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» Learning to localize detected objects
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MIR
2004
ACM
236views Multimedia» more  MIR 2004»
14 years 3 months ago
Boosting contextual information in content-based image retrieval
We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into acc...
Jaume Amores, Nicu Sebe, Petia Radeva, Theo Gevers...
MVA
2002
226views Computer Vision» more  MVA 2002»
13 years 9 months ago
Adaptive Background Estimation and Shadow Removal in Indoor Scenes
2 Background Model Background subtraction algorithm is susceptible to both global and local illumination changes such as shadows, sunlight and reflection. These changes sometimes c...
Junya Morita, Yoshio Iwai, Masahiko Yachida
CVPR
2007
IEEE
15 years 3 days ago
Multi-Layer Background Subtraction Based on Color and Texture
In this paper, we propose a robust multi-layer background subtraction technique which takes advantages of local texture features represented by local binary patterns (LBP) and pho...
Jian Yao, Jean-Marc Odobez
MVA
2000
166views Computer Vision» more  MVA 2000»
13 years 11 months ago
Motion Segmentation and Tracking by Embedding Global Model Within a Contextual Relaxation Scheme
IAPR Workshop on Machine Vision and Applications, pp. 455-458, 2000, Tokyo, Japan In this paper, we integrate the model-based tracking and local contexture (temporal and spatial) ...
Yunqiang Chen, Thomas S. Huang
IJRR
2011
159views more  IJRR 2011»
13 years 5 months ago
Learning visual representations for perception-action systems
We discuss vision as a sensory modality for systems that effect actions in response to perceptions. While the internal representations informed by vision may be arbitrarily compl...
Justus H. Piater, Sébastien Jodogne, Renaud...