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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.10 No.3
- 발행연도
- 2015.5
- 수록면
- 1,264 - 1,274 (11page)
이용수
초록· 키워드
오류제보하기
Human action recognition received many interest in the computer vision community. Most of the existing methods focus on either construct robust descriptor from the temporal domain, or computational method to exploit the discriminative power of the descriptor. In this paper we explore the idea of using local action attributes to form an action descriptor, where an action is no longer characterized with the motion changes in the temporal domain but the local semantic description of the action. We propose an novel framework where introduces local action attributes to represent an action for the final human action categorization. The local action attributes are defined for each body part which are independent from the global action. The resulting attribute descriptor is used to jointly model human action to achieve robust performance. In addition, we conduct some study on the impact of using body local and global low-level feature for the aforementioned attributes. Experiments on the KTH dataset and the MV-TJU dataset show that our local action attribute based descriptor improve action recognition performance.
목차
Abstract
1. Introduction
2. Related Work
3. Method Overview
4. Partwise Bag-of-Words Representation
5. Action Attribute-based Action Recognition
6. Experiments and Results
References
참고문헌 (38)
참고문헌 신청
1. [학술대회논문] - A. Yilmaz / 2005 / Recognizing human actions in videos acquired by uncalibrated moving cameras / ICCV : 150 ~ 157
2. [학술지(정기간행물)] - J. Wu / 2014 / Learning effective event models to recognize a large number of human actions / IEEE Transactions on Multimedia
3. [학술지(정기간행물)] - J. Wang / 2014 / Learning actionlet ensemble for 3d human action recognition / Transactions on Pattern Analysis and Machine Intelligence
4. [학술지(정기간행물)] - Zan Gao / 2014 / Human Action Recognition Using Pyramid Histograms of Oriented Gradients and Collaborative Multi-task Learning / KSII Transactions on Internet and Information Systems 8 (2) : 483 ~ 503
5. [학술대회논문] - C. Schuldt / 2004 / Recognizing human actions: A local svm approach / ICPR : 32 ~ 36
2. [학술지(정기간행물)] - J. Wu / 2014 / Learning effective event models to recognize a large number of human actions / IEEE Transactions on Multimedia
3. [학술지(정기간행물)] - J. Wang / 2014 / Learning actionlet ensemble for 3d human action recognition / Transactions on Pattern Analysis and Machine Intelligence
4. [학술지(정기간행물)] - Zan Gao / 2014 / Human Action Recognition Using Pyramid Histograms of Oriented Gradients and Collaborative Multi-task Learning / KSII Transactions on Internet and Information Systems 8 (2) : 483 ~ 503
5. [학술대회논문] - C. Schuldt / 2004 / Recognizing human actions: A local svm approach / ICPR : 32 ~ 36
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