Decision method choice in a human posture recognition context

التفاصيل البيبلوغرافية
العنوان: Decision method choice in a human posture recognition context
المؤلفون: Perrin, Stéphane, Benoit, Eric, Coquin, Didier
المصدر: Human-Computer Systems Interaction. Backgrounds and Applications 4, 4, 2018
سنة النشر: 2018
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
الوصف: Human posture recognition provides a dynamic field that has produced many methods. Using fuzzy subsets based data fusion methods to aggregate the results given by different types of recognition processes is a convenient way to improve recognition methods. Nevertheless, choosing a defuzzification method to imple-ment the decision is a crucial point of this approach. The goal of this paper is to present an approach where the choice of the defuzzification method is driven by the constraints of the final data user, which are expressed as limitations on indica-tors like confidence or accuracy. A practical experimentation illustrating this ap-proach is presented: from a depth camera sensor, human posture is interpreted and the defuzzification method is selected in accordance with the constraints of the final information consumer. The paper illustrates the interest of the approach in a context of postures based human robot communication.
نوع الوثيقة: Working Paper
DOI: 10.1007/978-3-319-62120-3_11
URL الوصول: http://arxiv.org/abs/1807.04170
رقم الانضمام: edsarx.1807.04170
قاعدة البيانات: arXiv
الوصف
DOI:10.1007/978-3-319-62120-3_11