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» Extracting the Essence from Sets of Images
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ECCV
2008
Springer
15 years 7 months ago
Unsupervised Classification and Part Localization by Consistency Amplification
We present a novel method for unsupervised classification, including the discovery of a new category and precise object and part localization. Given a set of unlabelled images, som...
Leonid Karlinsky, Michael Dinerstein, Dan Levi, Sh...
MIR
2010
ACM
232views Multimedia» more  MIR 2010»
16 years 28 days ago
Exploiting external knowledge to improve video retrieval
Most video retrieval systems are multimodal, commonly relying on textual information, low- and high-level semantic features extracted from query visual examples. In this work, we ...
David Vallet, Iván Cantador, Joemon M. Jose
CVPR
2012
IEEE
13 years 8 months ago
Enhanced continuous sign language recognition using PCA and neural network features
In this work a Gaussian Hidden Markov Model (GHMM) based automatic sign language recognition system is built on the SIGNUM database. The system is trained on appearance-based feat...
Yannick L. Gweth, Christian Plahl, Hermann Ney
CVGIP
2007
136views more  CVGIP 2007»
15 years 6 months ago
Contour-based surface reconstruction using MPU implicit models
This paper presents a technique for creating a smooth, closed surface from a set of 2D contours, which have been extracted from a 3D scan. The technique interprets the pixels that...
Ilya Braude, Jeffrey Marker, Ken Museth, Jonathan ...

Publication
258views
15 years 3 months ago
iModel: Interactive Co-segmentation for Object of Interest 3D Modeling
We present an interactive system to create 3D models of objects of interest in their natural cluttered environments. A typical setting for 3D modeling of an object of interest invo...
Adarsh Kowdle, Wen-Chao Chen, Dhruv Batra, Tsuhan ...