980 lines
22 KiB
Text
980 lines
22 KiB
Text
/*
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* veloscan implementation
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*
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* Copyright (C) Andreas Nuechter, Li Wei, Li Ming
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*
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* Released under the GPL version 3.
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*
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*/
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/**
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* @file
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* @brief Implementation of a 3D scan and of 3D scan matching in all variants
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* @author Li Wei, Wuhan University, China
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* @author Li Ming, Wuhan University, China
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* @author Andreas Nuechter. Jacobs University Bremen, Germany
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*/
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#ifdef _MSC_VER
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#ifdef OPENMP
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#define _OPENMP
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#endif
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#endif
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#include <fstream>
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using std::ifstream;
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using std::ofstream;
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#include <iostream>
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using std::cout;
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using std::cerr;
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using std::endl;
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#include <sstream>
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using std::stringstream;
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#include "veloslam/veloscan.h"
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#ifdef _OPENMP
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#include <omp.h>
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#endif
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#ifdef _MSC_VER
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#include <windows.h>
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#else
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#include <dlfcn.h>
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#endif
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#ifdef _MSC_VER
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#define strcasecmp _stricmp
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#define strncasecmp _strnicmp
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#else
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#include <strings.h>
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#endif
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#include <cstring>
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using std::flush;
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#include "slam6d/Boctree.h"
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#include "veloslam/veloscan.h"
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#include "veloslam/pcddump.h"
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#include "veloslam/trackermanager.h"
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#include "veloslam/clusterboundingbox.h"
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#ifdef _OPENMP
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#include <omp.h>
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#endif
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#ifdef _MSC_VER
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#include <windows.h>
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#else
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#include <dlfcn.h>
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#endif
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#ifdef _MSC_VER
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#define strcasecmp _stricmp
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#define strncasecmp _strnicmp
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#else
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#include <strings.h>
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#endif
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#include <cstring>
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using std::flush;
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#include <GL/gl.h>
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#include <GL/glu.h>
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#ifdef _MSC_VER
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#include <GL/glut.h>
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#else
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#include <GL/freeglut.h>
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#endif
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#include "veloslam/velodefs.h"
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#include "veloslam/color_util.h"
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int scanCount =0;
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TrackerManager trackMgr;
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float absf(float a)
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{
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return a>0?a:-a;
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}
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Trajectory::Trajectory()
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{
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}
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/**
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* default Constructor
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*/
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VeloScan::VeloScan()
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: Scan()
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{
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isTrackerHandled =false;
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}
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/**
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* Desctuctor
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*/
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VeloScan::~VeloScan()
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{
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FreeAllCellAndCluterMemory();
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}
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int VeloScan::DeletePoints()
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{
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FreeAllCellAndCluterMemory();
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return 0;
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}
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/**
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* Copy constructor
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*/
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VeloScan::VeloScan(const VeloScan& s)
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: Scan(s)
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{ }
