Viewpoint insensitive actions recognition using hidden conditional random fields

Xiaofei Ji; Honghai Liu; Yibo Li

doi:10.1007/978-3-642-15387-7_41

Viewpoint insensitive actions recognition using hidden conditional random fields

Xiaofei Ji^*
, Honghai Liu
, Yibo Li

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

The viewpoint issue has been one of the bottlenecks for research development and practical implementation of human motion analysis. In this paper, we introduce a new method, e.g., hidden conditional random fields(HCRFs) to achieve viewpoint insensitive human action recognition. The HCRF model can relax the independence assumption of the generative models. So it is very suitable to model the human actions from different actors and different viewpoints. Experiment results on a public dataset demonstrate the effectiveness and robustness of our method.

Original language	English
Title of host publication	Knowledge-Based and Intelligent Information and Engineering Systems - 14th International Conference, KES 2010, Proceedings
Pages	369-378
Number of pages	10
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-15387-7_41
State	Published - 2010
Externally published	Yes
Event	14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010 - Cardiff, United Kingdom Duration: 8 Sep 2010 → 10 Sep 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	6276 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010
Country/Territory	United Kingdom
City	Cardiff
Period	8/09/10 → 10/09/10

Keywords

Conditional random field
Hidden conditional random field
Human action recognition
Viewpoint insensitive

Access to Document

10.1007/978-3-642-15387-7_41

Cite this

Ji, X., Liu, H., & Li, Y. (2010). Viewpoint insensitive actions recognition using hidden conditional random fields. In Knowledge-Based and Intelligent Information and Engineering Systems - 14th International Conference, KES 2010, Proceedings (PART 1 ed., pp. 369-378). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6276 LNAI, No. PART 1). https://doi.org/10.1007/978-3-642-15387-7_41

Ji, Xiaofei ; Liu, Honghai ; Li, Yibo. / Viewpoint insensitive actions recognition using hidden conditional random fields. Knowledge-Based and Intelligent Information and Engineering Systems - 14th International Conference, KES 2010, Proceedings. PART 1. ed. 2010. pp. 369-378 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{95e70a785bfb4b608b0c5c8509ff7339,

title = "Viewpoint insensitive actions recognition using hidden conditional random fields",

abstract = "The viewpoint issue has been one of the bottlenecks for research development and practical implementation of human motion analysis. In this paper, we introduce a new method, e.g., hidden conditional random fields(HCRFs) to achieve viewpoint insensitive human action recognition. The HCRF model can relax the independence assumption of the generative models. So it is very suitable to model the human actions from different actors and different viewpoints. Experiment results on a public dataset demonstrate the effectiveness and robustness of our method.",

keywords = "Conditional random field, Hidden conditional random field, Human action recognition, Viewpoint insensitive",

author = "Xiaofei Ji and Honghai Liu and Yibo Li",

year = "2010",

doi = "10.1007/978-3-642-15387-7\_41",

language = "英语",

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

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booktitle = "Knowledge-Based and Intelligent Information and Engineering Systems - 14th International Conference, KES 2010, Proceedings",

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Ji, X, Liu, H & Li, Y 2010, Viewpoint insensitive actions recognition using hidden conditional random fields. in Knowledge-Based and Intelligent Information and Engineering Systems - 14th International Conference, KES 2010, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 6276 LNAI, pp. 369-378, 14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010, Cardiff, United Kingdom, 8/09/10. https://doi.org/10.1007/978-3-642-15387-7_41

Viewpoint insensitive actions recognition using hidden conditional random fields. / Ji, Xiaofei; Liu, Honghai; Li, Yibo.
Knowledge-Based and Intelligent Information and Engineering Systems - 14th International Conference, KES 2010, Proceedings. PART 1. ed. 2010. p. 369-378 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6276 LNAI, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Viewpoint insensitive actions recognition using hidden conditional random fields

AU - Ji, Xiaofei

AU - Liu, Honghai

AU - Li, Yibo

PY - 2010

Y1 - 2010

N2 - The viewpoint issue has been one of the bottlenecks for research development and practical implementation of human motion analysis. In this paper, we introduce a new method, e.g., hidden conditional random fields(HCRFs) to achieve viewpoint insensitive human action recognition. The HCRF model can relax the independence assumption of the generative models. So it is very suitable to model the human actions from different actors and different viewpoints. Experiment results on a public dataset demonstrate the effectiveness and robustness of our method.

AB - The viewpoint issue has been one of the bottlenecks for research development and practical implementation of human motion analysis. In this paper, we introduce a new method, e.g., hidden conditional random fields(HCRFs) to achieve viewpoint insensitive human action recognition. The HCRF model can relax the independence assumption of the generative models. So it is very suitable to model the human actions from different actors and different viewpoints. Experiment results on a public dataset demonstrate the effectiveness and robustness of our method.

KW - Conditional random field

KW - Hidden conditional random field

KW - Human action recognition

KW - Viewpoint insensitive

UR - https://www.scopus.com/pages/publications/78449234395

U2 - 10.1007/978-3-642-15387-7_41

DO - 10.1007/978-3-642-15387-7_41

M3 - 会议稿件

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SN - 3642153860

SN - 9783642153860

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

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BT - Knowledge-Based and Intelligent Information and Engineering Systems - 14th International Conference, KES 2010, Proceedings

T2 - 14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010

Y2 - 8 September 2010 through 10 September 2010

ER -

Ji X, Liu H, Li Y. Viewpoint insensitive actions recognition using hidden conditional random fields. In Knowledge-Based and Intelligent Information and Engineering Systems - 14th International Conference, KES 2010, Proceedings. PART 1 ed. 2010. p. 369-378. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-15387-7_41

Viewpoint insensitive actions recognition using hidden conditional random fields

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