cv::Mat OpenCvDetector::calculateFeatureMatrix(const Segments& segments)
{
cv::Mat featureMatrix(segments.size(), m_featureDimensions.size(), CV_32FC1);
for(size_t i = 0; i < segments.size(); i++) {
const Segment& segment = segments[i];
std::map<FeatureDimension, float> featureValueLookup; // one entry per dimension per feature
for(size_t j = 0; j < m_features.size(); j++) {
Feature::Ptr feature = m_features[j];
Eigen::VectorXd values;
feature->evaluate(segment, values);
// Each feature can have multiple dimensions, store these in a map so we can look up
// the requested dimensions in the next step
for(size_t dim = 0; dim < feature->getNDimensions(); dim++) {
featureValueLookup[ feature->getDescription(dim) ] = values(dim);
}
}
// Look up the requested dimensions
for(size_t k = 0; k < m_featureDimensions.size(); k++) {
const FeatureDimension& featureDescription = m_featureDimensions[k];
featureMatrix.at<float>(i, k) = featureValueLookup[featureDescription];
}
}
return featureMatrix;
}
void OpenCvDetector::detect(const Segments& segments, Labels& labels, Confidences& confidences)
{
cv::Mat featureMatrix = calculateFeatureMatrix(segments);
for(size_t i = 0; i < segments.size(); i++) {
// Implemented by the derived class.
classifyFeatureVector(featureMatrix.row(i), labels[i], confidences[i]);
}
}