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int VeloScan::TransferToCellArray(int maxDist, int minDist)
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{
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#define DefaultColumnSize 360
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Point P;
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DataXYZ xyz(get("xyz"));
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int size= xyz.size();
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int columnSize= 360; //cfg.cfgPlaneDetect.ColumnSize;
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int CellSize= 50; //cfg.cfgPlaneDetect.CellSize;
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int MinRad=minDist; //cfg.cfgPlaneDetect.MinRad;
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int MaxRad=maxDist; //cfg.cfgPlaneDetect.MaxRad
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if((MaxRad-MinRad)%CellSize!=0)
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CellSize=10;
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int i,j,count=0;
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int CellNumber=(MaxRad-MinRad)/CellSize;
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float flag;
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int offset;
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if(columnSize==0)
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return -1;
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if(columnSize%360!=0)
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columnSize=DefaultColumnSize;
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int sectionSize=columnSize/8;
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scanCellArray.resize(columnSize);
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for(i=0; i<columnSize; ++i)
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scanCellArray[i].resize(CellNumber);
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float inc=(M_PI*2)/columnSize;
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vector<float> tanv;
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vector<float>::iterator result;
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for(i=0; i<sectionSize; ++i)
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{
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tanv.push_back(tan(inc*i));
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}
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int diff;
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for(i=0; i<size; ++i)
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{
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count++;
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Point pt;
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pt.x = xyz[i][0];
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pt.y = xyz[i][1];
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pt.z = xyz[i][2];
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pt.point_id = i; //important for find point in scans ---raw points
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pt.rad = sqrt(pt.x*pt.x + pt.z*pt.z);
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pt.tan_theta = pt.z/pt.x ;
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if(pt.rad <=MinRad || pt.rad>=MaxRad)
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continue;
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// some point losted which on the vline or hline
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if(pt.x >=0 && pt.z>=0 )
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{
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if(pt.x > pt.z)
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{
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flag= pt.tan_theta;
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result=upper_bound(tanv.begin(),tanv.end(),flag);
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if(result==tanv.end())
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{
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offset=sectionSize-1;
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}
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else
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{
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offset=result-tanv.begin();
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}
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}
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else
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{
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flag=1/pt.tan_theta;
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result=upper_bound(tanv.begin(),tanv.end(),flag);
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if(result==tanv.end())
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{
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offset=sectionSize;
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}
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else
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{
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diff=result-tanv.begin();
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offset=sectionSize*2-1-(diff);
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}
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}
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}
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else if(pt.x <= 0 && pt.z >=0)
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{
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if(-pt.x>pt.z)
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{
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flag=-pt.tan_theta;
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result=upper_bound(tanv.begin(),tanv.end(),flag);
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if(result==tanv.end())
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{
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offset=sectionSize*3;
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}
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else
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{
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offset=sectionSize*4-1-(result-tanv.begin());
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}
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}
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else
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{
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flag=1/-pt.tan_theta;
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result=upper_bound(tanv.begin(),tanv.end(),flag);
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if(result==tanv.end())
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{
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offset=sectionSize*3-1;
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}
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else
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{
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offset=sectionSize*2+(result-tanv.begin());
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}
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}
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}
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else if(pt.x<=0 && pt.z<=0)
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{
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if(-pt.x>-pt.z)
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{
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flag=pt.tan_theta;
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result=upper_bound(tanv.begin(),tanv.end(),flag);
