The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Evaluation of Face Resolution for Expression Analysis
Abstract
Most automatic facial expression analysis (AFEA) systems attempt to recognize facial expressions from data collected in a highly controlled environment with very high resolution frontal faces ( face regions greater than 200 x 200 pixels). However, in real environments, the face image is often in lower resolution and with head motion. It is unclear that the performance of AFEA systems for low resolution face images. The general approach to AFEA consists of 3 steps: face acquisition, facial feature extraction, and facial expression recognition. This paper explores the effects of different image resolutions for each step of facial expression analysis. The different approaches are compared for face detection, face data extraction and expression recognition. A total of five different resolutions of the head region are studied (288x384, 144x192, 72x96, 36x48, and 18Xx24) based on a widely used public database. The lower resolution images are down-sampled from the originals.
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Cites
Neural network-based face detection
Rowley, H. A., Baluja, S., & Kanade, T. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.655647 · Cited by 3,554
Recognizing action units for facial expression analysis
Tian, Y.-I., Kanade, T., & Cohn, J. F. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.908962 · Cited by 1,745
Self-citationExpert system for automatic analysis of facial expressions
Pantic, M., & Rothkrantz, L. J. M. (2000) · Image and Vision Computing · doi:10.1016/s0262-8856(00)00034-2 · Cited by 415
Cited by
Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions
Zhao, G., & Pietikainen, M. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1110 · Cited by 2,846
Facial expression recognition based on Local Binary Patterns: A comprehensive study
Shan, C., Gong, S., & McOwan, P. W. (2009) · Image and Vision Computing · doi:10.1016/j.imavis.2008.08.005 · Cited by 2,300
Local Directional Number Pattern for Face Analysis: Face and Expression Recognition
Ramirez Rivera, A., Rojas Castillo, J., & Oksam Chae, O. (2013) · IEEE Transactions on Image Processing · doi:10.1109/tip.2012.2235848 · Cited by 512
Robust facial expression recognition using local binary patterns
Shan, C., Gong, S., & McOwan, P. W. (2005) · IEEE International Conference on Image Processing 2005 · doi:10.1109/icip.2005.1530069 · Cited by 414
Facial expression recognition using radial encoding of local Gabor features and classifier synthesis
Gu, W., Xiang, C., Venkatesh, Y. V., Huang, D., & Lin, H. (2012) · Pattern Recognition · doi:10.1016/j.patcog.2011.05.006 · Cited by 311
Metadata
- Authors
- Tian, Y.-L.
- Venue
- 2004 Conference on Computer Vision and Pattern Recognition Workshop
- Publisher
- IEEE
- Published
- 2005-04-05
- Pages
- 82-82
- OpenAlex
- W2143245774
- Cited by
- 204
- References
- 3
- Type
- conference abstract
- Language
- en
- Open access
- closed
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