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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»
15 years 6 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»
15 years 1 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»
14 years 11 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
16 years 1 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
15 years 6 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...