C + + version of the LLC code __c++

Image Sparse Coding Summary: LLC and SCSPM , the article gives a very detailed explanation of sparse coding.

The author of "Locality-constrained Linear coding for Image Classification" provides MATLAB code implementation, see HTTP://WWW.IFP.ILLINOIS.EDU/~JYANG29 /llc.htm.

The following is based on the author's code, implemented by OPENCV, the C + + version of the LLC:

Matlab code:www.ifp.illinois.edu/~jyang29/llc.htm

<span style= "FONT-SIZE:12PX;"  
      > Cv::mat bowmodel::findknn (Cv::mat &codebook, Cv::mat &input, int k) {int nbase = codebook.rows;  
      int nquery = input.rows;  
      Mat II = INPUT.MUL (input);  
        
      Mat cc = Codebook.mul (codebook);  
      Mat SII (NQUERY,1,CV_32FC1);  
      Sii.setto (0);  
      Mat SCC (NBASE,1,CV_32FC1);  
      Scc.setto (0);  for (int i = 0; i<ii.rows; i++) {for (int j = 0; j<ii.cols; j + +) {sii.at<float> (i,0)  
        + + ii.at<float> (i,j); (int i = 0; i<cc.rows; i++) {for (int j = 0; j<cc.cols; + +) {SCC.  
        At<float> (i,0) + = cc.at<float> (i,j);  
      } Mat D (NQUERY,NBASE,CV_32FC1); for (int i = 0; i<nquery; i++) {for (int j = 0; j<nbase; j + +) {d.at<float> (i,j) = Si  
        I.at<float> (i,0);  
  } Mat CT;    Transpose (codebook, CT);  
        
      Mat D1 = 2*input*ct;  
      Mat Scct;  
      Transpose (SCC, SCCT);  
      Mat D2 (Nquery, Nbase, CV_32FC1); for (int i = 0; i<nquery; i++) {for (int j = 0; j<nbase; j + +) {d2.at<float> (i,j) = s  
        Cct.at<float> (0,J);  
      } D = D-d1 + D2;  
      Mat SD;  
      Sortidx (D, SD, cv_sort_every_row+cv_sort_ascending);  
      Mat IDX (NQUERY,K,CV_8UC1); for (int i = 0; i<nquery; i++) {for (int j = 0; j<k; j + +) {idx.at<uchar> (i,j) = SD.R  
        ow (i). Col (j) .at<uchar> (0,0);  
      } ii.release ();  
      Cc.release ();  
      Sii.release ();  
      Scc.release ();  
      D.release ();  
      Ct.release ();  
      D1.release ();  
      Scct.release ();  
      D2.release ();  
      Sd.release ();  
    return IDX; } Cv::mat Bowmodel::llccode (Cv::mat &codebook, Cv::mat &amP;input, Cv::mat IDX, int k) {int nquery = input.rows;  
        int nbase = codebook.rows;  
      
        int dim = Codebook.cols;  
        Mat II = Mat::eye (k, K, CV_32FC1);  
        Mat Coeff (NQUERY,NBASE,CV_32FC1);  
        Coeff.setto (0);  
        Mat Z;  
        Mat Z1 (K,DIM,CV_32FC1);  
        Mat Z2 (K,DIM,CV_32FC1);  
        Mat C;  
        Mat un (K,1,CV_32FC1);  
        Un.setto (1);  
        Mat temp;  
        Mat Temp2;  
        Mat W;  
      
        Mat wt; for (int n = 0; n<nquery; n++) {for (int i = 0; i<k; i++) {for (int j = 0; J<di M  
                    J + +) {z1.at<float> (i,j) = Codebook.at<float> (idx.at<uchar> (N,i), j);  
                Z2.at<float> (i,j) = input.at<float> (N,J);  
            }} z = z1-z2;  
            Transpose (z, temp);  
            C = z*temp;  
    c = C + ii* (1e-4) *trace (c) [0];        Invert (C,TEMP2);  
            W = Temp2*un;  
            float sum_w=0;  
            for (int i = 0; i<k; i++) {sum_w + = w.at<float> (i,0);  
            } w = w/sum_w;  
            Transpose (w, WT); for (int i = 0; i<k; i++) {coeff.at<float> (n,idx.at<uchar> (n,i)) = wt.at<float> (0,  
            i);  
        } ii.release ();  
        Z.release ();  
        Z1.release ();  
        Z2.release ();  
        C.release ();  
        Un.release ();  
        Temp.release ();  
        Temp2.release ();  
        W.release ();  
      
        Wt.release ();  
    return Coeff; } </span>