适用于AR android应用的3d对象识别 [英] 3d object recognition for AR android app

问题描述

我正在尝试开发AR android应用程序.
它应该检测并识别相机捕获的对象，为此，我正在使用OpenCV，但是我对AR领域中的移动设备的对象识别不是很熟悉.

I'm trying to develop an AR android application.
it should detect and recognize the object captured by the camera, I'm using OpenCV for this purpose, but I'm not very familiar with object recognition for mobile devices in the AR field.

我有两个问题:

1-哪种算法在精度和速度上更好(SIFT，SURF，FAST，ORB或其他)?

1- which algorithm is better (in the meaning of precision and speed) SIFT, SURF, FAST, ORB, or something else?

2-我想知道检测和跟踪过程是否会像这样:
拍摄相机帧，检测其关键点，计算其描述符，然后将其与数据库中可用的每张图像(描述符垫)进行匹配，以查找其所属的图像.
我觉得上述步骤在计算上会很繁琐，尤其是在每帧重复执行这些步骤以保持跟踪对象的情况下.

2- I wonder if the process of detecting and tracking would be something like this :
taking a camera frame, detect its key points, compute its descriptors then match it with each image(Mat of descriptors) available in the database to find which one it belongs to.
I feel that the mentioned steps will be computationally heavy and especially if they're repeated for each frame to keep tracking the object.

请向我提供一些最适合我目标的算法和步骤的详细信息.
预先感谢

please provide me with some details about the algorithm and the steps that best fit my goal.
Thanks in advance

推荐答案

我知道这是一个老问题，但我认为它将能够帮助其他人.

I know it is an old question but I feel it will be able to help others.

有一个很好的教程，该教程使用Android，OpenCV和OpenGL ES 3.0使用NDK与Android Studio一起构建小型AR应用程序. 它有很好的解释和一个Github仓库来检查代码.

There is this good tutorial which is using Android, OpenCV and OpenGL ES 3.0 to build a small AR app with Android studio using the NDK. It has good explainations and a Github repo to check the code.

http://www.anandmuralidhar.com/blog/android/simple- ar/

它使用ORB功能检测/匹配标记以在场景中生成3D对象. 关于第二点，本教程可以使您了解该过程的工作原理.

It uses ORB features to detect/match marker to spawn 3D object on the scene. About your second point, the tutorial can give you an idea of how the process can work.

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