Abstract book (pdf) - ICPR 2010

simulation study and demonstrated that KF and PVA worked congruently for uniformly distributed preferred directions
(PDs) whereas KF outperformed PVA for non-uniform PDs. In addition, we showed that KF decoded better than PVA for
low signal-to-noise ratio (SNR) or a small ensemble size. The results suggest that KF may decode direction better than
PVA with non-uniform PDs or with low SNR and small ensemble size.
09:00-11:10, Paper ThAT9.39
3D Active Shape Model for Automatic Facial Landmark Location Trained with Automatically Generated Landmark
Points
Zhou, Dianle, TMSP
Petrovska-Delacretaz, Dijana, Inst. Telecom SudParis (ex GET-INT)
Dorizzi, Bernadette, TELECOM & Management SudParis
In this paper, a 3D Active Shape Model (3DASM) algorithm is presented to automatically locate facial landmarks from different
views. The 3DASM is trained by setting different shape and texture parameters of 3D Morphable Model (3DMM).
Using 3DMM to synthesize training data offers us two advantages: first, few manual operations are need, except labeling
landmarks on the mean face of 3DMM. Second, since the learning data are directly from 3DMM, landmarks have one to one
correspondence between the 2D points detected from the image and 3D points on 3DMM. This kind of correspondence will
benefit 3D face reconstruction processing. During fitting, 3D rotation parameters are added comparing to 2D Active Shape
Model (ASM). So we separate shape variations into intrinsic change (caused by the character of different person) and extrinsic
change (caused by model projection). The experimental results show that our method is robust to pose variation.
09:00-11:10, Paper ThAT9.40
Using Moments on Spatiotemporal Plane for Facial Expression Recognition
Ji, Yi, INSA de Lyon
Idrissi, Khalid, INSA de Lyon
In this paper, we propose a novel approach to capture the dynamic deformation caused by facial expressions. The proposed
method is concentrated on the spatiotemporal plane which is not well explored. It uses the moments as features to describe
the movements of essential components such as eyes and mouth on vertical time plane. The system we developed can automatically
recognize the expression on images as well as on image sequences. The experiments are performed on 348 sequences
from 95 subjects in Cohn-Kanade database and obtained good results as high as 96.1% in 7-class recognition for
frames and 98.5% in 6-class for sequences.
09:00-11:10, Paper ThAT9.41
Towards a More Realistic Appearance-Based Gait Representation for Gender Recognition
Martín-Félez, Raúl, Univ. Jaume I
Mollineda, Ramón A., Univ. Jaume I
Sanchez, J. Salvador, Univ. Jaume I
A realistic appearance-based representation of side-view gait sequences is here introduced. It is based on a prior method
where a set of appearance-based features of a gait sample is used for gender recognition. These features are computed from
parameter values of ellipses that fit body parts enclosed by regions previously defined while ignoring well-known facts of
the human body structure. This work presents an improved regionalization method supported by some adaptive heuristic
rules to better adjust regions to body parts. As a result, more realistic ellipses and a more meaningful feature space are obtained.
Gender recognition experiments conducted on the CASIA Gait Database show better classification results when using
the new features.
09:00-11:10, Paper ThAT9.42
A Calibration-Free Head Gesture Recognition System with Online Capability
Wöhler, Nils-Christian, Bielefeld Univ.
Großekathöfer, Ulf, Bielefeld Univ.
Dierker, Angelika, Bielefeld Univ.
Hanheide, Marc, Univ. of Birmingham
Kopp, Stefan, Bielefeld Univ.
Hermann, Thomas, Bielefeld Univ.
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