/**
* Match two feature stores given a homography from the features in store 1 to store 2. The THRESHOLD is a spatial
* threshold in pixels to restrict the number of feature comparisons.
*
* @return Number of matches
*/
public int match(FreakFeaturePointStack i_query, FreakMatchPointSetStack i_ref, InverseHomographyMat i_hinv, double tr, FeaturePairStack i_maches)
{
if (i_query.getLength() * i_ref.getLength() == 0)
{
return(0);
}
double tr_sqr = tr * tr;
FreakFeaturePoint[] query_buf = i_query.getArray();
FreakMatchPointSetStack.Item[] ref_buf = i_ref.getArray();
int q_len = i_query.getLength();
int r_len = i_ref.getLength();
for (int i = 0; i < q_len; i++)
{
int first_best = int.MaxValue; // std::numeric_limits<unsigned int>::max();
int second_best = int.MaxValue; // std::numeric_limits<unsigned int>::max();
int best_index = int.MaxValue; // std::numeric_limits<int>::max();
FreakFeaturePoint fptr1 = query_buf[i];
// Map p1 to p2 space through H
//i_hinv.multiplyPointHomographyInhomogenous(fptr1.x, fptr1.y, tmp);
double qx, qy;
{
double w = i_hinv.m20 * fptr1.x + i_hinv.m21 * fptr1.y + i_hinv.m22;
qx = (i_hinv.m00 * fptr1.x + i_hinv.m01 * fptr1.y + i_hinv.m02) / w; // XP
qy = (i_hinv.m10 * fptr1.x + i_hinv.m11 * fptr1.y + i_hinv.m12) / w; // YP
}
// Search for 1st and 2nd best match
for (int j = 0; j < r_len; j++)
{
FreakFeaturePoint fptr2 = ref_buf[j];
// Both points should be a MINIMA or MAXIMA
if (fptr1.maxima != fptr2.maxima)
{
continue;
}
double tx = (qx - fptr2.x);
double ty = (qy - fptr2.y);
// Check spatial constraint
if ((tx * tx) + (ty * ty) > tr_sqr)
{
continue;
}
int d = fptr1.descripter.hammingDistance(fptr2.descripter);
if (d < first_best)
{
second_best = first_best;
first_best = d;
best_index = (int)j;
}
else if (d < second_best)
{
second_best = d;
}
}
// Check if FIRST_BEST has been set
if (first_best != int.MaxValue)
{
// If there isn't a SECOND_BEST, then always choose the FIRST_BEST.
// Otherwise, do a ratio test.
if (second_best == int.MaxValue)
{
FeaturePairStack.Item t = i_maches.prePush();
t.query = fptr1;
t.ref_ = ref_buf[best_index];
}
else
{
// Ratio test
double r = (double)first_best / (double)second_best;
if (r < this.mThreshold)
{
FeaturePairStack.Item t = i_maches.prePush();
t.query = fptr1;
t.ref_ = ref_buf[best_index];
}
}
}
}
return(i_maches.getLength());
}
/**
* Match two feature stores.
*
* @return Number of matches
*/
public virtual int match(FreakFeaturePointStack i_query, Keyframe i_key_frame, FeaturePairStack i_maches)
{
FreakMatchPointSetStack ref_ = i_key_frame.getFeaturePointSet();
if (i_query.getLength() == 0 || ref_.getLength() == 0)
{
return(0);
}
// mMatches.reserve(features1.size());
for (int i = 0; i < i_query.getLength(); i++)
{
int first_best = int.MaxValue;
int second_best = int.MaxValue;
int best_index = int.MaxValue;
// Search for 1st and 2nd best match
FreakFeaturePoint p1 = i_query.getItem(i);
for (int j = 0; j < ref_.getLength(); j++)
{
// Both points should be a MINIMA or MAXIMA
if (p1.maxima != ref_.getItem(j).maxima)
{
continue;
}
// ASSERT(FEATURE_SIZE == 96, "Only 96 bytes supported now");
int d = i_query.getItem(i).descripter.hammingDistance(ref_.getItem(j).descripter);
if (d < first_best)
{
second_best = first_best;
first_best = d;
best_index = (int)j;
}
else if (d < second_best)
{
second_best = d;
}
}
// Check if FIRST_BEST has been set
if (first_best != int.MaxValue)
{
// If there isn't a SECOND_BEST, then always choose the FIRST_BEST.
// Otherwise, do a ratio test.
if (second_best == int.MaxValue)
{
// mMatches.push_back(match_t((int)i, best_index));
FeaturePairStack.Item t = i_maches.prePush();
t.query = i_query.getItem(i);
t.ref_ = ref_.getItem(best_index);
}
else
{
// Ratio test
double r = (double)first_best / (double)second_best;
if (r < mThreshold)
{
FeaturePairStack.Item t = i_maches.prePush();
t.query = i_query.getItem(i);
t.ref_ = ref_.getItem(best_index);
// mMatches.push_back(match_t((int)i, best_index));
}
}
}
}
// ASSERT(mMatches.size() <= features1->size(), "Number of matches should be lower");
return(i_maches.getLength());
}
/**
* Match two feature stores with an index on features2.
*
* @return Number of matches
*/
override public int match(FreakFeaturePointStack i_query, Keyframe i_key_frame, FeaturePairStack i_maches)
{
//indexが無いときはベースクラスを使う。
BinaryHierarchicalNode index2 = i_key_frame.getIndex();
if (index2 == null)
{
return(base.match(i_query, i_key_frame, i_maches));
}
FreakMatchPointSetStack ref_ = i_key_frame.getFeaturePointSet();
if (i_query.getLength() * ref_.getLength() == 0)
{
return(0);
}
FreakFeaturePoint[] query_buf = i_query.getArray();
int q_len = i_query.getLength();
for (int i = 0; i < q_len; i++)
{
int first_best = int.MaxValue; // std::numeric_limits<unsigned int>::max();
int second_best = int.MaxValue; // std::numeric_limits<unsigned int>::max();
FreakMatchPointSetStack.Item best_index = null; // std::numeric_limits<int>::max();
// Perform an indexed nearest neighbor lookup
FreakFeaturePoint fptr1 = query_buf[i];
int num_of_fp = this._selector.query(index2, fptr1.descripter);
// Search for 1st and 2nd best match
FreakMatchPointSetStack.Item[] v = this._selector._result;
for (int j = 0; j < num_of_fp; j++)
{
FreakFeaturePoint fptr2 = v[j];
// Both points should be a MINIMA or MAXIMA
if (fptr1.maxima != fptr2.maxima)
{
continue;
}
int d = fptr1.descripter.hammingDistance(fptr2.descripter);
if (d < first_best)
{
second_best = first_best;
first_best = d;
best_index = v[j];
}
else if (d < second_best)
{
second_best = d;
}
}
// Check if FIRST_BEST has been set
if (first_best != int.MaxValue)
{
// If there isn't a SECOND_BEST, then always choose the FIRST_BEST.
// Otherwise, do a ratio test.
if (second_best == int.MaxValue)
{
FeaturePairStack.Item t = i_maches.prePush();
t.query = fptr1;
t.ref_ = best_index;
}
else
{
// Ratio test
double r = (double)first_best / (double)second_best;
if (r < mThreshold)
{
// mMatches.push_back(match_t((int)i, best_index));
FeaturePairStack.Item t = i_maches.prePush();
t.query = fptr1;
t.ref_ = best_index;
}
}
}
}
return(i_maches.getLength());
}
