如何获取由体OpenCV生成的体的顶点

Question

我使用opencv和kinect进行身体跟踪和拘留。我使用下面的代码跟踪一个身体和生成一个数字。我的第一个想法是探测不同的区域，但后来我发现不同的位置可以有相同的面积。所以我想得到图形的顶点，来得到这些点之间的距离。或者你能为这个问题推荐什么？在

import cv2
import cv 
import numpy as np
from freenect import sync_get_depth as get_depth, sync_get_video as get_video
import subprocess
import time

def distancia(depth):

    depth = depth.sum()

    if depth > 280000000 and depth < 290000000:
        print 'Está dentro del rango'
        time.sleep(2)
        return True
    else:
        return False

def video(n):
    video = "parole /home/carlos/Vídeos/Webcam/" + n + ".webm"
    return_code = subprocess.call(video, shell=True)

def open_kinect():
    # Parte de Kinect
    (depth,_), (rgb,_) = get_depth(), get_video()
    d3 = np.dstack((depth,depth,depth)).astype(np.uint8)
    da = np.hstack((d3,rgb))
    img = np.array(da[::2,::2,::-1])
    #img2 = cv.fromarray()  
    return img, depth

def main():
    #cap = cv2.VideoCapture(0)

    while 1:
        #return_code = subprocess('parole /home/carlos/Vídeos/1.mp4', shell=True)

        #ret,img = cap.read()
        img, depth = open_kinect()
        gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
        blur = cv2.GaussianBlur(gray,(5,5),0)
        ret,thresh1 = cv2.threshold(blur,255,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)

        # Eliminacion de Fondo
        # noise removal
        kernel = np.ones((3,3),np.uint8)
        opening = cv2.morphologyEx(thresh1,cv2.MORPH_OPEN,kernel, iterations = 2)

        contours, hierarchy = cv2.findContours(thresh1,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
        drawing = np.zeros(img.shape,np.uint8)

        # sure background area
        sure_bg = cv2.dilate(opening,kernel,iterations=3)

        # Finding sure foreground area
        #dist_transform = cv2.distanceTransform(opening,cv2.DIST_L2,5)
        dist_transform = cv2.distanceTransform(opening,cv2.cv.CV_DIST_L2,5)
        ret, sure_fg = cv2.threshold(dist_transform,0.7*dist_transform.max(),255,0)

        # Finding unknown region
        sure_fg = np.uint8(sure_fg)
        unknown = cv2.subtract(sure_bg,sure_fg)
        # Termina eliminacion de fondo

        max_area=0

        for i in range(len(contours)):
            cnt=contours[i]
            area = cv2.contourArea(cnt)
            if(area>max_area):
                max_area=area
                ci=i

        cnt=contours[ci]
        hull = cv2.convexHull(cnt)
        moments = cv2.moments(cnt)


        if moments['m00']!=0:
            cx = int(moments['m10']/moments['m00']) # cx = M10/M00
            cy = int(moments['m01']/moments['m00']) # cy = M01/M00

        centr=(cx,cy)

        cv2.circle(img,centr,5,[0,0,255],2)
        cv2.drawContours(drawing,[cnt],0,(0,255,0),2)
        cv2.drawContours(drawing,[hull],0,(0,0,255),2)

        cnt = cv2.approxPolyDP(cnt,0.01*cv2.arcLength(cnt,True),True)
        hull = cv2.convexHull(cnt,returnPoints = False)

        try:
            defects = cv2.convexityDefects(cnt,hull)
            mind=0
            maxd=0
            for i in range(defects.shape[0]):
                s,e,f,d = defects[i,0]
                start = tuple(cnt[s][0])
                end = tuple(cnt[e][0])
                far = tuple(cnt[f][0])
                dist = cv2.pointPolygonTest(cnt,centr,True)
                cv2.line(img,start,end,[0,255,0],2)
                cv2.circle(img,far,5,[0,0,255],-1)

            print(i)
            i=0

            #Here i calculated the area of the different figures 
            time.sleep(1)
            if distancia(depth):
                print max_area

                if max_area > 17400 and max_area < 18000:
                    video("1")
                elif max_area > 18400 and max_area < 19000:
                    video("2")
                elif max_area > 23100 and max_area < 236000:
                    video("3")
                elif max_area > 20100 and max_area  < 20500:
                    video("4")
                elif max_area > 14000  and max_area < 14700:
                    video("5")

        except Exception as e:
            print 'Error', e
            #raw_input()

        cv2.imshow('output',drawing)
        cv2.imshow('Original',img)
        k = cv2.waitKey(10)
        if k == 27:
            break   

main()

这是我得到的一个例子 https://drive.google.com/file/d/0B6AAm-ulsq0VTFNJSVRXMEZVTVk/view

这个我想要什么 https://drive.google.com/file/d/0B6AAm-ulsq0VWm43RDJLaFd1aFE/view?usp=sharing