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if(result==tanv.end())
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{
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offset=sectionSize*5-1;
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}
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else
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{
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offset=sectionSize*4+(result-tanv.begin());
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}
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}
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else
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{
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flag=1/pt.tan_theta;
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result=upper_bound(tanv.begin(),tanv.end(),flag);
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if(result==tanv.end())
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{
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offset=sectionSize*5;
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}
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else
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{
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offset=sectionSize*6-1-(result-tanv.begin());
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}
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}
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}
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else if(pt.x>=0&&pt.z<=0)
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{
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if(pt.x>-pt.z)
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{
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flag=-pt.tan_theta;
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result=upper_bound(tanv.begin(),tanv.end(),flag);
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if(result==tanv.end())
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{
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offset=sectionSize*7;
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}
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else
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{
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offset=sectionSize*8-1-(result-tanv.begin());
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}
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}
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else
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{
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flag=1/-pt.tan_theta;
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result=upper_bound(tanv.begin(),tanv.end(),flag);
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if(result==tanv.end())
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{
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offset=sectionSize*7-1;
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}
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else
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{
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offset=sectionSize*6+(result-tanv.begin());
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}
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}
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}
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else
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{
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continue;
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}
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int k= (int)((pt.rad-MinRad)/(CellSize*1.0));
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scanCellArray[offset][k].push_back(&pt);
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}
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return 0;
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}
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int VeloScan::CalcCellFeature(cell& cellobj, cellFeature& f)
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{
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int outlier;
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float lastMaxY;
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f.size=cellobj.size();
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f.cellType=0;
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if(f.size==0)
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{
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f.cellType|=CELL_TYPE_INVALID;
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return 0;
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}
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f.ave_x= f.ave_y = f.ave_z=0.0;
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f.delta_y=0;
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int i=0;
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for(i=0; i<f.size; ++i)
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{
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f.ave_x+=cellobj[i]->x;
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f.ave_z+=cellobj[i]->z;
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f.ave_y+=cellobj[i]->y;
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// if(cellobj[i]->type & POINT_TYPE_BELOW_R)
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// f.cellType |=CELL_TYPE_BELOW_R;
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if(i==0)
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{
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outlier=0;
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f.min_x=f.max_x=cellobj[i]->x;
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f.min_z=f.max_z=cellobj[i]->z;
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lastMaxY=f.min_y=f.max_y=cellobj[i]->y;
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}
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else
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{
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if(f.max_x<cellobj[i]->x) f.max_x=cellobj[i]->x;
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if(f.min_x>cellobj[i]->x) f.min_x=cellobj[i]->x;
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if(f.max_z<cellobj[i]->z) f.max_z=cellobj[i]->z;
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if(f.min_z>cellobj[i]->z) f.min_z=cellobj[i]->z;
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if(f.max_y<cellobj[i]->y)
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{
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lastMaxY=f.max_y;
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f.max_y=cellobj[i]->y;
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outlier=i;
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}
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if(f.min_y>cellobj[i]->y)
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f.min_y=cellobj[i]->y;
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}
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}
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if(f.size>1)
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{
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int y=f.ave_y-cellobj[outlier]->y;
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y/=(f.size-1)*1.0;
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if(cellobj[outlier]->y-y<50)
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{
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outlier=-1;
