Enhanced Forest Microexpression Recognition Based on Optical Flow Direction Histogram and Deep Multiview Network
المؤلف
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-08-31
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
In order to recognize the instantaneous changes of facial microexpressions in natural environment, a method based on optical flow direction histogram and depth multiview network to enhance forest microexpression recognition was proposed.
In the preprocessing stage, the histogram equalization of the acquired face image is performed, and then the dense key points of the face are detected.
According to the coordinates of the key points and the face action coding system (FACS), the face region is divided into 15 regions of interest (ROI).
In the feature extraction stage, the optical flow direction histogram feature between adjacent frames in ROI is extracted to detect the peak frame of microexpression sequence.
Finally, the average optical flow direction histogram feature of the image sequence from the initial frame to the peak frame is extracted.
In the classification stage, firstly, the head pose parameters under horizontal degrees of freedom are estimated to eliminate the influence of head pose motion, and a forest multiview conditional probability model based on deep multiview network is established.
Conditional probability and neural connection function are introduced into the node splitting learning of random tree to improve the learning ability and distinguishing ability of the model on the limited training set.
Finally, multiview-weighted voting is used to determine the categories of facial microexpressions.
Experiments on CASME II microexpression dataset show that the proposed method can effectively describe the changes of microexpressions and improve the recognition accuracy compared with other new methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Huanmin. 2020. Enhanced Forest Microexpression Recognition Based on Optical Flow Direction Histogram and Deep Multiview Network. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1196111
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Huanmin. Enhanced Forest Microexpression Recognition Based on Optical Flow Direction Histogram and Deep Multiview Network. Mathematical Problems in Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1196111
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Huanmin. Enhanced Forest Microexpression Recognition Based on Optical Flow Direction Histogram and Deep Multiview Network. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1196111
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1196111
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر