دانلود مقاله انگلیسی رایگان:بهبود تأیید کاربر در تعامل انسان و روبات از طریق ورودی های صوتی یا تصویری از طریق ارزیابی کیفیت نمونه - 2021
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  • Improving user verification in human-robot interaction from audio or image inputs through sample quality assessment Improving user verification in human-robot interaction from audio or image inputs through sample quality assessment
    Improving user verification in human-robot interaction from audio or image inputs through sample quality assessment

    سال انتشار:

    2021


    عنوان انگلیسی مقاله:

    Improving user verification in human-robot interaction from audio or image inputs through sample quality assessment


    ترجمه فارسی عنوان مقاله:

    بهبود تأیید کاربر در تعامل انسان و روبات از طریق ورودی های صوتی یا تصویری از طریق ارزیابی کیفیت نمونه


    منبع:

    Sciencedirect - Elsevier - Pattern Recognition Letters, 149 (2021) 179-184: doi:10:1016/j:patrec:2021:06:014


    نویسنده:

    David Freire-Obregón, Kevin Rosales-Santana, Pedro A. Marín-Reyes, Adrian Penate-Sanchez∗, Javier Lorenzo-Navarro, Modesto Castrillón-Santana


    چکیده انگلیسی:

    In this paper, we tackle the task of improving biometric verification in the context of Human-Robot Interaction (HRI). A robot that wants to identify a specific person to provide a service can do so by either image verification or, if light conditions are not favourable, through voice verification. In our approach, we will take advantage of the possibility a robot has of recovering further data until it is sure of the identity of the person. The key contribution is that we select from both image and audio signals the parts that are of higher confidence. For images we use a system that looks at the face of each person and selects frames in which the confidence is high while keeping those frames separate in time to avoid using very similar facial appearance. For audio our approach tries to find the parts of the signal that contain a person talking, avoiding those in which noise is present by segmenting the signal. Once the parts of interest are found, each input is described with an independent deep learning architecture that obtains a descriptor for each kind of input (face/voice). We also present in this paper fusion methods that improve performance by combining the features from both face and voice, results to validate this are shown for each independent input and for the fusion methods.© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
    Keywords: Biometric verification | Audiovisual verification | Human robot interaction


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 6
    حجم فایل: 902 کیلوبایت

    قیمت: رایگان


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