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» The Dark Side of Object Learning: Learning Objects
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IROS
2007
IEEE
146views Robotics» more  IROS 2007»
14 years 4 months ago
Capturing robot workspace structure: representing robot capabilities
— Humans have at some point learned an abstraction of the capabilities of their arms. By just looking at the scene they can decide which places or objects they can easily reach a...
Franziska Zacharias, Christoph Borst, Gerd Hirzing...
ICDM
2006
IEEE
110views Data Mining» more  ICDM 2006»
14 years 4 months ago
Manifold Clustering of Shapes
Shape clustering can significantly facilitate the automatic labeling of objects present in image collections. For example, it could outline the existing groups of pathological ce...
Dragomir Yankov, Eamonn J. Keogh
WACV
2005
IEEE
14 years 3 months ago
Robust Salient Motion Detection with Complex Background for Real-Time Video Surveillance
Moving object detection is very important for video surveillance. In many environments, motion maybe either interesting (salient) motion (e.g., a person) or uninteresting motion (...
Ying-li Tian, Arun Hampapur
MM
2004
ACM
219views Multimedia» more  MM 2004»
14 years 3 months ago
Multi-level annotation of natural scenes using dominant image components and semantic concepts
Automatic image annotation is a promising solution to enable semantic image retrieval via keywords. In this paper, we propose a multi-level approach to annotate the semantics of n...
Jianping Fan, Yuli Gao, Hangzai Luo
EMMCVPR
2001
Springer
14 years 2 months ago
A Hierarchical Markov Random Field Model for Figure-Ground Segregation
To segregate overlapping objects into depth layers requires the integration of local occlusion cues distributed over the entire image into a global percept. We propose to model thi...
Stella X. Yu, Tai Sing Lee, Takeo Kanade