Recognize Facial Expression Using Active Appearance Model And Neural Network

摘要：

　　We present an image processing pipeline to recognize facial expression by first using a face template to identify a set of feature points on faces and then applying a neural network to classify facial expression to one of six categories,namely,happy,surprise,sad,distracted,focused,and plain.We tested the pipeline on standard database and found that it can achieve satisfactory performance.We next applied the pipeline on newly acquired video to classify facial expression in real time.The testing showed that the pipeline can obtain good results over a range of imaging conditions.

关键词： face detection facial expression classification active appearance model neural network

作者: Taihao Li Jianshe Zhou Naren Tuya Cuifen Du Zhiqiang Chen Shupeng Liu

作者单位: Beijing Advanced Innovation Center for Imaging Technology Capital Normal University Beijing,China Key Laboratory of Specialty Fiber Optics and Optical Access Networks,School of Communication and Inf

会议类型: 国际会议

会议名称: 第九届网络分布式计算与知识发现国际会议( 2017 International Conference on Cyber-enabled distributed computing and knowledge discovery)

会议地点: 南京

会议语种:英文

页码: 182-185

在线出版日期: 2017-10-12（万方平台首次上网日期，不代表论文的发表时间）