Computational Intelligence Methods for Facial Emotion Recognition: A Comparative Study
سال انتشار: 1397
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 318
فایل این مقاله در 13 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
این مقاله در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_SPRE-2-2_001
تاریخ نمایه سازی: 23 تیر 1398
چکیده مقاله:
Emotion recognition plays a critical role in the human communications. It is one of the major ways to be in touch with others. Four parameters including eye opening size, mouth opening size, ratio of eye opening size to eye width and mouth width are used as a reduced-size feature set in this study. This paper compares the performance of facial emotion recognition classification models based on the following computational intelligence methods: fuzzy logic, chaotic gravitational search algorithm (CGSA), and artificial neural network (ANN) from eyes and mouth features tested on the FACES database. Experimental results show the superior performance of ANN-based method compared to fuzzy- and CGSA-based methods. In addition, this comparative study triggers the idea of a hybrid system based on these computational methods that outperforms the human detection system.
کلیدواژه ها:
نویسندگان
Fatemeh Shahrabi Farahani
Department of Mechatronic Engineering, Islamic Azad University, South Tehran Branch
Mansour Sheikhan
Electrical Engineering Department, South Tehran Branch, Islamic Azad University, Tehran, Iran.