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    Soft-biometric attributes from selfie images

    Date
    2019-09-22
    Author
    Rattani, Ajita
    Agrawal, Mudit
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    Citation
    Rattani A., Agrawal M. (2019) Soft-Biometric Attributes from Selfie Images. In: Rattani A., Derakhshani R., Ross A. (eds) Selfie Biometrics. Advances in Computer Vision and Pattern Recognition. Springer, Cham
    Abstract
    The aim of this chapter is to discuss the soft-biometric attributes that can be extracted from selfie images acquired from mobile devices. Existing literature suggests that various features in demographics, such as gender and age, in physical, such as periocular and eyebrow, and in material, such as eyeglasses and clothing, have been extracted from selfie images for continuous user authentication and performance enhancement of primary biometric traits. Due to the limited hardware resources, low resolution of front-facing cameras, and the usage of the device in different environmental conditions, factors such as robustness to low-quality data, consent-free acquisition, lower computational complexity, and privacy, favor soft-biometric prediction in mobile devices.
    Description
    Click on the DOI link to access the article (may not be free).
    URI
    https://doi.org/10.1007/978-3-030-26972-2_10
    http://hdl.handle.net/10057/16812
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