我正在尝试从OpenNI中的depthMap()函数生成二进制图像,它提供了一个int类型的数组。有了那个图像,我想做blob-Tracking。 问题是我无法从depthMap生成清晰的二进制图像。在我的理解中,深度图像为距离传感器更近的所有物体产生了明亮的像素,而距离传感器越远,它们就越暗。所以我问(一维)数组中的每个像素是否超过我的最小值并且在我的最大阈值之下,以构成我想要获取数据的范围。 这是我的代码:
// import library
import SimpleOpenNI.*;
import processing.opengl.*; // opengl
import blobDetection.*; // blobs
// declare SimpleOpenNI object
SimpleOpenNI context;
BlobDetection theBlobDetection;
BlobBall blobBalls;
PrintWriter output;
// threshold for binaryImage
int minThreshold, maxThreshold;
// Size of the kinect Image
int kinectWidth = 640;
int kinectHeight = 480;
//
float globalX, globalY;
// Colors
color bgColor = color(0, 0, 123);
color white = color(255,255,255);
color black = color(0,0,0);
// PImage to hold incoming imagery
int[] distanceArray;
PImage cam, forBlobDetect;
void setup() {
output = createWriter("positions.txt");
// init threshold
minThreshold = 960;
maxThreshold = 2500;
// same as Kinect dimensions
size(kinectWidth, kinectHeight);
background(bgColor);
// initialize SimpleOpenNI object
context = new SimpleOpenNI(this);
if (context.isInit() == false) {
println("Can't init SimpleOpenNI, maybe the camera is not connected!");
exit();
}
else {
// mirror the image to be more intuitive
context.setMirror(true);
context.enableDepth();
// context.enableScene();
distanceArray = context.depthMap();
forBlobDetect = new PImage(width, height);
theBlobDetection = new BlobDetection(forBlobDetect.width, forBlobDetect.height);
theBlobDetection.setThreshold(0.2);
}
}
void draw() {
noStroke();
// update the SimpleOpenNI object
context.update();
// put the image into a PImage
cam = context.depthImage();
// copy the image into the smaller blob image
// forBlobDetect.copy(cam, 0, 0, cam.width, cam.height, 0, 0, forBlobDetect.width, forBlobDetect.height);
// blur the blob image
forBlobDetect.filter(BLUR, 2);
//
int pos = 0;
int currentDepthValue = 0;
distanceArray = context.depthMap();
for(int x = 0; x < cam.width; x++) {
for(int y = 0; y < cam.height; y++) {
pos = y*cam.width+x;
currentDepthValue = distanceArray[pos];
// println(currentDepthValue);
if((currentDepthValue > minThreshold) && (currentDepthValue < maxThreshold)) {
forBlobDetect.pixels[pos] = black;
} else {
forBlobDetect.pixels[pos] = white;
}
}
}
// for(int i=0; i < distanceArray.length; i++) {
// currentDepthValue = distanceArray[i];
// // println(currentDepthValue);
// if(currentDepthValue > minThreshold) /*&& (currentDepthValue < maxThreshold)*/) {
// forBlobDetect.pixels[pos] = white;
// } else {
// forBlobDetect.pixels[pos] = black;
// }
// }
// detect the blobs
theBlobDetection.computeBlobs(forBlobDetect.pixels);
// display the image
image(cam, 0, 0);
image(forBlobDetect, 0, 0, width/2, height/2);
// image(context.sceneImage(), context.depthWidth(), 0);
}
答案 0 :(得分:0)
我自己真的很愚蠢,因为我误解了11位阵列。 感谢“看到事情”的例子我解决了它。 https://github.com/atduskgreg/Making-Things-See-Examples/tree/master/ax02_depth_range_limit