21.3.6.1.6 Face Expression Recognition for Pain

Chapter Contents (Back)
Faces, Expression. Facial Expressions. Pain.

Hammal, Z.[Zakia], Kunz, M.[Miriam],
Pain monitoring: A dynamic and context-sensitive system,
PR(45), No. 4, April 2012, pp. 1265-1280.
Elsevier DOI 1112
Pain expression; Spontaneous facial expressions; Context based recognition; Transferable Belief Model; Classification BibRef

Hammal, Z.[Zakia],
Efficient Detection of Consecutive Facial Expression Apices Using Biologically Based Log-Normal Filters,
ISVC11(I: 586-595).
Springer DOI 1109
BibRef

Hammal, Z.[Zakia], Arguin, M.[Martin], Gosselin, F.[Frédéric],
Comparing a Transferable Belief Model Capable of Recognizing Facial Expressions with the Latest Human Data,
ISVC07(I: 509-520).
Springer DOI 0711
BibRef

Hammal, Z., Couvreur, L., Caplier, A., Rombaut, M.,
Facial Expression Recognition Based on the Belief Theory: Comparison with Different Classifiers,
CIAP05(743-752).
Springer DOI 0509
BibRef

Littlewort, G.C.[Gwen C.], Bartlett, M.S.[Marian Stewart], Lee, K.[Kang],
Automatic coding of facial expressions displayed during posed and genuine pain,
IVC(27), No. 12, November 2009, pp. 1797-1803.
Elsevier DOI 0910
Machine learning; Computer vision; Malingering; Facial expression; Spontaneous behavior; Automated FACS BibRef

Ashraf, A.B.[Ahmed Bilal], Lucey, S.[Simon], Cohn, J.F.[Jeffrey F.], Chen, T.H.[Tsu-Han], Ambadar, Z.[Zara], Prkachin, K.M.[Kenneth M.], Solomon, P.E.[Patricia E.],
The painful face: Pain expression recognition using active appearance models,
IVC(27), No. 12, November 2009, pp. 1788-1796.
Elsevier DOI 0910
Active appearance models; Support vector machines; Pain; Facial expression; Automatic facial image analysis; FACS BibRef

Lucey, P.[Patrick], Cohn, J.F.[Jeffrey F.], Prkachin, K.M.[Kenneth M.], Solomon, P.E.[Patricia E.], Chew, S.[Sien], Matthews, I.[Iain],
Painful monitoring: Automatic pain monitoring using the UNBC-McMaster shoulder pain expression archive database,
IVC(30), No. 3, March 2012, pp. 197-205.
Elsevier DOI 1204
Pain; Active Appearance Models (AAMs); Action Units (AUs); FACS BibRef

Lucey, P.[Patrick], Cohn, J.F.[Jeffrey F.], Prkachin, K.M.[Kenneth M.], Solomon, P.E.[Patricia E.], Matthews, I.[Iain],
Painful data: The UNBC-McMaster shoulder pain expression archive database,
FG11(57-64).
IEEE DOI 1103
Dataset, Facial Expression. BibRef

Lucey, P.[Patrick], Cohn, J.F.[Jeffrey F.], Matthews, I., Lucey, S.[Simon], Sridharan, S.[Sridha], Howlett, J., Prkachin, K.M.[Kenneth M.],
Automatically Detecting Pain in Video Through Facial Action Units,
SMC-B(41), No. 3, June 2011, pp. 664-674.
IEEE DOI 1106
BibRef

Lucey, P.[Patrick], Cohn, J.F.[Jeffrey F.], Lucey, S.[Simon], Sridharan, S.[Sridha], Prkachin, K.M.[Kenneth M.],
Automatically detecting action units from faces of pain: Comparing shape and appearance features,
CVPR4HB09(12-18).
IEEE DOI 0906
BibRef

Sikka, K.[Karan], Dhall, A.[Abhinav], Bartlett, M.S.[Marian Stewart],
Classification and weakly supervised pain localization using multiple segment representation,
IVC(32), No. 10, 2014, pp. 659-670.
Elsevier DOI 1410
BibRef
Earlier:
Weakly supervised pain localization using multiple instance learning,
FG13(1-8)
IEEE DOI 1309
Emotion classification. face recognition BibRef

Sikka, K.[Karan], Wu, T.F.[Ting-Fan], Susskind, J.[Josh], Bartlett, M.S.[Marian Stewart],
Exploring Bag of Words Architectures in the Facial Expression Domain,
Face12(II: 250-259).
Springer DOI 1210
BibRef

Deriso, D.M.[David M.], Susskind, J.[Josh], Tanaka, J.[Jim], Winkielman, P.[Piotr], Herrington, J.[John], Schultz, R.[Robert], Bartlett, M.S.[Marian Stewart],
Exploring the Facial Expression Perception-Production Link Using Real-Time Automated Facial Expression Recognition,
Face12(II: 270-279).
Springer DOI 1210
BibRef

