The painful face – Pain expression recognition using active appearance models-Reference-Cited by-同舟云学术

The painful face – Pain expression recognition using active appearance models

Published:2009-11 Issue:12 Volume:27 Page:1788-1796
ISSN:0262-8856
Container-title:Image and Vision Computing
language:en
Short-container-title:Image and Vision Computing

Author:

Ashraf Ahmed Bilal,Lucey Simon,Cohn Jeffrey F.,Chen Tsuhan,Ambadar Zara,Prkachin Kenneth M.,Solomon Patricia E.

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing

Reference35 articles.

1. M. Bartlett, G. Littlewort, C. Lainscesk, I. Fasel, J. Movellan, Machine learning methods for fully automatic recognition of facial expressions and facial actions, in: IEEE International Conference on Systems, Man and Cybernetics, October 2004, pp. 592–597.

2. G. Littlewort, M. Bartlett, K. Lee, Faces of pain – automated measurement of spontaneous facial expressions of genuine and posed pain, in: Proceedings of the 9th International Conference on Multimodal Interfaces (ICMI), 2007, pp. 15–21.

3. A.B. Ashraf, S. Lucey, J. Cohn., T. Chen, Z. Ambadar, K. Prkachin, P. Solomon, The painful face – pain expression recognition using active appearance models, in: Proceedings of the 9th International Conference on Multimodal Interfaces (ICMI), 2007, pp. 9–14.

4. Recognizing facial expression: machine learning and application to spontaneous behavior;Bartlett;IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2005

5. M.S. Bartlett, G. Littlewort, M. Frank, C. Lainscsek, I. Fasel, J. Movellan, Fully automatic facial action recognition in spontaneous behavior, in: Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition, 2006, pp. 223–228.

Cited by 216 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Analyzing deep textual facial patterns for human pain sentiment recognition system in smart healthcare framework;Intelligent Decision Technologies;2024-08-15

2. Machine learning model of facial expression outperforms models using analgesia nociception index and vital signs to predict postoperative pain intensity: a pilot study;Korean Journal of Anesthesiology;2024-04-01

3. Application of a human-centered design for embedded machine learning model to develop data labeling software with nurses: Human-to-Artificial Intelligence (H2AI);International Journal of Medical Informatics;2024-03

4. Postoperative accurate pain assessment of children and artificial intelligence: A medical hypothesis and planned study;World Journal of Clinical Cases;2024-02-06

5. Artificial intelligence model predicting postoperative pain using facial expressions: a pilot study;Journal of Clinical Monitoring and Computing;2023-12-27