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Author
H.M.G. Stokman; Theo Gevers
Title
Selection and Fusion of Color Models for Image Feature Detection
Type
Journal
Year
2007
Publication
IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.29(3):371–381
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ALTRES;ISE
Approved
no
Call Number
Admin @ si @ StG2007
Serial
948
Permanent link to this record
Author
Joost Van de Weijer; Theo Gevers; A. Gijsenij
Title
Edge-Based Color Constancy
Type
Journal
Year
2007
Publication
IEEE Trans. on Image Processing, vol. 16(9):2207–2214
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ISE
Approved
no
Call Number
CAT @ cat @ WGG2007
Serial
949
Permanent link to this record
Author
Mikhail Mozerov; Ariel Amato; Xavier Roca; Jordi Gonzalez
Title
Trajectory Occlusion Handling with Multiple View Distance Minimisation Clustering
Type
Journal
Year
2008
Publication
Optical Engineering, vol. 47(04)04702, DOI:10.11781.2909665
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Notes
ISE
Approved
no
Call Number
ISE @ ise @ MAR2008c
Serial
970
Permanent link to this record
Author
Carles Fernandez; Xavier Roca; Jordi Gonzalez
Title
Providing Automatic Multilingual Text Generation to Artificial Cognitive Systems
Type
Journal
Year
2008
Publication
Abbreviated Journal
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Notes
ISE
Approved
no
Call Number
ISE @ ise @ FRG2008
Serial
1021
Permanent link to this record
Author
Mikhail Mozerov; Ignasi Rius; Xavier Roca; Jordi Gonzalez
Title
Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences
Type
Journal Article
Year
2010
Publication
EURASIP Journal on Advances in Signal Processing
Abbreviated Journal
EURASIPJ
Volume
Issue
Pages
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Abstract
Article ID 507247
A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.
Address
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Thesis
Publisher
Place of Publication
Editor
Language
Summary Language
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Series Editor
Series Title
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Edition
ISSN
1110-8657
ISBN
Medium
Area
Expedition
Conference
Notes
ISE
Approved
no
Call Number
ISE @ ise @ MRR2010
Serial
1208
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