Recognize Facial Expression Using Active Appearance Model And Neural Network
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.
face detection facial expression classification active appearance model neural network
Taihao Li Jianshe Zhou Naren Tuya Cuifen Du Zhiqiang Chen Shupeng Liu
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
国际会议
南京
英文
182-185
2017-10-12(万方平台首次上网日期,不代表论文的发表时间)