machine learning homework: Age Estimation
#Code Description#
the function interface (ageestimation.m):
[ pred_age ] = ageestimation( image )
required files: /functions, cAAA.mat, meanscl.mat, meantrans.mat, svr_poly_model.mat
other code:
1. featureExtraction.m & append_features.m : extract feature and modify the data structure
2. main.m: train support vector regression model
3. test_image.m: test the function interface
4. checknumericargs.m, ticstatus.m, tocstatus.m (just for convenience) : Used to display the progress of a long process
#Main Reference#
[1] Xin Geng, Zhi-Hua Zhou, and Kate Smith-Miles. Automatic age estimation based on facial aging patterns. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 29(12):2234–2240,2007.
[2] Georgios Tzimiropoulos and Maja Pantic. Optimization problems for fast aam fitting in-thewild. In Computer Vision (ICCV), 2013 IEEE International Conference on, pages 593–600.IEEE, 2013. http://www.mathworks.com/matlabcentral/fileexchange/44651-active-appearance-models--aams-
[3] Khoa Luu, Karl Ricanek, Tien D Bui, and Ching Y Suen. Age estimation using active appearance models and support vector machine regression. In Biometrics: Theory, Applications, and Systems, 2009. BTAS’09. IEEE 3rd International Conference on, pages 1–5.IEEE, 2009.
Ricanek, Karl, and Tamirat Tesafaye. "Morph: A longitudinal image database of normal adult age-progression." Automatic Face and Gesture Recognition, 2006. FGR 2006. 7th International Conference on. IEEE, 2006.
Contact: huajh7@gmail.com
2014/6/19