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问题描述

目标:检测/确定人为操作,例如。拾取/提升物品以读取标签并将其保持在架子上(在商店中),坐在安装/爬升原子物体上。椅子,长凳,梯子等。



环境:商店/商店,相机(VGA - > 1MP),固定(即不是PTZ)。



限制:


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  1. 存在已知和未知的人类。

  2. 在一段时间内商店中可能重新排列对象(待售商品)。

  3. 随着时间的推移,照明可能发生变化。
    例如:商店的前面区域可能在白天获得充足的阳光,在夜间变为人工光。

  4. $ b


    1. 虽然我理解OpenCV是面部检测和面部识别的理想选择,但它可以用于分析动作坐着的行为,把物体抬起架子的行为?


    2. 由于商店中的摄像机大多在天花板高度,所以一般没有额外的面部视图,但大多是自上而下的视图。我理解Haar Cascade(PCA)不是很有用,但是需要其他方法。 3D头几何测定。是否有其他库(OpenCV除外)需要用于这样的任务?是否还有开源库?



    解决方案

    时间有些人来到这里,寻求帮助(或更好的,代码),以解决计算机视觉中的一些最困难的研究问题。没有被最广泛的学者和科学家解决的问题。有时,他们要求他们在SF电影中看到的算法。然后他们离开沮丧,因为OpenCV是不够友好。



    现在,认真的,如果你是一个博士的图像处理,处理一些天才项目,你不需要来自这里的建议。如果你不是,机会是真的很低。



    您可以使用合理的资源和精确度来追踪商店中的使用者:使用移动平均背景减法器(OpenCV中提供)来决定空白商店看起来像,并从每个帧中减去背景,看到来的对象和dissapear。您可以使用blob analisys lib提取它们。卡尔曼滤波器(或更简单的跟踪器)将帮助您跟踪移动的对象。



    祝你好运!


    Objective: Detect / determine human actions, s.a. picking / lifting items to read label and keeping it back on rack (in a store), sitting-on, mounting/climbing-atom objects s.a. chair, bench, ladder etc.

    Environment: Store / shop, which is mostly well lit. Cameras (VGA -> 1MP), fixed (i.e. not PTZ).

    Constraints:

    1. Presence of known and unknown human beings.
    2. Possible rearrangement of objects (items for sale) in the store, over a period of time.
    3. Possible changes in lighting over time. For example: Frontal areas of store might get ample sunlight during day, which changes to artificial light at night. Also, during night more lights can be switched-on.

    Question:

    1. While I understand that OpenCV is great for face-detection and usable for face-recognition, can it be used for analyzing "actions", s.a. the act of sitting, the act of lifting an object off the shelf ? If so, what are some of these algorithms I should dig deeper into ?

    2. Since cameras in stores are mostly at ceiling height, they generally do not have a frontal face view, but mostly a top-down view. I understand that Haar Cascade (PCA) isn't quite usable, but one needs other methods s.a. 3D Head geometry determination. Are there other libraries (other than OpenCV) which need to be used for such tasks ? Are there open-source libraries for the same ?

    解决方案

    From time to time some people come here and ask for help (or better, code) to solve some of the most difficult research problems in computer vision. Problems that were not solved by the most regarded academics and scientists. Sometimes, they ask for algorithms they've seen in SF movies. Then they leave frustrated, because OpenCV is "not friendly enough".

    Now, seriously, if you are a team of PhDs in image processing, working on some genius project, you don't need advice from here. And if you aren't, the chance to do it is really low.

    What you can do with reasonable resources and accuracy is to track people in the store: Use a moving-average background subtractor(available in OpenCV) to determine how the empty store looks like, and subtract that background from each frame, to see objects that come and dissapear. You can extract them with the blob analisys lib. A Kalman filter (or a simpler tracker) will help you keep track of the moving objects.

    Good luck!

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10-10 18:40