Pose and Illumination Invariance of Attribute Detectors in Person Re-identification

  • Authors

    • Mohammadali Saghafi
    • Aini Hussain
    • Mohamad Hanif Md. Saad
    • Mohd Asyraf Zulkifley
    • Nooritawati Md Tahir
    • Mohd Faisal Ibrahim
    2018-10-02
    https://doi.org/10.14419/ijet.v7i4.11.20796
  • person re-identification, Attribute, metric learning.

  • Abstract

    The use of attributes in person re-identification and video surveillance applications has grabbed attentions of many researchers in recent times. Attributes are suitable tools for mid-level representation of a part or a region in an image as it is more similar to human perception as compared to the quantitative nature of the normal visual features description of those parts. Hence, in this paper, the preliminary experimental results to evaluate the robustness of attribute detectors against pose and light variations in contrast to the use of local appearance features is discussed. Results attained proven that the attribute-based detectors are capable to overcome the negative impact of pose and light variation towards person re-identification activities. In addition, the degree of importance of different attributes in re-identification is evaluated and compared with other previous works in this field.

     

     

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  • How to Cite

    Saghafi, M., Hussain, A., Hanif Md. Saad, M., Asyraf Zulkifley, M., Md Tahir, N., & Faisal Ibrahim, M. (2018). Pose and Illumination Invariance of Attribute Detectors in Person Re-identification. International Journal of Engineering & Technology, 7(4.11), 174-178. https://doi.org/10.14419/ijet.v7i4.11.20796

    Received date: 2018-10-02

    Accepted date: 2018-10-02

    Published date: 2018-10-02