% LOTAA - Learning object templates by active basis model and adaboost
% 
% LOTAA main functions.
%   StartFromHere			 - The entry point of this project. You can customize the procecure by modifying this function.
%   SetTemplateParameters	 - Specify parameters of templates for each object category.
%   LearnActiveBasisTemplate - Learn an active basis template for a given category. 
%   LearnAdaboostTemplate    - Learn an adaboost template for a given category. 
%   GenerateManual           - Generate html manual for the matlab code.
%   GenerateFigureCaption    - Generate html and latex documentation for the experimental results. 
%
% Sub directories containing code
%   common/         - The common utilities used by both learning methods.
%   adaboost/       - The adaboost learner.
%   activebasis/    - The shared sketch algorithm for active basis model.
%   m2html/         - An imported matlab documentation project.
%
% Other sub directories:
%   image/          - The image data organized by directories (e.g. cat). 
%   result/         - Learned templates by active basis model and adaboost. The templates are saved in .mat files
%                       in directories named by object categories.
%   document/       - Matlab code manual in html. Figures and captions in html and latex. 
%
% How to conduct experiments:
%   - To perform experiments on the current image categories,  run "StartFromHere".
%   - To modify or append experimental parameters, open "SetTemplateParameters".
%   For each category, you can specify or modify 1) the template size,
%   2) number of Gabor elements in the active basis / adaboost template,
%   and 3) scale of Gabor elements.
%   - To append new data, add new directories of images into "image/".
%   
%   Copyright (C) 2009 Zhangzhang Si (zzsi@stat.ucla.edu), Hui Tang, Ying Nian Wu in UCLA Stat. Dept.
%   $Revision: 0.0 $Date: 2009/10/27 14:30:00 $
