CamShift算法基于色值，适用于追踪颜色和背景差异较大的目标。
效果图
以下调试代码，仅供参考：
package com.kongqw;
import android.graphics.Bitmap;
import org.opencv.android.Utils;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.MatOfFloat;
import org.opencv.core.MatOfInt;
import org.opencv.core.Rect;
import org.opencv.core.RotatedRect;
import org.opencv.core.Scalar;
import org.opencv.core.TermCriteria;
import org.opencv.imgproc.Imgproc;
import org.opencv.video.Video;
import java.util.Collections;
import java.util.List;
import java.util.Vector;
/**
* Created by kongqingwei on 2017/4/26.
* ObjectTracker
*/
public abstract class ObjectTracker {
private Mat hsv, hue, mask, prob;
private Rect trackRect;
private RotatedRect rotatedRect;
private Mat hist;
private List<Mat> hsvList, hueList;
private Bitmap bitmap;
private MatOfFloat ranges;
public abstract void onCalcBackProject(Bitmap prob);
public ObjectTracker(Mat rgba) {
hist = new Mat();
trackRect = new Rect();
rotatedRect = new RotatedRect();
hsvList = new Vector<>();
hueList = new Vector<>();
hsv = new Mat(rgba.size(), CvType.CV_8UC3);
mask = new Mat(rgba.size(), CvType.CV_8UC1);
hue = new Mat(rgba.size(), CvType.CV_8UC1);
prob = new Mat(rgba.size(), CvType.CV_8UC1);
bitmap = Bitmap.createBitmap(prob.width(), prob.height(), Bitmap.Config.ARGB_8888);
ranges = new MatOfFloat(0f, 256f);
}
public Bitmap createTrackedObject(Mat mRgba, Rect region) {
//将rgb摄像头帧转化成hsv空间的
rgba2Hsv(mRgba);
updateHueImage();
Mat tempMask = mask.submat(region);
// MatOfFloat ranges = new MatOfFloat(0f, 256f);
MatOfInt histSize = new MatOfInt(25);
List<Mat> images = Collections.singletonList(hueList.get(0).submat(region));
Imgproc.calcHist(images, new MatOfInt(0), tempMask, hist, histSize, ranges);
Bitmap bitmap = Bitmap.createBitmap(hue.width(), hue.height(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(hue, bitmap);
// 将hist矩阵进行数组范围归一化，都归一化到0~255
Core.normalize(hist, hist, 0, 255, Core.NORM_MINMAX);
trackRect = region;
return bitmap;
}
private void rgba2Hsv(Mat rgba) {
Imgproc.cvtColor(rgba, hsv, Imgproc.COLOR_RGB2HSV);
//inRange函数的功能是检查输入数组每个元素大小是否在2个给定数值之间，可以有多通道,mask保存0通道的最小值，也就是h分量
//这里利用了hsv的3个通道，比较h,0~180,s,smin~256,v,min(vmin,vmax),max(vmin,vmax)。如果3个通道都在对应的范围内，则
//mask对应的那个点的值全为1(0xff)，否则为0(0x00).
int vMin = 65, vMax = 256, sMin = 55;
Core.inRange(
hsv,
new Scalar(0, sMin, Math.min(vMin, vMax)),
new Scalar(180, 256, Math.max(vMin, vMax)),
mask
);
}
private void updateHueImage() {
hsvList.clear();
hsvList.add(hsv);
// hue初始化为与hsv大小深度一样的矩阵，色调的度量是用角度表示的，红绿蓝之间相差120度，反色相差180度
hue.create(hsv.size(), hsv.depth());
hueList.clear();
hueList.add(hue);
MatOfInt from_to = new MatOfInt(0, 0);
// 将hsv第一个通道(也就是色调)的数复制到hue中，0索引数组
Core.mixChannels(hsvList, hueList, from_to);
}
public RotatedRect objectTracking(Mat mRgba) {
rgba2Hsv(mRgba);
updateHueImage();
// 计算直方图的反投影。
// Imgproc.calcBackProject(hueList, new MatOfInt(0), hist, prob, ranges, 255);
Imgproc.calcBackProject(hueList, new MatOfInt(0), hist, prob, ranges, 1.0);
// 计算两个数组的按位连接（dst = src1 & src2）计算两个数组或数组和标量的每个元素的逐位连接。
Core.bitwise_and(prob, mask, prob, new Mat());
// 追踪目标
rotatedRect = Video.CamShift(prob, trackRect, new TermCriteria(TermCriteria.EPS, 10, 1));
// 将本次最终到的目标作为下次追踪的对象
trackRect = rotatedRect.boundingRect();
rotatedRect.angle = -rotatedRect.angle;
Imgproc.rectangle(prob, trackRect.tl(), trackRect.br(), new Scalar(255, 255, 0, 255), 6);
Utils.matToBitmap(prob, bitmap);
onCalcBackProject(bitmap);
return rotatedRect;
}
}使用部分
public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
mRgba = inputFrame.rgba();
mGray = inputFrame.gray();
if (null == objectTracker) {
objectTracker = new ObjectTracker(mRgba) {
@Override
public void onCalcBackProject(final Bitmap prob) {
MainActivity.this.runOnUiThread(new Runnable() {
@Override
public void run() {
imageView.setImageBitmap(prob);
}
});
}
};
}
if (null != mTrackWindow) {
Log.i(TAG, "onCameraFrame: objectTracker = " + objectTracker + " mTrackWindow = " + mTrackWindow);
RotatedRect rotatedRect = objectTracker.objectTracking(mRgba);
Imgproc.ellipse(mRgba, rotatedRect, FACE_RECT_COLOR, 6);
Rect rect = rotatedRect.boundingRect();
Imgproc.rectangle(mRgba, rect.tl(), rect.br(), FACE_RECT_COLOR, 3);
}
// System.gc();
return mRgba;
}int xDown;
int yDown;
@Override
public boolean onTouch(View v, MotionEvent event) {
int cols = mRgba.cols();
int rows = mRgba.rows();
int xOffset = (mOpenCvCameraView.getWidth() - cols) / 2;
int yOffset = (mOpenCvCameraView.getHeight() - rows) / 2;
switch (event.getAction()) {
case MotionEvent.ACTION_DOWN:
xDown = (int) event.getX() - xOffset;
yDown = (int) event.getY() - yOffset;
break;
case MotionEvent.ACTION_UP:
int xUp = (int) event.getX() - xOffset;
int yUp = (int) event.getY() - yOffset;
// 获取跟踪目标
mTrackWindow = new Rect(Math.min(xDown, xUp), Math.min(yDown, yUp), Math.abs(xUp - xDown), Math.abs(yUp - yDown));
// 创建跟踪目标
Bitmap bitmap = objectTracker.createTrackedObject(mRgba, mTrackWindow);
imageView.setImageBitmap(bitmap);
Toast.makeText(getApplicationContext(), "已经选中跟踪目标！", Toast.LENGTH_SHORT).show();
break;
default:
break;
}
return true;
}参考