Mixed signature descriptor with global invariants for 3D motion trajectory perception and recognition

Jianyu Yang; Y. F. Li; Keyi Wang

doi:10.1109/IEEM.2010.5674635

Mixed signature descriptor with global invariants for 3D motion trajectory perception and recognition

Jianyu Yang
, Y. F. Li^*
, Keyi Wang

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

Motion perception and recognition by trajectory are important for motion analysis. A flexible and adaptable descriptor of motion trajectory plays important role in the performance of perception and recognition. Motion trajectories usually use raw data for many tasks, which is not effective. Shape descriptors and signature of differential invariants are good for local features but global feature is lacking. In this paper, we present a mixed signature descriptor with global invariants which were not included in previous descriptors. The mixed signature is capable of capturing the global feature and is flexible in many tasks. The conducted experiments verified the capability of our method. ©2010 IEEE.

Original language	English
Title of host publication	IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management
Pages	1952-1956
DOIs	https://doi.org/10.1109/IEEM.2010.5674635
Publication status	Published - 2010
Event	2010 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM2010) - Venetian Macao Resort Hotel, Macao, China Duration: 7 Dec 2010 → 10 Dec 2010

Conference

Conference	2010 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM2010)
Place	China
City	Macao
Period	7/12/10 → 10/12/10

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@inproceedings{3bbc01c7271b4bd1b16f231e579a8dc5,

title = "Mixed signature descriptor with global invariants for 3D motion trajectory perception and recognition",

abstract = "Motion perception and recognition by trajectory are important for motion analysis. A flexible and adaptable descriptor of motion trajectory plays important role in the performance of perception and recognition. Motion trajectories usually use raw data for many tasks, which is not effective. Shape descriptors and signature of differential invariants are good for local features but global feature is lacking. In this paper, we present a mixed signature descriptor with global invariants which were not included in previous descriptors. The mixed signature is capable of capturing the global feature and is flexible in many tasks. The conducted experiments verified the capability of our method. {\textcopyright}2010 IEEE.",

author = "Jianyu Yang and Li, \{Y. F.\} and Keyi Wang",

year = "2010",

doi = "10.1109/IEEM.2010.5674635",

language = "English",

isbn = "9781424485031",

pages = "1952--1956",

booktitle = "IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management",

note = "2010 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM2010) ; Conference date: 07-12-2010 Through 10-12-2010",

}

Yang, J, Li, YF & Wang, K 2010, Mixed signature descriptor with global invariants for 3D motion trajectory perception and recognition. in IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management., 5674635, pp. 1952-1956, 2010 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM2010), Macao, China, 7/12/10. https://doi.org/10.1109/IEEM.2010.5674635

Mixed signature descriptor with global invariants for 3D motion trajectory perception and recognition. / Yang, Jianyu; Li, Y. F.; Wang, Keyi.
IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management. 2010. p. 1952-1956 5674635.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Mixed signature descriptor with global invariants for 3D motion trajectory perception and recognition

AU - Yang, Jianyu

AU - Li, Y. F.

AU - Wang, Keyi

PY - 2010

Y1 - 2010

N2 - Motion perception and recognition by trajectory are important for motion analysis. A flexible and adaptable descriptor of motion trajectory plays important role in the performance of perception and recognition. Motion trajectories usually use raw data for many tasks, which is not effective. Shape descriptors and signature of differential invariants are good for local features but global feature is lacking. In this paper, we present a mixed signature descriptor with global invariants which were not included in previous descriptors. The mixed signature is capable of capturing the global feature and is flexible in many tasks. The conducted experiments verified the capability of our method. ©2010 IEEE.

AB - Motion perception and recognition by trajectory are important for motion analysis. A flexible and adaptable descriptor of motion trajectory plays important role in the performance of perception and recognition. Motion trajectories usually use raw data for many tasks, which is not effective. Shape descriptors and signature of differential invariants are good for local features but global feature is lacking. In this paper, we present a mixed signature descriptor with global invariants which were not included in previous descriptors. The mixed signature is capable of capturing the global feature and is flexible in many tasks. The conducted experiments verified the capability of our method. ©2010 IEEE.

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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-78751684017&origin=recordpage

U2 - 10.1109/IEEM.2010.5674635

DO - 10.1109/IEEM.2010.5674635

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781424485031

SP - 1952

EP - 1956

BT - IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management

T2 - 2010 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM2010)

Y2 - 7 December 2010 through 10 December 2010

ER -

Mixed signature descriptor with global invariants for 3D motion trajectory perception and recognition

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