distance.h

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#ifndef VOCABULARY_TREE_DISTANCE_H
#define VOCABULARY_TREE_DISTANCE_H

#include <stdint.h>
#include <Eigen/Core>

namespace vt {
namespace distance {

template<typename T>
struct Accumulator
{
  typedef T type;
};

template<> struct Accumulator<uint8_t>  { typedef uint32_t type; };
template<> struct Accumulator<uint16_t> { typedef uint32_t type; };
template<> struct Accumulator<int8_t>   { typedef int32_t type; };
template<> struct Accumulator<int16_t>  { typedef int32_t type; };
// Have noticed loss of precision when computing sum-squared-error with many input features.
template<> struct Accumulator<float>    { typedef double type; };

template<class Feature>
struct L2
{
  typedef typename Feature::value_type value_type;
  typedef typename Accumulator<value_type>::type result_type;

  result_type operator()(const Feature& a, const Feature& b) const
  {
    result_type result = result_type();
    for (size_t i = 0; i < a.size(); ++i) {
      result_type diff = a[i] - b[i];
      result += diff*diff;
    }
    return result;
  }
};

template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
struct L2< Eigen::Matrix<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
{
  typedef Eigen::Matrix<Scalar, Rows, Cols, Options, MaxRows, MaxCols> feature_type;
  typedef Scalar value_type;
  typedef typename Accumulator<Scalar>::type result_type;

  result_type operator()(const feature_type& a, const feature_type& b) const
  {
    return (a - b).squaredNorm();
  }
};

} } //namespace vt::distance

#endif