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ICASSP
2011
IEEE
12 years 11 months ago
A revisit to MRF-based depth map super-resolution and enhancement
This paper presents a Markov Random Field (MRF)-based approach for depth map super-resolution and enhancement. Given a low-resolution or moderate quality depth map, we study the p...
Jiangbo Lu, Dongbo Min, Ramanpreet Singh Pahwa, Mi...
ICIP
2008
IEEE
14 years 2 months ago
Regularized depth from defocus
In the area of depth estimation from images an interesting approach has been structure recovery from defocus cue. Towards this end, there have been a number of approaches [4, 6]. ...
Vinay P. Namboodiri, Subhasis Chaudhuri, Sunil Had...
ICCV
2009
IEEE
13 years 5 months ago
Segmentation, ordering and multi-object tracking using graphical models
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...
Chaohui Wang, Martin de La Gorce, Nikos Paragios
APAL
2008
92views more  APAL 2008»
13 years 7 months ago
The complexity of random ordered structures
We show that for random bit strings, Up(n), with probability, p = 1 2 , the firstorder quantifier depth D(Up(n)) needed to distinguish non-isomorphic structures is (lg lg n), with...
Joel H. Spencer, Katherine St. John
ECCV
2010
Springer
13 years 8 months ago
Semantic Segmentation of Urban Scenes Using Dense Depth Maps
In this paper we present a framework for semantic scene parsing and object recognition based on dense depth maps. Five viewindependent 3D features that vary with object class are e...
Chenxi Zhang, Liang Wang, Ruigang Yang