loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Mouna Selmi ; Mounim A. El-Yacoubi and Bernadette Dorizzi

Affiliation: Institut Mines-Telecom / Telecom SudPari, France

ISBN: 978-989-8565-41-9

Keyword(s): Human Activity Recognition, Hidden Conditional Random Field, SVM/HCRF Combination, Space-time Interest Points’ Trajectories.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Human-Computer Interaction ; Image and Video Analysis ; Learning of Action Patterns ; Methodologies and Methods ; Motion and Tracking ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Physiological Computing Systems ; Software Engineering ; Video Analysis

Abstract: In this paper, we propose a novel human activity recognition approach based on STIPs’ trajectories as local descriptors of video sequences. This representation compares favorably with state of art feature extraction methods. In addition, we investigate the use of SVM/HCRF combination for temporal sequence modeling, where SVM is applied locally on short video segments to produce probability scores, the latter being considered as the input vectors to HCRF. This method constitutes a new contribution to the state of the art on activity recognition task. The obtained results demonstrate that our method is efficient and compares favorably with state of the art methods on human activity recognition.

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 3.227.249.234

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:
Selmi, M.; A. El-Yacoubi, M. and Dorizzi, B. (2013). A Combined SVM/HCRF Model for Activity Recognition based on STIPs Trajectories.In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8565-41-9, pages 568-572. DOI: 10.5220/0004267405680572

@conference{icpram13,
author={Mouna Selmi. and Mounim A. El{-}Yacoubi. and Bernadette Dorizzi.},
title={A Combined SVM/HCRF Model for Activity Recognition based on STIPs Trajectories},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2013},
pages={568-572},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004267405680572},
isbn={978-989-8565-41-9},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - A Combined SVM/HCRF Model for Activity Recognition based on STIPs Trajectories
SN - 978-989-8565-41-9
AU - Selmi, M.
AU - A. El-Yacoubi, M.
AU - Dorizzi, B.
PY - 2013
SP - 568
EP - 572
DO - 10.5220/0004267405680572

Login or register to post comments.

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