Rathee, N.[Neeru], Ganotra, D.[Dinesh],
A novel approach for pain intensity detection based on facial feature deformations,
JVCIR(33), No. 1, 2015, pp. 247-254.
Elsevier DOI 1512
Thin Plate Spline BibRef

Rathee, N.[Neeru], Ganotra, D.[Dinesh],
Multiview Distance Metric Learning on facial feature descriptors for automatic pain intensity detection,
CVIU(147), No. 1, 2016, pp. 77-86.
Elsevier DOI 1605
Multiview Distance Metric Learning BibRef

Kaltwang, S.[Sebastian], Todorovic, S., Pantic, M.[Maja],
Doubly Sparse Relevance Vector Machine for Continuous Facial Behavior Estimation,
PAMI(38), No. 9, September 2016, pp. 1748-1761.
IEEE DOI 1609
emotion recognition BibRef

Kaltwang, S.[Sebastian], Rudovic, O.[Ognjen], Pantic, M.[Maja],
Continuous Pain Intensity Estimation from Facial Expressions,
ISVC12(II: 368-377).
Springer DOI 1209
BibRef

Martinez, D.L., Rudovic, O.[Ognjen], Picard, R.W.[Rosalind W.],
Personalized Automatic Estimation of Self-Reported Pain Intensity from Facial Expressions,
DeepAffective17(2318-2327)
IEEE DOI 1709
Estimation, Face, Hidden Markov models, Image sequences, Pain, Recurrent neural networks, Reliability BibRef

Florea, C.[Corneliu], Florea, L.[Laura], Butnaru, R.[Raluca], Bandrabur, A.[Alessandra], Vertan, C.[Constantin],
Pain intensity estimation by a self-taught selection of histograms of topographical features,
IVC(56), No. 1, 2016, pp. 13-27.
Elsevier DOI 1609
Histograms of Topographical (HoT) features BibRef

Aung, M.S.H., Kaltwang, S., Romera-Paredes, B., Martinez, B., Singh, A., Cella, M., Valstar, M., Meng, H., Kemp, A., Shafizadeh, M., Elkins, A.C., Kanakam, N., de Rothschild, A., Tyler, N., Watson, P.J., Williams, A.C.d.C., Pantic, M., Bianchi-Berthouze, N.,
The Automatic Detection of Chronic Pain-Related Expression: Requirements, Challenges and the Multimodal EmoPain Dataset,
AffCom(7), No. 4, October 2016, pp. 435-451.
IEEE DOI 1612
Context modeling BibRef

Lo Presti, L.[Liliana], La Cascia, M.[Marco],
Boosting Hankel matrices for face emotion recognition and pain detection,
CVIU(156), No. 1, 2017, pp. 19-33.
Elsevier DOI 1702
BibRef
Earlier:
Using Hankel matrices for dynamics-based facial emotion recognition and pain detection,
AMFG15(26-33)
IEEE DOI 1510
BibRef
And:
Ensemble of Hankel Matrices for Face Emotion Recognition,
CIAP15(II:586-597).
Springer DOI 1511
Emotion recognition BibRef


Lu, Y., Mahmoud, M., Robinson, P.,
Estimating Sheep Pain Level Using Facial Action Unit Detection,
FG17(394-399)
IEEE DOI 1707
Animals, Ear, Face, Feature extraction, Gold, Pain, Taxonomy BibRef

Egede, J., Valstar, M., Martinez, B.,
Fusing Deep Learned and Hand-Crafted Features of Appearance, Shape, and Dynamics for Automatic Pain Estimation,
FG17(689-696)
IEEE DOI 1707
Estimation, Face, Feature extraction, Machine learning, Pain, Physiology, Shape BibRef

Zamzmi, G.[Ghada], Pai, C.Y.[Chih-Yun], Goldgof, D.[Dmitry], Kasturi, R.[Rangachar], Sun, Y.[Yu], Ashmeade, T.[Terri],
Automated Pain Assessment in Neonates,
SCIA17(II: 350-361).
Springer DOI 1706
BibRef

Zamzmi, G., Pai, C.Y., Goldgof, D., Kasturi, R., Ashmeade, T., Sun, Y.,
An approach for automated multimodal analysis of infants' pain,
ICPR16(4148-4153)
IEEE DOI 1705
Biomedical monitoring, Feature extraction, Optical imaging, Pain, Pediatrics, Physiology, Strain BibRef

Ruiz, A.[Adria], Rudovic, O.[Ognjen], Binefa, X.[Xavier], Pantic, M.[Maja],
Multi-Instance Dynamic Ordinal Random Fields for Weakly-Supervised Pain Intensity Estimation,
ACCV16(II: 171-186).
Springer DOI 1704
BibRef

Yang, R., Tong, S., Bordallo, M., Boutellaa, E., Peng, J., Feng, X., Hadid, A.,
On pain assessment from facial videos using spatio-temporal local descriptors,
IPTA16(1-6)
IEEE DOI 1703
emotion recognition BibRef

