调整OpenCV HOG方法，使用热像仪

Question

我正在使用OpenCV中的以下示例（opencv-2.4.11 / samples / python2 / peopledetect.py）来检测行人。

#!/usr/bin/env python

import numpy as np
import cv2

help_message = '''
USAGE: peopledetect.py <image_names> ...

Press any key to continue, ESC to stop.
'''

def inside(r, q):
    rx, ry, rw, rh = r
    qx, qy, qw, qh = q
    return rx > qx and ry > qy and rx + rw < qx + qw and ry + rh < qy + qh

def draw_detections(img, rects, thickness = 1):
    for x, y, w, h in rects:
        # the HOG detector returns slightly larger rectangles than the real objects.
        # so we slightly shrink the rectangles to get a nicer output.
        pad_w, pad_h = int(0.15*w), int(0.05*h)
        cv2.rectangle(img, (x+pad_w, y+pad_h), (x+w-pad_w, y+h-pad_h), (0, 255, 0), thickness)


if __name__ == '__main__':
    import sys
    from glob import glob
    import itertools as it

    print help_message

    hog = cv2.HOGDescriptor()
    hog.setSVMDetector( cv2.HOGDescriptor_getDefaultPeopleDetector() )

    for fn in it.chain(*map(glob, sys.argv[1:])):
        print fn, ' - ',
        try:
            img = cv2.imread(fn)
        except:
            print 'loading error'
            continue

        found, w = hog.detectMultiScale(img, winStride=(8,8), padding=(32,32), scale=1.05)
        found_filtered = []
        for ri, r in enumerate(found):
            for qi, q in enumerate(found):
                if ri != qi and inside(r, q):
                    break
            else:
                found_filtered.append(r)
        draw_detections(img, found)
        draw_detections(img, found_filtered, 3)
        print '%d (%d) found' % (len(found_filtered), len(found))
        cv2.imshow('img', img)
        ch = 0xFF & cv2.waitKey()
        if ch == 27:
            break
    cv2.destroyAllWindows()

不幸的是，检测结果似乎不稳定，因为在某些帧上检测到行人并且没有检测到与第一个帧非常相似的其他帧，如下所示。

我的问题

1. 我可以使用OpenCV的HOG实现来检测从热像仪捕获的帧上的行人吗？
2. 如果是，如何调整OpenCV的peopledetect.py示例以获得更好的结果？
3. 否则，请告诉我您使用OpenCV进行行人检测方法的预处理方法或其他指示的建议。

谢谢你们！