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f.ave_y/=f.size*1.0;
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}
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else
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{
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f.max_y=lastMaxY;
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f.ave_y=y;
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}
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}
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else
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{
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outlier=-1;
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f.ave_y/=f.size*1.0;
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}
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f.ave_x/=f.size*1.0;
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f.ave_z/=f.size*1.0;
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for(i=0; i<f.size; ++i)
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{
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if(i==outlier)
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continue;
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f.delta_y+= absf(cellobj[i]->y - f.ave_y);
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}
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float threshold;
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threshold=f.delta_y;
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float GridThresholdGroundDetect =120;
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if( threshold > GridThresholdGroundDetect)
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f.cellType =CELL_TYPE_STATIC;
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else
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f.cellType =CELL_TYPE_GROUND;
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return 0;
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}
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int VeloScan::CalcScanCellFeature()
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{
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int i,j;
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if( scanCellArray.size()==0)
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return -1;
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int columnSize=scanCellArray.size();
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int cellNumber=scanCellArray[0].size();
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if( scanCellFeatureArray.size()==0)
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{
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scanCellFeatureArray.resize(columnSize);
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for(i=0; i<columnSize; ++i)
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scanCellFeatureArray[i].resize(cellNumber);
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}
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for(j=0; j <columnSize; j++)
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{
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cellColumn &column=scanCellArray[j];
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cellNumber=column.size();
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for( i=0; i<cellNumber; i++)
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{
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cell &cellObj=scanCellArray[j][i];
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cellFeature &feature=scanCellFeatureArray[j][i];
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feature.columnID=j;
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feature.cellID=i;
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feature.pCell=&cellObj;
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CalcCellFeature(cellObj,feature);
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// if( feature.delta_y > 120)
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// {
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// scanCellFeatureArray[j][i].cellType |= CELL_TYPE_STATIC;
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// for(int k=0;k <scanCellArray[j][i].size(); k++)
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// scanCellArray[j][i][k]->type |= POINT_TYPE_ABOVE_DELTA_Y;
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//
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// }
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}
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}
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return 0;
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}
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int VeloScan::SearchNeigh(cluster& clu,charvv& flagvv,int i,int j)
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{
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int columnSize=scanCellArray.size();
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int cellNumber=scanCellArray[0].size();
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if(i==-1)
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i= columnSize-1;
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if(i==columnSize)
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i= 0;
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if(i<0||i>=columnSize||j<0||j>=cellNumber)
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return 0;
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if(flagvv[i][j]==1)
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return 0;
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if(scanCellFeatureArray[i][j].size==0)
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{
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flagvv[i][j]=1;
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return 0;
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}
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if(scanCellFeatureArray[i][j].cellType & CELL_TYPE_STATIC)
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{
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flagvv[i][j]=1;
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clu.push_back(&scanCellFeatureArray[i][j]);
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SearchNeigh(clu,flagvv,i-1,j-1);
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SearchNeigh(clu,flagvv,i-1,j);
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SearchNeigh(clu,flagvv,i-1,j+1);
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SearchNeigh(clu,flagvv,i,j-1);
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SearchNeigh(clu,flagvv,i,j+1);
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SearchNeigh(clu,flagvv,i+1,j-1);
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SearchNeigh(clu,flagvv,i+1,j);
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SearchNeigh(clu,flagvv,i+1,j+1);
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SearchNeigh(clu,flagvv,i,j+2);
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SearchNeigh(clu,flagvv,i,j-2);
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SearchNeigh(clu,flagvv,i+2,j);
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SearchNeigh(clu,flagvv,i-2,j);
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//SearchNeigh(clu,flagvv,i,j+3);
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//SearchNeigh(clu,flagvv,i,j-3);
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//SearchNeigh(clu,flagvv,i+3,j);
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//SearchNeigh(clu,flagvv,i-3,j);
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}
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return 0;
