EfficientModel (DEPRECATED in favor of the new CloudPrepare class) More...
#include <EfficientModel.h>
Public Member Functions | |
EfficientModel (const std::vector< Point2 > &vPoints) | |
void | extract (double maxError, std::vector< Point2 > &vEfficientPointsOut) |
Extract a subset of points. More... | |
void | zSmoothing (int numIterations, double maxDifferencePerIteration, SmoothingStrategy sms) |
Smoothing. More... | |
Protected Member Functions | |
void | go () |
int | insertKeepError (double factor, double err, std::vector< Point2 * > &vIn, std::vector< Point2 * > &vNeedlessBigError, std::vector< Point2 * > &vNeedlessSmallError) |
void | insertMinHull () |
void | part1_extractFC () |
void | part2_setWeights () |
void | show (const char *name) |
void | solveCand (Candidate *pCand, double maxErr) |
void | sortVtx (std::vector< Point2 * > &vVtx) |
EfficientModel (DEPRECATED in favor of the new CloudPrepare class)
void GEOM_FADE25D::EfficientModel::extract | ( | double | maxError, |
std::vector< Point2 > & | vEfficientPointsOut | ||
) |
Extract a subset of points.
This method extracts a subset of the original point cloud that represents the model more efficiently. Thereby the original and the simplified model cover the same area.
maxError | is the maximum height difference between the original points and the simplified model. | |
[out] | vEfficientPointsOut | is used to return a subset of the original points that represents the model more efficiently. |
maxError
is tiny i.e., below the noise level of the point cloud, then processing can take quite some time. Consider using the zSmoothing() method before. void GEOM_FADE25D::EfficientModel::zSmoothing | ( | int | numIterations, |
double | maxDifferencePerIteration, | ||
SmoothingStrategy | sms | ||
) |
Smoothing.
This method should be used before extract(). It adapts the z-values according to the chosen SmoothingStrategy sms
.
numIterations | Number of iterations |
maxDifferencePerIteration | is the maximum change of any z-value |
sms | is one of SMST_MINIMUM, SMST_MAXIMUM, SMST_MEDIAN, SMST_AVERAGE |