KLT跟踪器在CCTV的人类跟踪 [英] KLT Tracker for human tracking in CCTV
问题描述
我想在CCTV影片中使用KLT追踪器进行追踪。人们非常接近中央电视台。我注意到有些时候人们改变头部的方向，并且帧速率稍慢。我从Rodrigues等人读到第3.4节：
I am trying to use a KLT tracker for human tracking in a CCTV footage. The people are very close to the CCTV. I noticed that some time people change the orientation of the heads and also the frame rate is slightly slow. I have read from Rodrigues et al. paper Section 3.4 that the:
这个简单的程序（KLT跟踪程序）是非常鲁棒的，并且可以建立头部检测之间的匹配，其中头部不连续检测到连续检测由于人群中的其他成员的姿势变化或部分闭塞。
"This simple procedure (KLT tracking procedure) is extremely robust and can establish matches between head detections where the head HAS NOT BEEN continuously detected continuously detected due to pose variation or partial occlusions due to other members of the crowd".
可以在此链接中找到纸张： Rodriguez et al。
Paper can be found in this link : Rodriguez et al.
1）。我理解KLT跟踪器是稳健的，以造成变化和遮挡。我是对的吗？
1). I understood that the KLT tracker is robust to pose variations and occlusions. Am I right?
我试图通过使用MATLAB KLT来跟踪一个人直到现在为止：
I was trying to track one single person in footage till now by using the MATLAB KLT as in :
但是，这些点在JUST 3帧后找不到。
However, the points were not being found after JUST 3 frames.
2）。有人可以解释为什么这种情况发生或更好的解决方案。也许使用粒子/卡尔曼滤波器应该更好？
2). Can someone explain why this is happening or else a better solution to this. Maybe using a particle/Kalman filter should be better?
推荐答案
我不建议使用KLT跟踪器来关闭闭路电视摄像机，以下原因：
1. CCTV帧速率通常较低，因此人们在帧之间显着改变它们的外观
2.由于相机靠近人，它们也由于透视而随时间改变其外观效果（例如，当人远离相机时可以看到脸部，但是当他/她靠近时，只有头部的顶部被看见）。
3.由于亲密，人们还会显着改变比例和长宽比，这对一些头部检测器来说是一个挑战。
I do not recommend using a KLT tracker for close CCTV cameras due to the following reasons: 1. CCTV frame rate is typically low, so people change their appearance significantly between frames 2. Since the camera is close to the people, they also change their appearance over time due to perspective effects (e.g. face can be seen when person is far from camera, but as he/she gets closer, only the top of the head is seen). 3. Due to closeness, people also significantly change scale and aspect ratio, which is a challenge for some head detectors.
KLT只有在邻居的像素，包括前景和背景，保持类似。上述属性使得大多数像素的可能性降低。我只能推荐KLT作为附加的基于运动的跟踪提示，作为部分运动场的向量。
KLT only works well when the neighborhood of the pixel, including both foreground and background, remains similar. The above properties make this less likely for most pixels. I can only recommend KLT as an additional motion based hint for tracking, as a vector of field of part motions.
大多数单人跟踪器不适应规模变化。我建议你从一些最先进的跟踪器开始，像Struck（C ++代码由Sam Hare提供这里），并修改搜索程序以使用比例更改。
Most single person trackers do not adapt well to scale change. I suggest you start with some state of the art tracker, like Struck (C++ code by Sam Hare available here), and modify the search routine to work with scale change.
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