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}
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int VeloScan::CalcClusterFeature(cluster& clu, clusterFeature& f)
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{
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f.size=clu.size();
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if(f.size==0)
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{
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return 0;
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}
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f.clusterType=0;
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f.pointNumber=0;
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f.avg_x =0; f.avg_y=0; f.avg_z=0;
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int i=0;
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for(i=0; i<f.size; ++i)
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{
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f.avg_x += clu[i]->ave_x;
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f.avg_y += clu[i]->ave_y;
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f.avg_z += clu[i]->ave_z;
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if(i==0)
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{
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f.min_x=f.max_x=clu[i]->min_x;
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f.min_z=f.max_z=clu[i]->min_z;
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f.min_y=f.max_y=clu[i]->min_y;
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}
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else
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{
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if(f.max_x<clu[i]->max_x)
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f.max_x=clu[i]->max_x;
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if(f.min_x>clu[i]->min_x)
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f.min_x=clu[i]->min_x;
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if(f.max_z<clu[i]->max_z)
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f.max_z=clu[i]->max_z;
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if(f.min_z>clu[i]->min_z)
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f.min_z=clu[i]->min_z;
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if(f.max_y<clu[i]->max_y)
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f.max_y=clu[i]->max_y;
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if(f.min_y>clu[i]->min_y)
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f.min_y=clu[i]->min_y;
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}
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f.pointNumber+=clu[i]->size;
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f.theta += clu[i]->size*clu[i]->columnID;
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f.radius += clu[i]->size*clu[i]->cellID;
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}
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|
|
f.size_x=f.max_x-f.min_x;
|
|
f.size_z=f.max_z-f.min_z;
|
|
f.size_y=f.max_y-f.min_y;
|
|
|
|
f.avg_x /= f.size;
|
|
f.avg_y /= f.size;
|
|
f.avg_z /= f.size;
|
|
|
|
f.theta=f.theta / (f.pointNumber*1.0);
|
|
f.radius=f.radius / (f.pointNumber*1.0);
|
|
|
|
return 0;
|
|
}
|
|
|
|
int VeloScan::FindAndCalcScanClusterFeature()
|
|
{
|
|
int i,j;
|
|
|
|
if( scanCellArray.size()==0)
|
|
return -1;
|
|
|
|
int columnSize=scanCellArray.size();
|
|
int cellNumber=scanCellArray[0].size();
|
|
|
|
charvv searchedFlag;
|
|
searchedFlag.resize(columnSize);
|
|
for(i=0; i<columnSize; ++i)
|
|
searchedFlag[i].resize(cellNumber,0);
|
|
|
|
for(i=0; i<columnSize; ++i)
|
|
{
|
|
for(j=0; j<cellNumber; ++j)
|
|
{
|
|
cluster clu;
|
|
SearchNeigh(clu,searchedFlag,i,j);
|
|
if(clu.size())
|
|
scanClusterArray.push_back(clu);
|
|
}
|
|
}
|
|
|
|
int clustersize=scanClusterArray.size();
|
|
if(scanClusterFeatureArray.size()==0)
|
|
scanClusterFeatureArray.resize(clustersize);
|
|
|
|
cout<<"clusterSize:"<<clustersize<<endl;
|
|
for(i=0; i<clustersize; ++i)
|
|
{
|
|
CalcClusterFeature(scanClusterArray[i],scanClusterFeatureArray[i]);
|
|
// BoundingBox clusterBox;
|
|
// clusterBox.CalBestRectangleBox(scanClusterArray[i],scanClusterFeatureArray[i]);
|
|
}
|
|
return 0;
|
|
}
|
|
|
|
void VeloScan::FreeAllCellAndCluterMemory()
|
|
{
|
|
int i,j;
|
|
int columnSize=scanCellArray.size();
|
|
int cellNumber=scanCellArray[0].size();
|
|
|
|
for(j=0; j <columnSize; j++)
|
|
{
|
|
cellColumn &column=scanCellArray[j];
|
|
cellFeatureColumn &columnFeature=scanCellFeatureArray[j];
|
|
|
|
cellNumber=column.size();
|
|
for( i=0; i<cellNumber; i++)
|
|
{
|
|
cell &cellObj=scanCellArray[j][i];
|
|
cellFeature &feature=scanCellFeatureArray[j][i];
|
|
cellObj.clear();
|
|
|
|
}
|
|
column.clear();
|
|
columnFeature.clear();
|
|
}
|
|
|
|
scanCellArray.clear();
|
|
scanCellFeatureArray.clear();
|
|
int ClusterSize=scanClusterArray.size();
|
|
for(j=0; j <ClusterSize; j++)
|
|
{
|
|
cluster &cludata=scanClusterArray[j];
|
|
clusterFeature &clu=scanClusterFeatureArray[j];
|
|
cludata.clear();
|
|
// clu.clear();
|
|
}
|
|
scanClusterArray.clear();
|
|
scanClusterFeatureArray.clear();
|
|
}
|
|
|
|
void VeloScan::calcReducedPoints_byClassifi(double voxelSize, int nrpts, PointType pointtype)
|
|
{
|
|
// only copy the points marked POINT_TYPE_STATIC_OBJECT
|
|
int realCount =0;
|
|
|
|
// get xyz to start the scan load, separated here for time measurement
|
|
DataXYZ xyz(get("xyz"));
|
|
DataType Pt(get("type"));
|
|
|
|
// if the scan hasn't been loaded we can't calculate anything
|
|
if(xyz.size() == 0)
|
|
throw runtime_error("Could not calculate reduced points, XYZ data is empty");
|
|
|
|
for (int i = 0; i < xyz.size(); i++)
|
|
{
|
|
if( Pt[i] & POINT_TYPE_STATIC_OBJECT)
|
|
{
|
|
realCount++;
|
|
}
|
|
}
|
|
|
|
// load only static part of scans in point_red for icp6D
|
|
DataXYZ xyz_t(create("xyz reduced", sizeof(double)*3*realCount));
|
|
realCount=0;
|
|
int j=0;
|
|
for (int i = 0; i < xyz.size(); i++)
|
|
{
|
|
if( Pt[i] & POINT_TYPE_STATIC_OBJECT)
|
|
{
|
|
xyz_t[j][0] = xyz[i][0];
|
|
xyz_t[j][1] = xyz[i][1];
|
|
xyz_t[j][2] = xyz[i][2];
|
|
j++;
|
|
realCount++;
|
|
}
|
|
}
|
|
|
|
// build octree-tree from CurrentScan
|
|
// put full data into the octtree
|
|
BOctTree<double> *oct = new BOctTree<double>(PointerArray<double>(xyz_t).get(),
|
|
xyz_t.size(), reduction_voxelSize, reduction_pointtype);
|
|
|
|
vector<double*> center;
|
|
center.clear();
|
|
|
|
if (reduction_nrpts > 0) {
|
|
if (reduction_nrpts == 1) {
|
|
oct->GetOctTreeRandom(center);
|
|
} else {
|
|
oct->GetOctTreeRandom(center, reduction_nrpts);
|
|
}
|
|
} else {
|
|
oct->GetOctTreeCenter(center);
|
|
}
|
|
|
|
// storing it as reduced scan
|
|
unsigned int size = center.size();
|
|
DataXYZ xyz_r(create("xyz reduced", sizeof(double)*3*size));
|
|
for(unsigned int i = 0; i < size; ++i) {
|
|
for(unsigned int j = 0; j < 3; ++j) {
|
|
xyz_r[i][j] = center[i][j];
|
|
}
|
|
}
|
|
|
|
delete oct;
|
|
}
|
|
|
|
bool findBusCluster(clusterFeature &glu, cluster &gluData)
|
|
{
|
|
/* double labelSVM;
|
|
for(int i=0;i<360;i++)
|
|
{
|
|
nod[i].index=i+1;
|
|
nod[i].value=intersectionFeature[i].slashLength/slashMaxLength;
|
|
}
|
|
nod[360].index=-1;
|
|
labelSVM= svm_predict(m,nod);
|
|
|
|
ofstream output;
|
|
output.open("intersection.txt");
|
|
output<<"labelSVM:"<<labelSVM<<endl;
|
|
for(int j=0;j<360;j++)
|
|
output<<j<<":"<<" "<<nod[j].value;
|
|
output.close();
|
|
|
|
if(labelSVM>0.5)
|
|
cout<<"intersection"<<endl;
|
|
else
|
|
cout<<"segment"<<endl;
|
|
*/
|
|
return 0;
|
|
}
|
|
|
|
//long objcount =0;
|
|
// In one scans find which the more like moving object such as pedestrian, car, bus.
