# SRC-RLS **Repository Path**: tjh199504/SRC-RLS ## Basic Information - **Project Name**: SRC-RLS - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2019-06-27 - **Last Updated**: 2020-12-19 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README Sparse Representation and Least Squares-Based Classification in Face Recognition This is the code to reproduce the results of the paper "Sparse Representation and Least Squares-Based Classification in Face Recognition" published in EUSIPCO 2014 --------------------------------------------------------------------------- Usage: 1) add to the path the entire "SRC-RLS" folder 2) run "runExperiments.m" --------------------------------------------------------------------------- More info: By default the experiments reproduce the SRC+RLS results on YaleB dataset. Data of YaleB and AR are provided to reproduce the results of the paper If you want to choose another dataset change the variable "dataset" If you want to choose another FR classifier change the variable "method" --------------------------------------------------------------------------- Adding your own Face Recognition classifier: If you want to add your classifier, modify: runFR.m: add another if statement for your classifier, and provide the code of your classifier. Output should be the label of the identity estimated by the classifier pasSelection.m: add another if for your classifier and specify the necessary parameters. --------------------------------------------------------------------------- BSD Licence.