alg...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
PAMI
2008
235views more  PAMI 2008»
13 years 4 months ago
Dependent Multiple Cue Integration for Robust Tracking
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and po...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
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
ECCV
2002
Springer
14 years 6 months ago
Probabilistic and Voting Approaches to Cue Integration for Figure-Ground Segmentation
This paper describes techniques for fusing the output of multiple cues to robustly and accurately segment foreground objects from the background in image sequences. Two different m...
Eric Hayman, Jan-Olof Eklundh