التعرف على تعبيرات الوجه باستخدام Walidlet Hybrid Transform
المؤلفون
أصبح التحليل التلقائي لتعبيرات الوجه مجال اهتمام شديد في رؤية الكمبيوتر ومجتمعات أبحاث الذكاء الاصطناعي. في هذه الورقة ، تم تقديم نهج للتعرف على تعبيرات الوجه لتعبيرات النماذج الأولية الستة (أي الفرح والمفاجأة والغضب والحزن والخوف والاشمئزاز) استنادًا إلى نظام تشفير حركة الوجه (FACS). يحاول النهج الاستفادة من مجموعة من المحولات المختلفة (Walid Let hybrid transform) ؛ أنها تتكون من تحويل فورييه السريع ؛ تحويل الرادون وتحويل متعدد الموجات لاستخراج الميزة. تم استخدام خريطة ميزات التنظيم الذاتي لـ Korhonen (SOFM) لتجميع الأنماط بناءً على الميزات التي تم الحصول عليها من التحويل الهجين أعلاه. تظهر النتيجة أن الطريقة لديها دقة جيدة جدًا في التعرف على تعبيرات الوجه. ومع ذلك ، فإن الطريقة المقترحة لها العديد من الميزات الواعدة التي تجعلها ممتعة. يوفر هذا النهج طريقة جديدة لاستخراج الميزات التي تتغلب فيها على مشكلة الإضاءة ، الوجوه التي تختلف من فرد إلى آخر بشكل كبير بسبب اختلاف العمر والعرق والجنس ومستحضرات التجميل ، كما أنها لا تتطلب تطبيعًا دقيقًا ومعادلة الإضاءة. تم تحقيق متوسط دقة تجميع بنسبة 94.8٪ لستة تعبيرات أساسية ، حيث تم استخدام قواعد بيانات مختلفة لاختبار الطريقة.
الكلمات المفتاحية:
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الرخصة
الحقوق الفكرية (c) 2020 Journal Port Science Research

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كيفية الاقتباس
- منشور: 2020-11-11
- إصدار: مجلد 3 عدد 1 (2020)
- القسم: Articles






