cv::SVM response one class for every sample - opencv

Question

I am new in Match faces , I am trying to learn how to use SVM with HOG descriptors.
I wrote a simple face recognizer with SVM, but when i activate it , code always returns 1
float *getHOG(const cv::Mat &image, int* count)//Compute HOG
{
cv::HOGDescriptor hog;
std::vector<float> res;
cv::Mat img2;
cv::resize(image, img2, cv::Size(64, 128));
hog.compute(img2, res, cv::Size(8, 8), cv::Size(0, 0));
*count = res.size();
float* result = new float[*count];
for(int i = 0; i < res.size(); i++)
{
result[i] = res[i];
}
return result;
}
const int dataSetLength = 10;
float **getTraininigData(int* setlen, int* veclen)//Load some samples of data
{
char *names[dataSetLength] = {
"../faces/s1/1.pgm",
"../faces/s1/2.pgm",
"../faces/s1/3.pgm",
"../faces/s1/4.pgm",
"../faces/s1/5.pgm",
"../faces/cars/1.jpg",
"../faces/cars/2.jpg",
"../faces/cars/3.jpg",
"../faces/cars/4.jpg",
"../faces/cars/5.jpg",
};
float **res = new float* [dataSetLength];
for(int i = 0; i < dataSetLength; i++)
{
std::cout<<names[i]<<"\n";
cv::Mat img = cv::imread(names[i], 0);
res[i] = getHOG(img, veclen);
}
*setlen = dataSetLength;
return res;
}
void test()//Training and activate SVM
{
int setlen, veclen;
float **trainingData = getTraininigData(&setlen, &veclen);
float *labels = new float[dataSetLength];
for(int i = 0; i < dataSetLength; i++)
{
labels[i] = (i < dataSetLength/2)? 0.0 : 1.0;
}
cv::Mat labelsMat(setlen, 1, CV_32FC1, labels);
cv::Mat trainingDataMat(setlen, veclen, CV_32FC1, trainingData);
cv::SVMParams params;
params.svm_type = cv::SVM::C_SVC;
params.kernel_type = cv::SVM::LINEAR;
params.term_crit = cv::TermCriteria(CV_TERMCRIT_ITER, 100, 1e-6);
std::cout<<labelsMat<<"\n";
cv::SVM SVM;
SVM.train(trainingDataMat, labelsMat, cv::Mat(), cv::Mat(), params);
cv::Mat img = cv::imread("../faces/s1/2.pgm", 0);//sample from train data, but ansewer is 1 for every sample
auto desc = getHOG(img, &veclen);
cv::Mat sampleMat(1, veclen, CV_32FC1, desc);
float response = SVM.predict(sampleMat);
std::cout<<"resp "<< response<<"\n";
}
What wrong with my code ?
PS sorry for my writing mistakes. English in not my native language

Answer 1

You don't have much training data. Note how Dalal and Triggs in their original paper on HOG (http://lear.inrialpes.fr/people/triggs/pubs/Dalal-cvpr05.pdf) used thousands of examples to train the SVM, you have just 5 negative and 5 positive.
You haven't set the C parameter (you need to find a good value via cross validation) - you will need more data.
Possibly HOG descriptors for faces and cars are not separable with a linear kernel, try RBF.
But this is unlikely to be an issue since D&L use a linear SVM in their paper.
Read this: http://www.csie.ntu.edu.tw/~cjlin/papers/guide/guide.pdf
If you haven't done this yet, get the SVM working for a simpler case (e.g. just use image patches instead of HOG).