Human-object interaction recognition by modeling context

Qun Zhang; Wei Liang; Xiabing Liu; Yumeng Wang

doi:10.1007/978-3-319-21963-9_35

Human-object interaction recognition by modeling context

Qun Zhang^*, Wei Liang, Xiabing Liu, Yumeng Wang

^*此作品的通讯作者

计算机学院

Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

In this paper, we present a new method to recognize humanobject interactions by modeling the context between human actions and manipulated objects. It is a challenging task due to severe occlusion between human and objects during the interacting process. While human actions and objects can provide strong context information, such as some action happening is usually related to a certain object, by which we can improve the accuracy of recognition for both of them. In this paper, we use global and local temporal features from skeleton sequences to model actions, and kernel features are applied to describe objects. We optimize all possible solutions from actions and objects by modeling the context between them. The results of experiments show the effectiveness of our method.

源语言	英语
主期刊名	Image and Graphics - 8th International Conference, ICIG 2015, Proceedings
编辑	Yu-Jin Zhang
出版商	Springer Verlag
页	385-395
页数	11
ISBN（印刷版）	9783319219622
DOI	https://doi.org/10.1007/978-3-319-21963-9_35
出版状态	已出版 - 2015
活动	8th International Conference on Image and Graphics, ICIG 2015 - Tianjin, 中国期限: 13 8月 2015 → 16 8月 2015

出版系列

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	9218
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

会议

会议	8th International Conference on Image and Graphics, ICIG 2015
国家/地区	中国
市	Tianjin
时期	13/08/15 → 16/08/15

访问文件

10.1007/978-3-319-21963-9_35

其它文件与链接

链接到 Scopus 的出版物

引用此

Zhang, Q., Liang, W., Liu, X., & Wang, Y. (2015). Human-object interaction recognition by modeling context. 在 Y.-J. Zhang (编辑), Image and Graphics - 8th International Conference, ICIG 2015, Proceedings (页码 385-395). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 9218). Springer Verlag. https://doi.org/10.1007/978-3-319-21963-9_35

Zhang, Qun ; Liang, Wei ; Liu, Xiabing 等. / Human-object interaction recognition by modeling context. Image and Graphics - 8th International Conference, ICIG 2015, Proceedings. 编辑 / Yu-Jin Zhang. Springer Verlag, 2015. 页码 385-395 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{57b15fe11c9a499b8e1a0e3a426b7c6e,

title = "Human-object interaction recognition by modeling context",

abstract = "In this paper, we present a new method to recognize humanobject interactions by modeling the context between human actions and manipulated objects. It is a challenging task due to severe occlusion between human and objects during the interacting process. While human actions and objects can provide strong context information, such as some action happening is usually related to a certain object, by which we can improve the accuracy of recognition for both of them. In this paper, we use global and local temporal features from skeleton sequences to model actions, and kernel features are applied to describe objects. We optimize all possible solutions from actions and objects by modeling the context between them. The results of experiments show the effectiveness of our method.",

keywords = "Action recognition, Context, Human-object interaction, Object classification",

author = "Qun Zhang and Wei Liang and Xiabing Liu and Yumeng Wang",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 8th International Conference on Image and Graphics, ICIG 2015 ; Conference date: 13-08-2015 Through 16-08-2015",

year = "2015",

doi = "10.1007/978-3-319-21963-9_35",

language = "English",

isbn = "9783319219622",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "385--395",

editor = "Yu-Jin Zhang",

booktitle = "Image and Graphics - 8th International Conference, ICIG 2015, Proceedings",

address = "Germany",

}

Zhang, Q, Liang, W, Liu, X & Wang, Y 2015, Human-object interaction recognition by modeling context. 在 Y-J Zhang (编辑), Image and Graphics - 8th International Conference, ICIG 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 9218, Springer Verlag, 页码 385-395, 8th International Conference on Image and Graphics, ICIG 2015, Tianjin, 中国, 13/08/15. https://doi.org/10.1007/978-3-319-21963-9_35

Human-object interaction recognition by modeling context. / Zhang, Qun; Liang, Wei; Liu, Xiabing 等.
Image and Graphics - 8th International Conference, ICIG 2015, Proceedings. 编辑 / Yu-Jin Zhang. Springer Verlag, 2015. 页码 385-395 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 9218).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Human-object interaction recognition by modeling context

AU - Zhang, Qun

AU - Liang, Wei

AU - Liu, Xiabing

AU - Wang, Yumeng

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - In this paper, we present a new method to recognize humanobject interactions by modeling the context between human actions and manipulated objects. It is a challenging task due to severe occlusion between human and objects during the interacting process. While human actions and objects can provide strong context information, such as some action happening is usually related to a certain object, by which we can improve the accuracy of recognition for both of them. In this paper, we use global and local temporal features from skeleton sequences to model actions, and kernel features are applied to describe objects. We optimize all possible solutions from actions and objects by modeling the context between them. The results of experiments show the effectiveness of our method.

AB - In this paper, we present a new method to recognize humanobject interactions by modeling the context between human actions and manipulated objects. It is a challenging task due to severe occlusion between human and objects during the interacting process. While human actions and objects can provide strong context information, such as some action happening is usually related to a certain object, by which we can improve the accuracy of recognition for both of them. In this paper, we use global and local temporal features from skeleton sequences to model actions, and kernel features are applied to describe objects. We optimize all possible solutions from actions and objects by modeling the context between them. The results of experiments show the effectiveness of our method.

KW - Action recognition

KW - Context

KW - Human-object interaction

KW - Object classification

UR - http://www.scopus.com/inward/record.url?scp=84943644739&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-21963-9_35

DO - 10.1007/978-3-319-21963-9_35

M3 - Conference contribution

AN - SCOPUS:84943644739

SN - 9783319219622

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 385

EP - 395

BT - Image and Graphics - 8th International Conference, ICIG 2015, Proceedings

A2 - Zhang, Yu-Jin

PB - Springer Verlag

T2 - 8th International Conference on Image and Graphics, ICIG 2015

Y2 - 13 August 2015 through 16 August 2015

ER -

Zhang Q, Liang W, Liu X, Wang Y. Human-object interaction recognition by modeling context. 在 Zhang YJ, 编辑, Image and Graphics - 8th International Conference, ICIG 2015, Proceedings. Springer Verlag. 2015. 页码 385-395. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-21963-9_35

Human-object interaction recognition by modeling context

摘要

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会议

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引用此