|
|
bool FilterNOMovingObjcets(clusterFeature &glu, cluster &gluData)
|
|
{
|
|
// small object do not use it!
|
|
if(glu.size <3)
|
|
return false;
|
|
if(glu.size_x > 800 || glu.size_z > 800 )
|
|
{
|
|
return false;
|
|
}
|
|
return true;
|
|
// no filter
|
|
|
|
//char filename[256];
|
|
//string file;
|
|
//sprintf(filename,"c:\\filename%d.txt", objcount);
|
|
//file =filename;
|
|
//DumpPointtoFile(gluData, file);
|
|
//DumpFeaturetoFile(glu, "c:\\feature");
|
|
//objcount++;
|
|
}
|
|
|
|
//long objcount =0;
|
|
// In one scans find which the more like moving object such as pedestrian, car, bus.
|
|
bool FindMovingObjcets(clusterFeature &glu, cluster &gluData)
|
|
{
|
|
// for debug moving object detections.
|
|
|
|
if( glu.size_y > 200 && ((glu.size_x>glu.size_y?glu.size_x:glu.size_y))<360)
|
|
{
|
|
return false;
|
|
}
|
|
else if((glu.size_y>350 && glu.size_x<140)|| (glu.size_x>350 && glu.size_y<140))
|
|
{
|
|
return false;
|
|
}
|
|
else if(glu.size_y > 250 )
|
|
{
|
|
return false;
|
|
}
|
|
else if((glu.size_x>glu.size_y?glu.size_x:glu.size_y)>420 && glu.size_z<130)
|
|
{
|
|
return false;
|
|
}
|
|
else if((glu.size_x>glu.size_y?glu.size_x:glu.size_y)>3.5
|
|
&& ((glu.size_x>glu.size_y?glu.size_x:glu.size_y)/(glu.size_x<glu.size_y?glu.size_x:glu.size_y)>4))
|
|
{
|
|
return false;
|
|
}
|
|
else if(glu.size_x<700 && glu.size_z<700 && glu.size_y > 100 )
|
|
{
|
|
return true;
|
|
}
|
|
if(glu.size_x>1500 || glu.size_z>1500 || glu.size_x*glu.size_z >600*600 )
|
|
{
|
|
return false;
|
|
}
|
|
if (glu.size_x*glu.size_z > 500*500 && glu.size_x/glu.size_z < 1.5)
|
|
{
|
|
return false;
|
|
}
|
|
if(glu.size_y < 100)
|
|
{
|
|
return false;
|
|
}
|
|
if((glu.size_x + glu.size_y + glu.size_z)<1.5)
|
|
{
|
|
return false;
|
|
}
|
|
if(glu.size_z>700)
|
|
{
|
|
return false;
|
|
}
|
|
if(glu.size_x>700)
|
|
{
|
|
return false;
|
|
}
|
|
if(( glu.size_x + glu.size_z) <4)
|
|
{
|
|
return false;
|
|
}
|
|
if( glu.size_x/glu.size_z> 3.0)
|
|
{
|
|
return false;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
|
|
// bi classification for distigushed the moving or static
|
|
void VeloScan::ClassifiAllObject()
|
|
{
|
|
int i,j;
|
|
int clustersize=scanClusterArray.size();
|
|
|
|
//Find moving Ojbects
|
|
for(i=0; i<clustersize; ++i)
|
|
{
|
|
clusterFeature &glu = scanClusterFeatureArray[i];
|
|
cluster &gluData=scanClusterArray[i];
|
|
|
|
if( FilterNOMovingObjcets(glu,gluData))
|
|
{
|
|
if(FindMovingObjcets(glu,gluData))
