Dirichlet-tree distribution enhanced random forests for facial feature detection

2014 IEEE International Conference on Image Processing, ICIP 2014

Volumn , Issue , 2014, Pages 234-238

  Liu, Yuanyuan ^a,b,c   Chen, Jingying ^a,b   Shan, Cunjie ^a  

^a CENTRAL CHINA NORMAL UNIVERSITY   (China)

^b Collaborative and Innovative Center for Educational Technology ^*  (China)

^c Wenhua College ^*  (China)

Author keywords

Composite weighted voting; D RF; Facial feature detection; FDM; Head pose estimation

Indexed keywords

DECISION TREES; FEATURE EXTRACTION; FORESTRY; FREQUENCY DIVISION MULTIPLEXING; IMAGE PROCESSING; IMAGE RECOGNITION; IMAGE RESOLUTION; PROBABILITY; REGRESSION ANALYSIS;

FACIAL DEFORMATIONS; FACIAL EXPRESSIONS; FACIAL FEATURE DETECTION; HEAD POSE ESTIMATION; POSITIVE/NEGATIVE; PROBABILITY MODELS; UNCONSTRAINED ENVIRONMENTS; WEIGHTED VOTING;

FACE RECOGNITION;

EID: 84947869847     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2014.7025046     Document Type: Conference Paper

References (15)

1. T. F. Cootes, M. C. Ionita, and S. P., "Robust and accurate shape model fitting using random forest regression voting," in Proc. European Conf. Computer Vision, 2012.
2. H. Yang and I. Patras, "Face parts localization using structured-output regression forests," in Proc. Assian Conf. Computer Vision. Springer, 2012.
3. M. Dantone, J. Gall, G. Fanelli, and L. Van Gool, "Real time facial feature detection using conditional regression forests," in CVPR, 2012.
4. T. Cootes, G. Edwards, and C. Taylor, "Active appearance models," in TPAMI, 2001, vol. 23, pp. 681-685.
5. H. Yang and I. Patras, "Privileged information-based conditional regression forests for facial feature detection," in Proc. IEEE Int1 Conf. on Automatic Face and Gesture Recognition, 2013.
6. Y. Liu, J. Chen, Y. Liu, Y. Gong, and N. Luo, "Dirichlettree distribution enhanced random forests for head pose estimation," in ICPRAM, 2014.
7. R. E. Schapire and Y. Singer, "Improved boosting algorithms using confidence-rated predictions," in Maching Learning, 1999, vol. 37(3), pp. 297-336.
8. Y. Li, X. Wang, and X. Ding, "Person-independent head pose estimation based on random forest regression," in Image Processing (ICIP), 2010 17th IEEE International Conference on. IEEE, 2010, pp. 1521-1524.
9. T. Minka, "The dirichlet-tree distribution," in http://research. microsoft. com/minka/papers/dirichlet/min kadirtree. pdf, 1999.
10. X. Yan and C. Han, "Mutiple target tracking by probability hypothesis density based on dirichlet distribution," in Journal of XiAn JiaoTong University, 2011, vol. 42, p. 2.
11. M. E. Jones and P. Viola, "Fast multi-view face detection," in Tech. Rep. TR2003-096. Mitsubishi Electric Research Laboratories, 2003.
12. L. Breiman, "Random forests," in Machine Learning, 2001, vol. 45(1), pp. 5-32.
13. C. E. Stauffer and W. Grimson et al, "Adaptive background mixture models for real-time tracking[c]," in Computer Vision and Pattern Recognition, 1999.
14. N. Gourier, D. Hall, and J. Crowley, "Estimating face orientation from robust detection of salient facial features," in Pointing. ICPR international Workshop on Visual Observation of Deictic Gestures, 2004, pp. 183-191.
15. G. Huang, M. Ramesh, T. Berg, and E., "Learned-miller. labeled faces in the wild: A database for studying face recognition in unconstrained environments," in Technical report, University of Massachusetts, Technical report, University of Massachusetts, 2007.