TY - JOUR
T1 - Survey on facial expression recognition of pain
AU - Peng, Jinye
AU - Yang, Ruijing
AU - Feng, Xiaoyi
AU - Wang, Wenxing
AU - Peng, Xianlin
N1 - Publisher Copyright:
© 2016, Nanjing University of Aeronautics an Astronautics. All right reserved.
PY - 2016/1/1
Y1 - 2016/1/1
N2 - In recent years, research on automatic pain recognition is of increased attetion, due to its wide application in clinics, especially for the treatment and nursing of patients who cannot express their pain vocally. Since the face is the vital cue for evaluating pain and the great progress has been made in facial expression recognition with computer vison technique, it is an effective way to recognize pain automatically utilizing facial information. Here, four existing databases used for pain recognition are firstly introduced, namely, the STOIC database, the Infant COPE database, the UNBC-McMaster Shoulder Pain Expression Archive database, and the BioVid Heat Pain databse. Then, the proposed methods in the last decade can be divided into four categories depending on the use of either static images, video sequences, person specific strategy or multimodal methods. Finally, the current state of the art in pain detection research, open issues and future directions are highlighted.
AB - In recent years, research on automatic pain recognition is of increased attetion, due to its wide application in clinics, especially for the treatment and nursing of patients who cannot express their pain vocally. Since the face is the vital cue for evaluating pain and the great progress has been made in facial expression recognition with computer vison technique, it is an effective way to recognize pain automatically utilizing facial information. Here, four existing databases used for pain recognition are firstly introduced, namely, the STOIC database, the Infant COPE database, the UNBC-McMaster Shoulder Pain Expression Archive database, and the BioVid Heat Pain databse. Then, the proposed methods in the last decade can be divided into four categories depending on the use of either static images, video sequences, person specific strategy or multimodal methods. Finally, the current state of the art in pain detection research, open issues and future directions are highlighted.
KW - Databases
KW - Expression recognition
KW - Face recognition
KW - Pain expression
KW - Pain recognition
UR - http://www.scopus.com/inward/record.url?scp=84960945973&partnerID=8YFLogxK
U2 - 10.16337/j.1004-9037.2016.01.004
DO - 10.16337/j.1004-9037.2016.01.004
M3 - 文章
AN - SCOPUS:84960945973
SN - 1004-9037
VL - 31
SP - 43
EP - 55
JO - Shuju Caiji Yu Chuli/Journal of Data Acquisition and Processing
JF - Shuju Caiji Yu Chuli/Journal of Data Acquisition and Processing
IS - 1
ER -