完整代码：https://github.com/YvanYan/image_processing/tree/master/object_tracking
流程：
1.读取视频，调整视频尺寸
2.更新追踪器，绘制目标区域
3.根据需要创建新的追踪目标
目前OpenCV已经实现了的追踪算法：
OPENCV_OBJECT_TRACKERS = {
"csrt": cv2.TrackerCSRT_create,
"kcf": cv2.TrackerKCF_create,
"boosting": cv2.TrackerBoosting_create,
"mil": cv2.TrackerMIL_create,
"tld": cv2.TrackerTLD_create,
"medianflow": cv2.TrackerMedianFlow_create,
"mosse": cv2.TrackerMOSSE_create
}
1.读取视频，调整视频尺寸
cap = cv2.VideoCapture('videos/soccer_01.mp4')
trackers = cv2.MultiTracker_create()
while (True):
frame = cap.read()[1]
if frame is None:
break
(h, w) = frame.shape[0:2]
width = 600
ratio = width / float(w)
height = int(h * ratio)
frame = cv2.resize(frame, (height, width), interpolation=cv2.INTER_AREA)
通过MultiTracker_create初始化追踪器集合。
2.更新追踪器，绘制目标区域
(success, boxs) = trackers.update(frame)
for box in boxs:
(x, y, w, h) = [int(v) for v in box]
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.imshow('frame', frame)
key = cv2.waitKey(100)
根据trackers.update返回的区域集，绘制不同的目标区域。
3.根据需要创建新的追踪目标
box = cv2.selectROI("frame", frame, fromCenter=False,
showCrosshair=True)
tracker = OPENCV_OBJECT_TRACKERS['kcf']()
trackers.add(tracker, frame, box)
使用selectROI创造矩形，然后创建kcf追踪器，将新的追踪器添加到追踪器集合中。
