EAI Endorsed Transactions on Pervasive Health and Technology 17(12): e2

Research Article

On the Extraction of Anthropometric Parameters by Visual and Non-Visual Means

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  • @ARTICLE{10.4108/eai.7-9-2017.153064,
        author={O. Kainz and M. Michalko and F. Jakab},
        title={On the Extraction of Anthropometric Parameters by Visual and Non-Visual Means},
        journal={EAI Endorsed Transactions on Pervasive Health and Technology},
        volume={17},
        number={12},
        publisher={EAI},
        journal_a={PHAT},
        year={2017},
        month={9},
        keywords={anthropometer, computer vision, description language, image processing, skeleton model, static image, structural anthropometry, human body.},
        doi={10.4108/eai.7-9-2017.153064}
    }
    
  • O. Kainz
    M. Michalko
    F. Jakab
    Year: 2017
    On the Extraction of Anthropometric Parameters by Visual and Non-Visual Means
    PHAT
    EAI
    DOI: 10.4108/eai.7-9-2017.153064
O. Kainz1,*, M. Michalko1, F. Jakab1
  • 1: DCI, FEEI, Technical University of Košice
*Contact email: ondrej.kainz@tuke.sk

Abstract

In this paper the system for collection and recording of anthropometric data is presented, along with the novel techniques for extraction of such data. The very system is built on selected open-source platform having developed various plugins as a part of the project. Means for the extraction follow two approaches: visual and non-visual. The first presumes the acquiring of data from static 2D image, the latter gets data through the direct measurement. Visual approach utilizes several principles following the image processing and related face detection algorithms. Moreover, known anthropometric relations are utilized to estimate other human body proportions. As for the non-visual approach, the hardware for direct measurement of human body parameters is designed, implemented and tested in the real environment. The output in the form of data of individual user may serve for statistical comparison with other users. Further, data of all users is to be used for correlation studies with several diseases and changes of overall health condition. In addition, the extracted data follow the concept of newly proposed Human body description language (HBDL) that may be used in various scientific fields and applications or various programming languages. Thus providing the standardized and structured form of data entry.