To segment "simple" objects in a RGB-D Scene.

Relevant publications

How to run the executable?

> ./segmentObjs testScene.png 




Edit configParams.txt to set the unit vector along the normal to the horizontal surface. If the orientation of the camera does not change, the unit vector does not have to be recomputed.

How to read the xml file?

Use the matlab function readCCFrmXML.m given with the executable.


The extracted closed contours for the scene shown in the left image are shown in the right image below.

rgbdScene rgbdSceneSegments

What is in .xyz file?

A text file containing 3D co-ordinates corresponding to each pixel in the 2D image. Each row contains the (x,y,z) co-ordinate of a single pixel. The pixels are scanned along the row first.

Below is an example of a .xyz file wherein x_{r,c} is the x-coordinate of the pixel at row r and col c in the 2D image (M rows, N Cols.)

x_{0,0}  	y_{0,0}		z_{0,0}
.     		.		.
.     		.		.
x_{0,N-1}	y_{0,N-1}	z_{0,N-1}
.     		.		.
.     		.		.
x_{M-1,0}  	y_{M-1,0} 	z_{M-1,0}
.     		.		.
.     		.		.
x_{M-1,N-1}	y_{M-1,N-1}	z_{M-1,N-1}

How do compute the unit vector along the normal to the horizontal surface?

Refer to calcUnitVertical.cpp
You just have to select a point on a horizontal surface in the scene and the program computes the unit vector along its normal.

How to capture the color image and 3D point cloud of a scene using Kinect?

One way to do that is using openni_camera in ROS (Robot Operating System).
After installing the drivers, create a ros package and use the source file given below to capture both the color image and the registered 3D point cloud.

#include "ros/ros.h"
#include "rosbag/bag.h"
#include <cv_bridge/CvBridge.h>
#include <opencv2/highgui/highgui.hpp>
#include rosbag/view.h"
#include "rosbag/query.h"
#include "rosbag/message_instance.h"
#include <boost/foreach.hpp>
#include <cstring>
#include <vector>
#include <iostream>
#include <fstream>
#include <pcl/io/pcd_io.h>
#include <pcl/ros/conversions.h>
#include <pcl_ros/point_cloud.h>
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>

typedef pcl::PointCloud<pcl::PointXYZRGB> Cloud_t;

void callBackFn(const sensor_msgs::ImageConstPtr& imgColorPtr){
	sensor_msgs::CvBridge bridge;
	IplImage* imgColor = bridge.imgMsgToCv(imgColorPtr, "bgr8");
	cvNamedWindow("image",1); cvShowImage("image", imgColor);

int imgCount = 0;
void callBackReadPtCloud(const Cloud_t::ConstPtr pts2){
 	if (pts2 != NULL){
		Cloud_t cloud = *pts2;
		int width  = cloud.width;
		int height = cloud.height;
		IplImage* img =cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 3);
		ofstream file3D;
		char fileNamePts[100];
		sprintf(fileNamePts,"",imgCount);, ios::out); 
	  	for(int i=0; i < height; i++){
			unsigned char* imgPtr = (unsigned char*)(img->imageData + i*img->widthStep);
			for(int j=0; j < width; j++){
				unsigned char* rgb_ptr 	     = (unsigned char*)&(cloud.points[i*width+j].rgb);
				*(imgPtr+j*3) =  (*(rgb_ptr+0));
				*(imgPtr+j*3+1) =  (*(rgb_ptr+1));
				*(imgPtr+j*3+2) =  (*(rgb_ptr+2));	
				//write the xyz values into a file!
				file3D << cloud.points[i*width+j].x << 
					"  " << cloud.points[i*width+j].y << 
					" " << cloud.points[i*width+j].z <<"\n";
		char fileNameImg[100];
		cvNamedWindow("image",1); cvShowImage("image",img); 

int main(int argc, char* argv[]){
	ros::init(argc, argv, "listener"); 
	ros::NodeHandle n;
	ros::Subscriber sub = n.subscribe("/camera/rgb/points", 1, callBackReadPtCloud);	
	return 0;