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Facial expressions identification like snapchat

I am working on app that detect eye blink of the user. I have been searching the web for 2 days but still don't have clear vision about how this can be done.
As far as i have knew is that the system supports face detection which is detecting if there is a face in the picture and locating it.
But this works only with images and detect only faces which is not what i need. I need to open an camera activity and directly detect the face of the user and locate his eyes and other facial parts and wait till he blinks, like when you long click on the screen on snap chat.
I have seen a lot about open-cv but still not sure what it is or how to use it or if it seize my goals.
Note: snap chat has no API released for the technology used, and even it doesn't let anyone to talk to the engineers behind this technology.

I know that openCV has the ability to allow image processing on the device's camera feed (as opposed to only being able to process still images).
Here is an introductory tutorial on eye detection using openCV:
http://romanhosek.cz/android-eye-detection-and-tracking-with-opencv/
If you can't find eye-blink detection tutorials in a google search, I think you'll have to create the code for eye-blink detection on your own, but I think openCV will be a helpful tool in doing so. There are lots of beginner openCV tutorials to help you get started.

Detecting pathways in a video using BoofCV on Android

For my application I have been looking into using BoofCV to detect if I am on a pathway or not. The pathway is just gravel so it is the color of a standard roadway. I'm not sure exactly what image processing technique to use. The BoofCV demo app has a lot of features, but I would like to know which one is appropriate for what I'm trying to do.
Ultimately I'd like to have a toast appear on the screen when I am on a pathway.

From your question, I'm guessing that you' re using a regular camera, as real time input from a moving object. In that case you may need to:
Calibrate and Stabilize your input frames (since your pathway is made from gravel). BoofCV provides libraries.
Adjust exposure, contrast or brightness (for night/low light vision cameras or low contrast frames).
Use BoofCV's Binary Image Ops, according to your app's needs (Image Thresholding, Binary Labeling etc).
Use a classifier for 2 classes ("inside pathway", "outside pathway").
Process your output and feedback results to your "decision operator", to make a choice and guide your moving object.
More details about your project may help for a better answer.

Image processing in Android

I'm beginner in android.
I’m working on a project that I'm supposed to convert smart phone movement into mouse movement via smart phone camera with android. The smart phone moves on a checkboard surface and the movement information is sent to computer by Bluetooth. Should I use image processing techniques to do that? Has anyone have a relative experience or a similar code to help me out?

If I understand correctly image processing would be a good way to go to discover movement on a 2d plane. The checkerboard pattern should make for relatively easy pixel image comparison.

You could implement this using object detection in simple way.
But for your method you will need to implement optical flow analysis algorithm.
Optical mice internally uses the similar technique called Digital image correlation, it captures the video frames contentiously and compares consecutive frames to detect the motion.
You should read about optical flow detection techniques on Wikipedia.
& this slide

how can i set the camera function that anti-shake(image Stabilizer) at android

I've made a Camera App.
I want to add the functionality of anti-shake.
But I could not find the setting for anti-shake(image Stabilizer).
Plz Help me!!

Usually Image Stabilizer is a built-in camera feature, while OIS (Optical-Image-Stabilization) is a built-in hardware feature; by now really few devices support them.
If device hasn't a built-in feature, i think you cannot do anything.
Android doesn't provide a direct API to manage image stabilization, but you may try:
if android.hardware.Camera.getParameters().getSupportedSceneModes(); contains steadyphoto keyword (see here), your device supports a kind of stabilization (usually it shots when accelerometer data indicates a "stable" situation)
check android.hardware.Camera.getParameters().flatten(); for a "OIS" or "image-stabilizer" keyword/values or similar to use in Parameters.set(key, value);. For the Samsung Galaxy Camera you should use parameters.set("image-stabilizer", "ois");//can be "ois" or "off"
if you are really boring you may try reading the accelerometer data and decide to shot when the device looks steady.
Good luck.

