Similarity measure for multi-attribute data

Chuanjun Li*, B. Prabhakaran, Si Qing Zheng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Efficient recognition of haptic data such as 3D motion capture data and sign language sensory data can have wide applications in the interactive computer animation and sign language automatic translation areas. For this purpose, we propose a similarity measure for multi-attribute haptic data, a new form of multimedia signal. The proposed similarity measure, based on singular value decomposition, captures the most important features of the signal data, allows for different signal generating rates and reasonable variations in similar signals. Experiments with real life and synthetic data demonstrate that the proposed similarity measure can capture the similarities of motions with different speeds and different lengths and can have up to 100% recognition rates.

Original languageEnglish
Title of host publication2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1149-1152
Number of pages4
ISBN (Print)0780388747, 9780780388741
DOIs
Publication statusPublished - 2005
Externally publishedYes
Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
Duration: 18 Mar 200523 Mar 2005

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
VolumeII
ISSN (Print)1520-6149

Conference

Conference2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Country/TerritoryUnited States
CityPhiladelphia, PA
Period18/03/0523/03/05

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