Image recognition for Android augmented reality app
First, sorry abour my poor english.
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.
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).
Can someone help me get started?
Answer
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).
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.
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.
Within my application I then used location to match up with previous detections etc.
Hopefully these may get you started.