Using dynamic programming to match human behavior sequences

Yan Chen; Qiang Wu; Xiangjian He

doi:10.1109/ICARCV.2008.4795746

Using dynamic programming to match human behavior sequences

Yan Chen, Qiang Wu, Xiangjian He

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

7 Citations (Scopus)

Abstract

This paper proposed a new approach for recognition and matching the human behavior sequence. Each human behavior sequence is represented by its key postures to greatly reduce the computation time. Normalization is applied to all the behavior sequences key postures for matching. A dynamic time warping (DTW) algorithm is used to perform the alignment of two time series. Experiments are carried out on an open human behavior database and exciting results have been obtained.

Original language	English
Title of host publication	2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008
Pages	1498-1503
Number of pages	6
DOIs	https://doi.org/10.1109/ICARCV.2008.4795746
Publication status	Published - 2008
Externally published	Yes
Event	2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008 - Hanoi, Viet Nam Duration: 17 Dec 2008 → 20 Dec 2008

Publication series

Name	2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008

Conference

Conference	2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008
Country/Territory	Viet Nam
City	Hanoi
Period	17/12/08 → 20/12/08

Keywords

Dynamic time warping
Key postures
Sequence matching

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/ICARCV.2008.4795746

Cite this

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title = "Using dynamic programming to match human behavior sequences",

abstract = "This paper proposed a new approach for recognition and matching the human behavior sequence. Each human behavior sequence is represented by its key postures to greatly reduce the computation time. Normalization is applied to all the behavior sequences key postures for matching. A dynamic time warping (DTW) algorithm is used to perform the alignment of two time series. Experiments are carried out on an open human behavior database and exciting results have been obtained.",

keywords = "Dynamic time warping, Key postures, Sequence matching",

author = "Yan Chen and Qiang Wu and Xiangjian He",

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doi = "10.1109/ICARCV.2008.4795746",

language = "English",

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pages = "1498--1503",

booktitle = "2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008",

note = "2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008 ; Conference date: 17-12-2008 Through 20-12-2008",

}

Chen, Y, Wu, Q & He, X 2008, Using dynamic programming to match human behavior sequences. in 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008., 4795746, 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008, pp. 1498-1503, 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008, Hanoi, Viet Nam, 17/12/08. https://doi.org/10.1109/ICARCV.2008.4795746

Using dynamic programming to match human behavior sequences. / Chen, Yan; Wu, Qiang; He, Xiangjian.
2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008. 2008. p. 1498-1503 4795746 (2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008).

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

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T1 - Using dynamic programming to match human behavior sequences

AU - Chen, Yan

AU - Wu, Qiang

AU - He, Xiangjian

PY - 2008

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N2 - This paper proposed a new approach for recognition and matching the human behavior sequence. Each human behavior sequence is represented by its key postures to greatly reduce the computation time. Normalization is applied to all the behavior sequences key postures for matching. A dynamic time warping (DTW) algorithm is used to perform the alignment of two time series. Experiments are carried out on an open human behavior database and exciting results have been obtained.

AB - This paper proposed a new approach for recognition and matching the human behavior sequence. Each human behavior sequence is represented by its key postures to greatly reduce the computation time. Normalization is applied to all the behavior sequences key postures for matching. A dynamic time warping (DTW) algorithm is used to perform the alignment of two time series. Experiments are carried out on an open human behavior database and exciting results have been obtained.

KW - Dynamic time warping

KW - Key postures

KW - Sequence matching

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DO - 10.1109/ICARCV.2008.4795746

M3 - Conference contribution

AN - SCOPUS:64549148331

SN - 9781424422876

T3 - 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008

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BT - 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008

T2 - 2008 10th International Conference on Control, Automation, Robotics and Vision, ICARCV 2008

Y2 - 17 December 2008 through 20 December 2008

ER -

Using dynamic programming to match human behavior sequences

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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