RETRACTED ARTICLE: Improving large-scale population recognition through structure optimization

Sue Inn Ch'ng, Kah Phooi Seng, Li Minn Ang

Research output: Book chapter/Published conference paperConference paper

Abstract

A problem that is commonly faced by large-scale population system is the high-dimensionality of data that needs to be processed at a given time. In this paper, a new face recognition training structure is proposed in which the large-scale population is split into smaller groups to be processed separately. To improve classification the proposed system uses global and local linear discriminant analysis together with a similarity measure to maximize the separation of features within each group. Implementations of the proposed structure indicate that the presented structure has a better performance and faster training time compared to a conventional training structure.

Original languageEnglish
Title of host publicationProceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
PublisherIEEE Computer Society
Pages380-383
Number of pages4
Volume5
ISBN (Print)9781424455386
DOIs
Publication statusPublished - 01 Jan 2010

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    Ch'ng, S. I., Seng, K. P., & Ang, L. M. (2010). RETRACTED ARTICLE: Improving large-scale population recognition through structure optimization. In Proceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010 (Vol. 5, pp. 380-383). [5564102] IEEE Computer Society. https://doi.org/10.1109/ICCSIT.2010.5564102