问题描述
我的项目是人脸验证。
系统说明：
System Description: My input is only one image (which was taken when the user logins for the first time) and using that image system should authenticate whenever the user logins to the application. The authentication images may differ from the first input image like -- different illumination conditions, different distance from camera and -10 to 10 degrees variation in pose. The camera used is same (ex: ipad) for all cases.
2）我需要从图像存储库中选择最接近的图像（和
不是所有存储的图像），并用于
验证以减少时间。 如何根据
照明/相机距离自动标记图片
2) When a new image comes, I need to select the closest image(s) (and not all stored images) from the image repository and use for authenticate to reduce the time. How to label an image based on illumination/distance from camera automatically??
3）如何使我的系统对于
照明和距离照相机的距离的变化$ dec $ $ <
3) How should I make my system to perform decently for changes in illumination and distance from camera??
请注意，任何人都可以建议我好alogirthm / papers / opensource-codes for我的上述问题？
Please, can anyone suggest me good alogirthm/papers/opensource-codes for my above questions??
虽然这听起来像一个研究项目，但如果我得到任何回应，我会非常感激。
Though it sounds like a research project, I would be extremely grateful if I get any response from someone.
推荐答案
对于这个任务，我想你应该看看的。 API基本上能够识别面部的结构（在当然的某些限制内），并为您提供面部可用的图像的坐标。
For this task I think you should take a look at OpenCV's Face Recognition API. The API is basically able to identify the structure of a face (within certain limitations of course) and provide you with the coordinates of the image within which the face is available.
在我看来，只有面对面的处理，减少了处理不同的背景颜色的需要，我认为这是你不真正需要的东西。
Having to deal with just the face in my opinion reduces the need to deal with different background colours which I think is something you do not really need.
一旦你有图像的脸，你可以缩放它向上/向下有一个统一的大小，也改变图像的颜色为灰度。最后，我会考虑将所有这些信息提供给，因为这些信息能够处理与输入不一致。这将允许您在每次用户登录时增加您的知识库。
Once you have the image of the face, you could scale it up/down to have a uniform size and also change the colour of the image to grey scale. Lastly, I would consider feeding all this information to an Artificial Neural Network since these are able to deal with inconsistencies with the input. This will allow you to increase your knowledge base each time a user logs in.
我确定还有其他方法可以解决这个问题。我们建议您查看，尝试查找处理此问题的论文，以获取更多信息可能的其他方式来实现你所追求的。另外，请记住，有些运气，你也可能找到一些开源项目已经做了你的大部分。
I'm pretty sure there are other ways to go around this. I would recommend taking a look at Google Scholar to try and find papers which deal with this matter for more information and quite possible other ways to achieve what you are after. Also, keep in mind that with some luck you might also find some open source project which already does most of what you are after.
这篇关于面部身份验证的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！