void
opengv::sac::MultiSampleConsensusProblem<M>::selectWithinDistance(
const model_t & model_coefficients,
const double threshold,
std::vector<std::vector<int> > &inliers )
{
std::vector<std::vector<double> > dist;
dist.resize(indices_->size());
inliers.clear();
inliers.resize(indices_->size());
for( size_t j = 0; j < indices_->size(); j++ )
dist[j].reserve((*indices_)[j].size());
getDistancesToModel( model_coefficients, dist );
for( size_t j = 0; j < indices_->size(); j++ )
{
inliers[j].clear();
inliers[j].reserve((*indices_)[j].size());
for(size_t i = 0; i < dist[j].size(); ++i)
{
if( dist[j][i] < threshold )
inliers[j].push_back( (*indices_)[j][i] );
}
}
}
int
opengv::sac::SampleConsensusProblem<M>::countWithinDistance(
const model_t & model_coefficients, const double threshold)
{
std::vector<double> dist;
dist.reserve(indices_->size());
getDistancesToModel( model_coefficients, dist );
int count = 0;
for( size_t i = 0; i < dist.size(); ++i )
{
if( dist[i] < threshold )
++count;
}
return count;
}
void RansacProblem<M>::selectWithinDistance (const model_t & model_coefficients,
const double threshold,
std::vector<int> &inliers)
{
std::vector<double> dist;
dist.reserve(indices_->size());
getDistancesToModel(model_coefficients, dist);
inliers.clear();
inliers.reserve(indices_->size());
for(size_t i = 0; i < dist.size(); ++i)
{
if(dist[i] < threshold)
{
inliers.push_back( (*indices_)[i] );
}
}
}
