loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ngoc-Trung Tran 1 ; Fakhreddine Ababsa 2 and Maurice Charbit 3

Affiliations: 1 Telecom ParisTECH and University of Evry, France ; 2 University of Evry, France ; 3 Telecom ParisTECH, France

ISBN: 978-989-758-077-2

Keyword(s): 3D Face Tracking, 3D Pose Tracking, Rigid Tracking, Non-rigid Tracking, Face Matching, Synthesized Face, Face Matching.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Human-Computer Interaction ; Methodologies and Methods ; Motion and Tracking ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Physiological Computing Systems

Abstract: The non-rigid face tracking has been achieved many advances in recent years, but most of empirical experiments are restricted at near-frontal face. This report introduces a robust framework for pose-free tracking of non-rigid face. Our method consists of two phases: training and tracking. In the training phase, a large offline synthesized database is built to train landmark appearance models using linear Support Vector Machine (SVM). In the tracking phase, a two-step approach is proposed: the first step, namely initialization, benefits 2D SIFT matching between the current frame and a set of adaptive keyframes to estimate the rigid parameters. The second step obtains the whole set of parameters (rigid and non-rigid) using a heuristic method via pose-wise SVMs. The combination of these aspects makes our method work robustly up to 90° of vertical axial rotation. Moreover, our method appears to be robust even in the presence of fast movements and tracking losses. Comparing to other publi shed algorithms, our method offers a very good compromise of rigid and non-rigid parameter accuracies. This study gives a promising perspective because of the good results in terms of pose estimation (average error is less than 4°on BUFT dataset) and landmark tracking precision (5.8 pixel error compared to 6.8 of one state-of-the-art method on Talking Face video). These results highlight the potential of using synthetic data to track non-rigid face in unconstrained poses. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.172.100.232

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Tran, N.; Ababsa, F. and Charbit, M. (2015). Towards Pose-free Tracking of Non-rigid Face using Synthetic Data.In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM, ISBN 978-989-758-077-2, pages 37-44. DOI: 10.5220/0005179300370044

@conference{icpram15,
author={Ngoc{-}Trung Tran. and Fakhreddine Ababsa. and Maurice Charbit.},
title={Towards Pose-free Tracking of Non-rigid Face using Synthetic Data},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},
year={2015},
pages={37-44},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005179300370044},
isbn={978-989-758-077-2},
}

TY - CONF

JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - Towards Pose-free Tracking of Non-rigid Face using Synthetic Data
SN - 978-989-758-077-2
AU - Tran, N.
AU - Ababsa, F.
AU - Charbit, M.
PY - 2015
SP - 37
EP - 44
DO - 10.5220/0005179300370044

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.