double compareSpatiograms(const spatiogram &p, const spatiogram &q ){
CV_Assert(p.bins==q.bins);
cv::Mat temp = cv::Mat::zeros(1, p.bins, CV_64FC1);
cv::Mat w = cv::Mat::zeros(1, p.bins, CV_64FC1);
for (int i=0; i<p.bins; i++){
// Means
cv::Mat ub1(2,1,CV_64FC1);
ub1.at<double>(0,0)=p.mu.at<double>(0,i);
ub1.at<double>(1,0)=p.mu.at<double>(1,i);
cv::Mat ub2(2,1,CV_64FC1);
ub2.at<double>(0,0)=q.mu.at<double>(0,i);
ub2.at<double>(1,0)=q.mu.at<double>(1,i);
// covariances in matrix format and clipped to 1
cv::Mat cm1=cv::Mat::ones(2,2,CV_64FC1);
cm1.at<double>(0,0) += p.cm.at<double>(0,i);
cm1.at<double>(1,1) += p.cm.at<double>(1,i);
cv::Mat cm2=cv::Mat::ones(2,2,CV_64FC1);
cm2.at<double>(0,0) += q.cm.at<double>(0,i);
cm2.at<double>(1,1) += q.cm.at<double>(1,i);
// weightening factor
cv::Mat invS = cm1.inv(cv::DECOMP_LU) + cm2.inv(cv::DECOMP_LU);
cv::Mat diff = ub2-ub1;
cv::Mat expo = (-0.5)*diff.t()*invS*diff;
w.at<double>(0,i) = std::exp( expo.at<double>(0,0) );
// Bhattacharyya coefficient
double rho = sqrt( p.cd.at<double>(0,i)*q.cd.at<double>(0,i) );
temp.at<double>(0,i) = (w.at<double>(0,i)) * rho;
}
return cv::sum(temp)[0];
}
TEST(BoundingBox, CoordinateSize){
Point lb(1,2,0);
Point ub(2,4,0);
BoundingBox bb1(lb, ub);
EXPECT_EQ(2, bb1.sizeCoordX());
EXPECT_EQ(3, bb1.sizeCoordY());
EXPECT_EQ(1, bb1.sizeCoordZ());
Point lb2(1,2,0);
Point ub2(2,4,0);
BoundingBox bb2(lb, ub);
// Intersection should return an bounding box equal to bb2 and bb1,
// they are the same bb
BoundingBox bbIntersection = bb2.intersection(bb1);
EXPECT_TRUE( bbIntersection.getLb().getX() == bb2.getLb().getX() &&
bbIntersection.getLb().getY() == bb2.getLb().getY() &&
bbIntersection.getLb().getZ() == bb2.getLb().getZ());
EXPECT_TRUE( bbIntersection.getUb().getX() == bb2.getUb().getX() &&
bbIntersection.getUb().getY() == bb2.getUb().getY() &&
bbIntersection.getUb().getZ() == bb2.getUb().getZ());
Point lb3(2,3,0);
Point ub3(2,4,0);
BoundingBox bb3(lb3, ub3);
bbIntersection = bb2.intersection(bb3);
// lower bound is the value of of bb3
EXPECT_TRUE( bbIntersection.getLb().getX() == lb3.getX() &&
bbIntersection.getLb().getY() == lb3.getY() &&
bbIntersection.getLb().getZ() == lb3.getZ());
// upper bound should not change
EXPECT_TRUE( bbIntersection.getUb().getX() == bb2.getUb().getX() &&
bbIntersection.getUb().getY() == bb2.getUb().getY() &&
bbIntersection.getUb().getZ() == bb2.getUb().getZ());
}
TEST(BoundingBox, NoIntersection){
Point lb(1,2,0), ub(2,4,0), lb2(3,5,0), ub2(4,6,0);
BoundingBox bb1(lb, ub);
BoundingBox bb2(lb2, ub2);
// Intersection should return an bounding box equal to bb2 and bb1,
// they are the same bb
BoundingBox bbInter = bb2.intersection(bb1);
EXPECT_FALSE( bb1.doesIntersect(bb2));
// Lower bound of intersection should contain greater values
// among lower bound of both bounding boxes (lb2)
EXPECT_TRUE( bbInter.getLb().getX() == lb2.getX() &&
bbInter.getLb().getY() == lb2.getY() &&
bbInter.getLb().getZ() == lb2.getZ());
// Upper bound of intersection should contain smaller values
// among upper bound of both bounding boxes (ub)
EXPECT_TRUE( bbInter.getUb().getX() == ub.getX() &&
bbInter.getUb().getY() == ub.getY() &&
bbInter.getUb().getZ() == ub.getZ());
}
//Construct the kdTree
kdTree::kdTree(vector<vector<double>> points, const string& method,
int cutdimension):
splitMethod(method){
if (points.empty())
{
kdTreeRoot = nullptr;
return;
}
// Select intial splitting axis
int dimension = (int)(points[0].size());
int axis = cutdimension % dimension;
size_t lb1(0),lb2(0),ub1(0),ub2(0);
size_t pivotLocation;
size_t numpoints = points.size();
if(numpoints == 1)
{
kdTreeRoot = shared_ptr<kdTreeNode>(new kdTreeNode(points[0]));
}
else
{
sort(points.begin(), points.end(), sorter(axis));
if (method == "median")
{
pivotLocation = (size_t)(numpoints/2);
}
else if (method == "mean")
{
double mean(0.0);
for (size_t i=0;i<numpoints;i++)
{
mean = mean + points[i][axis];
}
mean =mean/(double)numpoints;
for (size_t i=0;i<numpoints;i++)
{
if (points[i][axis]>= mean)
{
pivotLocation = i;
break;
}
}
}
/* lb1 = 0; */
ub1 = pivotLocation;
lb2 = pivotLocation +1;
ub2 = (size_t)points.size();
// Recursively create Left SubTree
unique_ptr<kdTree> left_child = move(unique_ptr<kdTree> (new kdTree(
slice<vector<double>>(points,lb1,ub1),
method,axis+1)));
// Recursively create Right SubTree
unique_ptr<kdTree> right_child = move(unique_ptr<kdTree> (new kdTree(
slice<vector<double>>(points,lb2,ub2),
method,axis+1)));
kdTreeRoot = shared_ptr<kdTreeNode>(
new kdTreeNode(
points[pivotLocation],
axis,
right_child->kdTreeRoot,
left_child->kdTreeRoot));
}
}
