从视频 Opencv Haar Cascade 获取前一帧

Question

我正在使用汽车级联来检测示例视频中的所有汽车。该程序目前正在它检测到的每辆汽车周围绘制矩形。但是，矩形在帧与帧之间不断变化。如果下一帧的新矩形与前一个矩形重叠，我想通过保留原始矩形来增加一些稳定性。为了实现这一点，我保存了前一帧（并从前一帧检测汽车）并将前一帧的矩形与当前帧进行比较。

 Mat frame;
Mat prevFrame;

while (capture.isOpened()) {
    capture.read(frame);
    vector<Rect> cars; // center of rectangles where each rectangle contains the detected object
    vector<Rect> prevCars; // to store previous tracked rectangles

    // Detects objects of different sizes in the input image. The detected objects are returned as a list of rectangles.
    car_cascade.detectMultiScale(frame, cars, 1.1, 2);

    if(!prevFrame.empty()) {
        car_cascade.detectMultiScale(prevFrame, prevCars, 1.1, 2);
    } else {
        cout << "EMPTY" << endl; // for testing
    }

    cout << "current : " << cars.size() << endl; // print out number of cars
    cout << "previous: " << prevCars.size() << endl; // print out number of cars


    // more code goes here which I haven't written here

    frame.copyTo(prevFrame); // set previous frame to current frame
    imshow("Video", frame);

    char key = waitKey(33);
    if (key == 'q')
    {
        break;
    }
}

但是，从前一帧检测到的汽车数量与前一帧不同。例如，

空 当前：3 上一个：0

Answer 1

为了跟踪和更新汽车的矩形，这是我要做的（类似 python 的代码）：

def getIndexOfCorrespondingTrackedCar(car) :
    for i in range(0, len(tracked_cars)) :
        if distance(car.center, tracked_cars[i].center) < THRESHOLD : // you will have to define a threshold according to your case. It has to be smaller than the speed of cars (in px/frame) though.
            return(i) // we found the corresponding car in the tracked_cars list
    return(-1) // we found no corresponding car, it must be a new car

tracked_cars = [] // list of tracked Rects
cars_current_frame = [] // list of Rects on the current frame

while(camera.open()) :

    cars_current_frame = getCarsInFrame(frame) // here you want to use your detectMultiScale function

    for ccf in cars_current_frame :
        car_idx = getIndexOfCorrespondingTrackedCar(ccf) // get the index of the corresponding car in tracked_cars list
        if car_idx is -1 : // No correspondance has been found, this is a new car
            tracked_cars.append(ccf)
        else :
            tracked_cars[car_idx] = ccf // we update the position of the tracked car with its new position

    deleteOutdatedCars(tracked_cars) // delete all the tracked cars that haven't been updated for a certain time (it most probably means that the car went off of the frame)

在我的示例中，我只使用了 Rect 列表，但在这里使用对象会更方便。我建议您使用以下成员变量创建一个 Car 类：

• 一个矩形来跟踪汽车的位置
• 上次更新的时间戳（删除“过时”汽车时需要该时间戳）
• 一个速度向量来近似下一帧上汽车的位置（可选）

我在手部跟踪系统中使用了类似的方法，效果很好。