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ICASSP
2011
IEEE
14 years 1 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
15 years 3 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
14 years 7 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»
14 years 9 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
14 years 10 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