Android的增强现实应用图像识别 [英] Image recognition for Android augmented reality app
问题描述
首先，对不起，华南简介我的英文不好。
First, sorry abour my poor english.
我打算建立一个增强现实应用程序的Android移动平台的主要特点是用户采取店铺的射门和应用承认，他拍摄店的能力。我不知道是不是最好的选择是使用图像识别API为许多现有的，但我认为这将是更具体的东西。也许自己图像的银行会有所帮助。
I'm planning to build an augmented reality app for android mobile platform and the main feature is the ability of the user to take a shoot of a shop and the application recognize the shop that he is photographing. I Do not know if the best option would be to use an image recognition api as many existing, but I think it would be something more specific. Maybe own a bank of images would help.
我的计划是具有存储一个数据库与它们的位置和使用的许多工具用于图像识别1和我的数据库中搜索到相同的位置。但我发现，所有的搜索引擎的图像（kooba，iqengines等）是不是免费的，没有便宜一点的。因此，将可能在商场使用有限的目录，例如商店的图像，例如和发送照片的智能手机（包括Android或iPhone）的工具。
My plan was to have a database of stores with their locations and use one of many tools for image recognition and search in my database to the same location. But I found that all search engines images (kooba, iqengines, etc.) are not free and not a little cheaper. So would a tool that could use a limited catalog, like shops images in a shopping mall for example and send photos of smartphones (both android or iphone).
有人可以帮助我开始？
推荐答案
我一直在做类似我的论文在大学的东西。我开发了检测路标的应用程序，阅读对他们的内容，那么个性化的/它取决于用户的preferences（成败参半）优先。
I've been doing something similar for my dissertation at University. I developed an application which detected signposts, read the content on them, then personalised / prioritised it depending on the user's preferences (with mixed success).
作为其中的一部分，我不得不考虑图像识别。
两件事情，你可能想看看是：
的高通公司QCAR SDK 。这是一个有点太形象具体是什么我后，但如果你是做在一个小范围内的商铺也可以正常工作。这将要求店形象的集合匹配 - 我不知道那将是多么成功的是
As part of this I had to look into Image Recognition.
Two things you may want to look at are:
The Qualcomm QCAR SDK. This was a little bit too image specific for what I was after, but if you were to do it on a small range of shops it may work. This would require a collection of shop images to match against - I don't know how successful it would be.
我实现了使用什么样的 JavaCV （一中的 OpenCV的），其中也有一个Android的转换。这似乎让图像识别多一点普遍高于previous选项，这就是为什么我用它。它需要你运行你自己的训练来创建一个分类，虽然（除非有做在它的图像识别的另一种方式）。但也有一些的指导可以帮助这一点。
我用它识别路标合理成功过只是一些基本训练，但往往没有认识到一些误报。
What I implemented used JavaCV (a conversion of OpenCV), which also has an Android conversion. It seems to allow for image recognition a bit more generally than the previous option which is why I used it. It would require you to run your own training to create a classifier though (unless there is another way of doing image recognition within it). But there are a number of guides which can help with that.
I used it for recognising signposts with reasonable success off just some basic training, though did tend to recognise a number of false positives.
在我的应用程序，然后使用的位置与previous检测等。
Within my application I then used location to match up with previous detections etc.
希望这些可以让你开始。
Hopefully these may get you started.
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