ELCVIA

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ELCVIA	5 records found	Search took 0.01 seconds.

12 p, 360.0 KB

Facial Emotional Classifier For Natural Interaction / Hupont, Isabelle (Universidad de Zaragoza. Departamento de Informática e Ingeniería de Sistemas) ; Cerezo, Eva (Universidad de Zaragoza. Departamento de Informática e Ingeniería de Sistemas) ; Baldassarri, Sandra (Universidad de Zaragoza. Departamento de Informática e Ingeniería de Sistemas)
The recognition of emotional information is a key step toward giving computers the ability to interact more naturally and intelligently with people. We present a simple and computationally feasible method to perform automatic emotional classification of facial expressions. [...]
2008 - DOI (Digital Object Identifier)

10.5565/rev/elcvia.272
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 7 n. 4 (2008) p. 1-12

Detailed record -

19 p, 5.9 MB

Principal Deformations Modes of Articulated Models for the Analysis of 3D Spine Deformities / Boisvert, Jonathan (École Polytechnique de Montréal) ; Cheriet, Farida (École Polytechnique de Montréal) ; Pennec, Xavier (INRIA (França). Asclepios Project Team) ; Labelle, Hubert (Sainte-Justine Hospital (Montréal, Canadà)) ; Ayache, Nicholas (INRIA (França). Asclepios Project Team)
Articulated models are commonly used for recognition tasks in robotics and in gait analysis, but can also be extremely useful to develop analytical methods targeting spinal deformities studies. The threedimensional analysis of these deformities is critical since they are complex and not restricted to a given plane. [...]
2008 - DOI (Digital Object Identifier)

10.5565/rev/elcvia.165
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 7 n. 4 (2008) p. 13-31

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19 p, 658.6 KB

Human Shape-Motion Analysis In Athletics Videos for Coarse To Fine Action/Activity Recognition Using Transferable BeliefModel / Ramasso, Emmanuel (GIPSA-lab. Images and Signal Department (Grenoble, França)) ; Panagiotakis, Costas (University of Crete (Heraklion, Grècia). Department of Computer Science) ; Rombaut, Michèle (GIPSA-lab. Images and Signal Department (Grenoble, França)) ; Pellerin, Denis (GIPSA-lab. Images and Signal Department (Grenoble, França)) ; Tziritas, Georgios (University of Crete (Heraklion, Grècia). Department of Computer Science)
We present an automatic human shape-motion analysis method based on a fusion architecture for human action and activity recognition in athletic videos. Robust shape and motion features are extracted from human detection and tracking. [...]
2008 - DOI (Digital Object Identifier)

10.5565/rev/elcvia.163
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 7 n. 4 (2008) p. 32-50

Detailed record -

11 p, 683.4 KB

Distortion Correction for 3D Scan of Trunk Swaying Human Body Segments / Funatomi, Takuya (Kyoto University. Academic Center for Computing and Media Studies) ; Iiyama, Masaaki (Kyoto University. Graduate School of Economics) ; Kakusho, Koh (Kyoto University. Academic Center for Computing and Media Studies) ; Minoh, Michihiko (Kyoto University. Academic Center for Computing and Media Studies)
We propose a method for acquiring a 3D shape of human body segments accurately. Using a light stripe triangulation range finder, we can acquire accurate 3D shape of a motionless object in dozens of seconds. [...]
2008 - DOI (Digital Object Identifier)

10.5565/rev/elcvia.251
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 7 n. 4 (2008) p. 51-61

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11 p, 767.4 KB

Finding Kinematic Structure in Time Series Volume Data / Mukasa, Tomoyuki (Kyoto University. Graduate School of Informatics) ; Nobuhara, Shohei (Kyoto University. Graduate School of Informatics) ; Maki, Atsuto (Kyoto University. Graduate School of Informatics) ; Matsuyama, Takashi (Kyoto University. Graduate School of Informatics)
This paper presents a new scheme for acquiring 3D kinematic structure and motion from time series volume data. Our basic strategy is to first represent the shape structure of the target in each frame by Reeb graph which we compute by using geodesic distance of target's surface, and then estimate the kinematic structure of the target which is consistent with these shape structures. [...]
2009 - DOI (Digital Object Identifier)

10.5565/rev/elcvia.164
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 7 n. 4 (2009) p. 62-72

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