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» Application of Level Set Methods in Computer Vision
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CVPR
2007
IEEE
14 years 9 months ago
Learning Gaussian Conditional Random Fields for Low-Level Vision
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
ICVGIP
2004
13 years 9 months ago
Use of Linear Diffusion in Depth Estimation Based on Defocus Cue
Diffusion has been used extensively in computer vision. Most common applications of diffusion have been in low level vision problems like segmentation and edge detection. In this ...
Vinay P. Namboodiri, Subhasis Chaudhuri
ICPR
2008
IEEE
14 years 8 months ago
A covariance-based method for dynamic background subtraction
Background subtraction in dynamic scenes is an important and challenging task. In this paper, we present a novel and effective method for dynamic background subtraction based on c...
Hongxun Yao, Shaohui Liu, Shengping Zhang, Wen Gao...
ROMAN
2007
IEEE
179views Robotics» more  ROMAN 2007»
14 years 1 months ago
A Bayesian Network Framework for Vision Based Semantic Scene Understanding
— For a robot to understand a scene, we have to infer and extract meaningful information from vision sensor data. Since scene understanding consists in recognizing several visual...
Seung-Bin Im, Keum-Sung Hwang, Sung-Bae Clio
DAC
1999
ACM
14 years 8 months ago
Gate-Level Design Exploiting Dual Supply Voltages for Power-Driven Applications
The advent of portable and high-density devices has made power consumption a critical design concern. In this paper, we address the problem of reducing power consumption via gate-...
Ching-Wei Yeh, Min-Cheng Chang, Shih-Chieh Chang, ...