If you want to develop software image stabilizer, OpenCV is helpful library for you. Following is the one of the way to stabilize the image using Feature.
At first, you should extract feature from image using feature extractor like SIFT, SURF algorithm. In my case, FAST+ORB algorithm is best. If you want more information, See this paper
After you get the features in images, you should find matching features with images.there are several matcher but Bruteforce matcher is not bad. If Bruteforce is slow in your system, you should use a algorithm like KD-Tree.
Last, you should get geometric transformation matrix which is minimize error of transformed points. You can use RANSAC algorithm in this process.
You can develop all this process using OpenCV and I already developed it in mobile devices. See this repository

Fingerprint Scanner using Camera [closed]

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Working on fingerprint scanner using camera or without, its possibility and its success rate?, I came across one of open source SDK named FingerJetFX its provide feasibilty with android too.
The FingerJetFX OSE fingerprint feature extractor is platform-independent and can be built
for, with appropriate changes to the make files, and run in environments with or without
operating systems, including
Linux
Android
Windows
Windows CE
various RTOSs
but I'm not sure whether Fingerprint scanner possible or not, I download the SDK and digging but no luck, even didn't found any steps to integrate the SDK, so having few of question which listed below:
I'm looking for suggestion and guidance:
Fingerprint scanner can be possible in android using camera or without camera?
With the help of FingerJetFX can I achieve my goal?
If 2nd answer is yes, then can someone provide me any sort of steps to integrate SDK in android?
Your suggestion are appreciable.

Android Camera Based Solutions:
As someone who's done significant research on this exact problem, I can tell you it's difficult to get a suitable image for templating (feature extraction) using a stock camera found on any current Android device. The main debilitating issue is achieving significant contrast between the finger's ridges and valleys. Commercial optical fingerprint scanners (which you are attempting to mimic) typically achieve the necessary contrast through frustrated total internal reflection in a prism.
In this case, light from the ridges contacting the prism are transmitted to the CMOS sensor while light from the valleys are not. You're simply not going to reliably get the same kind of results from an Android camera, but that doesn't mean you can't get something useable under ideal conditions.
I took the image on the left with a commercial optical fingerprint scanner (Futronics FS80) and the right with a normal camera (15MP Cannon DSLR). After cropping, inverting (to match the other scanner's convention), contrasting, etc the camera image, we got the following results.
The low contrast of the camera image is apparent.
But the software is able to accurately determine the ridge flow.
And we end up finding a decent number of matching minutia (marked with red circles.)
Here's the bad news. Taking these types of up close shots of the tip of a finger is difficult. I used a DSLR with a flash to achieve these results. Additionally most fingerprint matching algorithms are not scale invariant. So if the finger is farther away from the camera on a subsequent "scan", it may not match the original.
The software package I used for the visualizations is the excellent and BSD licensed SourceAFIS. No corporate "open source version"/ "paid version" shenanigans either although it's currently only ported to C# and Java (limited).
Non Camera Based Solutions:
For the frightening small number of devices that have hardware that support "USB Host Mode" you can write a custom driver to integrate a fingerprint scanner with Android. I'll be honest, for the two models I've done this for it was a huge pain. I accomplished it by using wireshark to sniff USB packets between the scanner and a linux box that had a working driver and then writing an Android driver based on the sniffed commands.
Cross Compiling FingerJetFX
Once you have worked out a solution for image acquisition (both potential solutions have their drawbacks) you can start to worry about getting FingerJetFX running on Android. First you'll use their SDK to write a self contained C++ program that takes an image and turns it into a template. After that you really have two options.
Compile it to a library and use JNI to interface with it.
Compile it to an executable and let your Android program call it as a subprocess.
For either you'll need the NDK. I've never used JNI so I'll defer to the wisdom of others on how best us it. I always tend to choose route #2. For this application I think it's appropriate since you're only really calling the native code to do one thing, template your image. Once you've got your native program running and cross compiled you can use the answer to this question to package it with your android app and call it from your Android code.

Tthere are a couple immediate hurdles:
Obtaining a good image of the fingerprint will be critical. According to their site, fingerjet expects standard fingerprint images - e.g. 8-bit greyscale (high contrast), flattened fingerprint images. If you took fingerprint pictures with the camera, the user would need to have a flat transparent surface (glass) you could flatten the fingerprints onto in order to take the picture. Your app would then locate the fingerprint in the image, transform it into a format acceptable for fingerjet. A library like OpenCV would help do this.
FingerJetFX OSE does not appear to offer canned android support - you will have to compile the library for android and use it via JNI/NDK.
From there, fingerjet should provide you with a compact representation of the print you can use for matching.
It would be feasible, but the usage requirement (need for the user to have a flat transparent surface available) might be a deal breaker...