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Authors: Kenji Nishida 1 ; Takumi Kobayashi 1 ; Taro Iwamoto 2 and Shinya Yamasaki 1

Affiliations: 1 National Institute of Advanced Industrial Science and Technology (AIST), Japan ; 2 Mazda Motor Co., Japan

ISBN: 978-989-758-157-1

Keyword(s): Action Prediction, Feature Selection, Intelligent Transport System, Image Feature Extraction.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer-Supported Education ; Data Manipulation ; Domain Applications and Case Studies ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Image Processing and Artificial Vision Applications ; Industrial, Financial and Medical Applications ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Support Vector Machines and Applications ; Theory and Methods

Abstract: In this study, we propose a method to predict how the target object move (run or walk) in the future by using only appearance-based image features. Such kind of motion prediction significantly contributes to intelligent braking system in cars; by knowing that the objects will run in several seconds such as in crossing streets, the car can start to brake in advance, which effectively reduces the risk for crash accidents. In the proposed method, we empirically evaluate which frames preceding the target action, 'running' in this case, are effective for predicting it in the framework of feature selection. By using the most effective frames at which the image features are extracted, we can build the action prediction method. In the experiments, those frames are found around 0.37 second before running action and we also show that they are closely related to human motion phases from walking to running from the viewpoint of biomechanics.

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Paper citation in several formats:
Nishida, K.; Kobayashi, T.; Iwamoto, T. and Yamasaki, S. (2015). Pedestrian Action Prediction using Static Image Feature.In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 3 NCTA: NCTA, (ECTA 2015) ISBN 978-989-758-157-1, pages 99-105. DOI: 10.5220/0005593600990105

@conference{ncta15,
author={Nishida, K. and Takumi Kobayashi. and Taro Iwamoto. and Shinya Yamasaki.},
title={Pedestrian Action Prediction using Static Image Feature},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 3 NCTA: NCTA, (ECTA 2015)},
year={2015},
pages={99-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005593600990105},
isbn={978-989-758-157-1},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 3 NCTA: NCTA, (ECTA 2015)
TI - Pedestrian Action Prediction using Static Image Feature
SN - 978-989-758-157-1
AU - Nishida, K.
AU - Kobayashi, T.
AU - Iwamoto, T.
AU - Yamasaki, S.
PY - 2015
SP - 99
EP - 105
DO - 10.5220/0005593600990105

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