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» Learning Object Shape: From Drawings to Images
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CVPR
2009
IEEE
1094views Computer Vision» more  CVPR 2009»
16 years 4 months ago
Uncalibrated Synthetic Aperture Photography for Defocus Control
Exaggerated defocus cannot be achieved with an ordinary compact digital camera because of its tiny sensor size, so taking pictures that draw the attention of a viewer to the subjec...
Natsumi Kusumoto, Shinsaku Hiura, Kosuke Sato
CVPR
2009
IEEE
1453views Computer Vision» more  CVPR 2009»
16 years 2 months ago
Learning Photometric Invariance From Diversified Color Model Ensembles
Color is a powerful visual cue for many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the i...
Jose M. Alvarez, Theo Gevers, Antonio M. Lopez
MICCAI
2009
Springer
15 years 5 months ago
On the Manifold Structure of the Space of Brain Images
This paper investigates an approach to model the space of brain images through a low-dimensional manifold. A data driven method to learn a manifold from a collections of brain imag...
Samuel Gerber, Tolga Tasdizen, Sarang C. Joshi, Ro...
MM
2003
ACM
239views Multimedia» more  MM 2003»
15 years 3 months ago
Foreground object detection from videos containing complex background
This paper proposes a novel method for detection and segmentation of foreground objects from a video which contains both stationary and moving background objects and undergoes bot...
Liyuan Li, Weimin Huang, Irene Y. H. Gu, Qi Tian
DCC
2008
IEEE
15 years 9 months ago
Object-Based Regions of Interest for Image Compression
A fully automated architecture for object-based region of interest (ROI) detection is proposed. ROI's are defined as regions containing user defined objects of interest, and ...
Sunhyoung Han, Nuno Vasconcelos