|
|
glu.clusterType =CLUSTER_TYPE_MOVING_OBJECT;
|
|
else
|
|
glu.clusterType =CLUSTER_TYPE_STATIC_OBJECT;
|
|
}
|
|
else
|
|
{
|
|
glu.clusterType =CLUSTER_TYPE_STATIC_OBJECT;
|
|
}
|
|
}
|
|
|
|
//Mark No Moving Ojbects CELLS
|
|
int k;
|
|
for(i=0; i<clustersize; ++i)
|
|
{
|
|
clusterFeature &glu = scanClusterFeatureArray[i];
|
|
if(glu.clusterType & CLUSTER_TYPE_MOVING_OBJECT)
|
|
{
|
|
cluster &gclu = scanClusterArray[i];
|
|
for(j =0; j< gclu.size() ; ++j)
|
|
{
|
|
cellFeature &gcF = *(gclu[j]);
|
|
gcF.cellType = CELL_TYPE_MOVING;
|
|
}
|
|
}
|
|
if(glu.clusterType & CLUSTER_TYPE_STATIC_OBJECT)
|
|
{
|
|
cluster &gclu = scanClusterArray[i];
|
|
for(j =0; j< gclu.size() ; ++j)
|
|
{
|
|
cellFeature &gcF = *(gclu[j]);
|
|
gcF.cellType = CELL_TYPE_STATIC;
|
|
}
|
|
}
|
|
|
|
|
|
}
|
|
}
|
|
|
|
void VeloScan::ClassifibyTrackingAllObject(int currentNO ,int windowsize )
|
|
{
|
|
trackMgr.ClassifiyTrackersObjects(Scan::allScans, currentNO, windowsize) ;
|
|
}
|
|
|
|
void VeloScan::MarkStaticorMovingPointCloud()
|
|
{
|
|
int i,j,k;
|
|
DataXYZ xyz(get("xyz"));
|
|
DataType Pt(get("type"));
|
|
|
|
int startofpoint = 0;
|
|
int colMax= scanCellFeatureArray.size();
|
|
for(i=0; i<colMax; ++i)
|
|
{
|
|
cellFeatureColumn &gFeatureCol = scanCellFeatureArray[i];
|
|
int rowMax= gFeatureCol.size();
|
|
for(j=0;j< rowMax; ++j)
|
|
{
|
|
cellFeature &gcellFreature = gFeatureCol[j];
|
|
startofpoint += gcellFreature.pCell->size();
|
|
cell &gCell =*( gcellFreature.pCell);
|
|
|
|
for( k=0; k< gcellFreature.pCell->size();++k)
|
|
{
|
|
// find Point in scan raw points by point_id;
|
|
Point p = *(gCell[k]);
|
|
if(gcellFreature.cellType & CELL_TYPE_STATIC)
|
|
Pt[p.point_id] = POINT_TYPE_STATIC_OBJECT;
|
|
if(gcellFreature.cellType & CELL_TYPE_MOVING)
|
|
Pt[p.point_id] = POINT_TYPE_MOVING_OBJECT;
|
|
if(gcellFreature.cellType & CELL_TYPE_GROUND)
|
|
Pt[p.point_id] = POINT_TYPE_GROUND;
|
|
}
|
|
|
|
}
|
|
}
|
|
}
|
|
|
|
void VeloScan::FindingAllofObject(int maxDist, int minDist)
|
|
{
|
|
TransferToCellArray(maxDist, minDist);
|
|
CalcScanCellFeature();
|
|
FindAndCalcScanClusterFeature();
|
|
|
|
return;
|
|
}
|
|
|
|
|
|
void VeloScan::TrackingAllofObject(int trackingAlgo)
|
|
{
|
|
trackMgr.HandleScan(*this,trackingAlgo);
|
|
}
|
|
|
|
void VeloScan::ClassifiAllofObject()
|
|
{
|
|
ClassifiAllObject();
|
|
}
|
|
|
|
void VeloScan::ExchangePointCloud()
|
|
{
|
|
MarkStaticorMovingPointCloud();
|
|
return;
|
|
}
|