[Retracted] Sparsity Based Locality-Sensitive Discriminative Dictionary Learning for Video Semantic Analysis

Algorithm 1

Sparsity Locality–Sensitive Discriminative Dictionary Learning Algorithm.

Input: Training samples A, Initial dictionary D and parameters

Output: The learned dictionary D

(a) Initialize the coding coefficient matrix X and i

(b) Optimize the solution by updating the sparse coding matrix X and the dictionary D. Update X by fixing D and updating each

according to equation (22) on class bases by solving for and then do

(c) If , update X, which means else do and go to (b)

(d) Initialize and respectively with and

(e) Solve equation (24) for the solution of

(f) Go to (g) if else do and return to (e)

(g) Compute from equation (25)

(h) Fix X and update D using equation (22)

(i) If , execute and go to (j) otherwise execute , and return to (e)

(j) Compute the reconstruction error. If the error value is less than the current minimum values, update the dictionary

on the minimum error which is

(k) Iteratively return to step (b) until convergence or the reconstruction error is less than the threshold error,

update D and the algorithm ends or go to (a)