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» A Conditional Random Field Model for Video Super-resolution
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IROS
2007
IEEE
157views Robotics» more  IROS 2007»
14 years 1 months ago
A spatio-temporal probabilistic model for multi-sensor object recognition
— This paper presents a general framework for multi-sensor object recognition through a discriminative probabilistic approach modelling spatial and temporal correlations. The alg...
Bertrand Douillard, Dieter Fox, Fabio T. Ramos
LREC
2008
101views Education» more  LREC 2008»
13 years 8 months ago
Sentiment Analysis Based on Probabilistic Models Using Inter-Sentence Information
This paper proposes a new method of the sentiment analysis utilizing inter-sentence structures especially for coping with reversal phenomenon of word polarity such as quotation of...
Kugatsu Sadamitsu, Satoshi Sekine, Mikio Yamamoto
TSP
2008
151views more  TSP 2008»
13 years 7 months ago
Convergence Analysis of Reweighted Sum-Product Algorithms
Markov random fields are designed to represent structured dependencies among large collections of random variables, and are well-suited to capture the structure of real-world sign...
Tanya Roosta, Martin J. Wainwright, Shankar S. Sas...
CVPR
2008
IEEE
14 years 9 months ago
Simultaneous super-resolution and 3D video using graph-cuts
This paper presents a new method to increase the quality of 3D video, a new media developed to represent 3D objects in motion. This representation is obtained from multi-view reco...
Tony Tung, Shohei Nobuhara, Takashi Matsuyama
ACCV
2009
Springer
14 years 2 months ago
Visual Saliency Based Object Tracking
Abstract. This paper presents a novel method of on-line object tracking with the static and motion saliency features extracted from the video frames locally, regionally and globall...
Geng Zhang, Zejian Yuan, Nanning Zheng, Xingdong S...