Zhou, J., Hong, X., Su, F., Zhao, G.,
Recurrent Convolutional Neural Network Regression for Continuous Pain Intensity Estimation in Video,
Affect16(1535-1543)
IEEE DOI 1612
BibRef

Saeijs, R.W.J.J., Tjon a Ten, W.E., de With, P.H.N.,
Dense-Hog-based 3D face tracking for infant pain monitoring,
ICIP16(1719-1723)
IEEE DOI 1610
Cameras BibRef

Li, C., Zinger, S., Tjon a Ten, W.E., de With, P.H.N.,
Video-based discomfort detection for infants using a Constrained Local Model,
WSSIP16(1-4)
IEEE DOI 1608
face recognition BibRef

Pence, T.B.[Toni B.], Dukes, L.C.[Lauren C.], Hodges, L.F.[Larry F.],
Animation Validation of Obese Virtual Pediatric Patients Using a FLACC Pain Scale,
VAMR16(552-564).
Springer DOI 1608
BibRef

Lundtoft, D.H.[Dennis H.], Nasrollahi, K.[Kamal], Moeslund, T.B.[Thomas B.], Escalera, S.[Sergio],
Spatiotemporal Facial Super-Pixels for Pain Detection,
AMDO16(34-43).
Springer DOI 1608
BibRef

Liu, Z.J.[Zhe-Jun], Wangluo, S.[Sijia], Dong, H.[Hua],
Advances and Tendencies: A Review of Recent Studies on Virtual Reality for Pain Management,
VAMR16(512-520).
Springer DOI 1608
BibRef

Irani, R.[Ramin], Nasrollahi, K.[Kamal], Moeslund, T.B.[Thomas B.],
Pain recognition using spatiotemporal oriented energy of facial muscles,
ChaLearn15(80-87)
IEEE DOI 1510
Energy measurement BibRef

Irani, R.[Ramin], Nasrollahi, K.[Kamal], Simon, M.O.[Marc O.], Corneanu, C.A.[Ciprian A.], Escalera, S.[Sergio], Bahnsen, C.[Chris], Lundtoft, D.H.[Dennis H.], Moeslund, T.B.[Thomas B.], Pedersen, T.L.[Tanja L.], Klitgaard, M.L.[Maria-Louise], Petrini, L.[Laura],
Spatiotemporal analysis of RGB-D-T facial images for multimodal pain level recognition,
ChaLearn15(88-95)
IEEE DOI 1510
Calibration BibRef

Pedersen, H.[Henrik],
Learning Appearance Features for Pain Detection Using the UNBC-McMaster Shoulder Pain Expression Archive Database,
CVS15(128-136).
Springer DOI 1507
BibRef

Zhang, X.[Xing], Yin, L.J.[Li-Jun], Cohn, J.F.,
Three dimensional binary edge feature representation for pain expression analysis,
FG15(1-7)
IEEE DOI 1508
emotion recognition BibRef

Florea, C.[Corneliu], Florea, L.[Laura], Vertan, C.[Constantin],
Learning Pain from Emotion: Transferred HoT Data Representation for Pain Intensity Estimation,
ACVR14(778-790).
Springer DOI 1504
BibRef

Werner, P.[Philipp], Al-Hamadi, A.[Ayoub], Walter, S.[Steffen], Gruss, S.[Sascha], Traue, H.C.[Harald C.],
Automatic heart rate estimation from painful faces,
ICIP14(1947-1951)
IEEE DOI 1502
Electrocardiography BibRef

Werner, P.[Philipp], Al-Hamadi, A.[Ayoub], Niese, R.[Robert], Walter, S.[Steffen], Gruss, S.[Sascha], Traue, H.C.[Harald C.],
Automatic Pain Recognition from Video and Biomedical Signals,
ICPR14(4582-4587)
IEEE DOI 1412
Data integration BibRef

Zafar, Z.[Zuhair], Khan, N.A.[Nadeem Ahmad],
Pain Intensity Evaluation through Facial Action Units,
ICPR14(4696-4701)
IEEE DOI 1412
Databases BibRef

Zaker, N., Mahoor, M.H., Mattson, W.I., Messinger, D.S., Cohn, J.F.,
A comparison of alternative classifiers for detecting occurrence and intensity in spontaneous facial expression of infants with their mothers,
FG13(1-6)
IEEE DOI 1309
eigenvalues and eigenfunctions BibRef

Reale, M., Zhang, X.[Xing], Yin, L.J.[Li-Jun],
Nebula feature: A space-time feature for posed and spontaneous 4D facial behavior analysis,
FG13(1-8)
IEEE DOI 1309
curvature measurement BibRef

Werner, P.[Philipp], Al-Hamadi, A.[Ayoub], Niese, R.[Robert],
Pain recognition and intensity rating based on Comparative Learning,
ICIP12(2313-2316).
IEEE DOI 1302
BibRef

Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Three-Dimensional Face Expression Recognition and Analysis .


Last update:Sep 18, 2017 at 11:34:11