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.
Related
I am working on a face recognition app where the picture is taken and sent to server for recognition.
I have to add a validation that user should capture picture of real person and of another picture. I have tried a feature of eye blink and in which the camera waits for eye blink and captures as soon as eye is blinked, but that is not working out because it detects as eye blink if mobile is shaken during capture.
Would like to ask for help here, is there any way that we can detect if user is capturing picture of another picture. Any ideas would help.
I am using react native to build both Android and iOS apps.
Thanks in advance.
Thanks for support.
I resolve it by the eye blink trick after all. Here is a little algorithm I used:
Open camera, click capture button:
Camera detects if any face is in the view and waits for eye blink.
If eye blink probability is 90% for both the eyes, wait 200 milliseconds. Detect face again with eye open probability > 90% to verify if the face is still there, and capture the picture at the end.
That's a cheap trick but working out so far.
Regards
On some iPhones (iOS 11.1 upwards), there's a so-called trueDepthCamera that's used for Face ID. With it (or the back facing dual camea system) you can capture images along with depth maps. You could exploit that feature to see if the face is flat (captured from an image) or has normal facial contours. See here...
One would have to come up with a 3d face model to fool that.
It's limited to only a few iPhone models though and I don't know about Android.
Are any of the current text capture APIs (e.g. Google's Text API) fast enough to capture text from a phone's video feed, and draw a box that stays on the text even as the camera moves?
I don't need fast enough to do full OCR per-frame (though that would be amazing!). I'm just looking for fast enough to recognize blocks of text and keep the bounding box displayed in sync with the live image.
There are two major options for good results. They are both C++ but there are wrappers. I've personally played with OpenCV for face recognition and the results were promising. Below links with small tutorials and demos.
OpenCV
Tessaract by Google
Firebase
onDeviceTextRecognizer is simple and working for me.
I'm building an Android app that has to identify, in realtime, a mark/pattern which will be on the four corners of a visiting card. I'm using a preview stream of the rear camera of the phone as input.
I want to overlay a small circle on the screen where the mark is present. This is similar to how reference dots will be shown on screen by a QR reader at the corner points of the QR code preview.
I'm aware about how to get the frames from camera using native Android SDK, but I have no clue about the processing which needs to be done and optimization for real time detection. I tried messing around with OpenCV and there seems to be a bit of lag in its preview frames.
So I'm trying to write a native algorithm usint raw pixel values from the frame. Is this advisable? The mark/pattern will always be the same in my case. Please guide me with the algorithm to use to find the pattern.
The below image shows my pattern along with some details (ratios) about the same (same as the one used in QR, but I'm having it at 4 corners instead of 3)
I think one approach is to find black and white pixels in the ratio mentioned below to detect the mark and find coordinates of its center, but I have no idea how to code it in Android. I looking forward for an optimized approach for real-time recognition and display.
Any help is much appreciated! Thanks
Detecting patterns on four corners of a visiting card:
Assuming background is white, you can simply try this method.
Needs to be done and optimization for real time detection:
Yes, you need OpenCV
Here is an example of real-time marker detection on Google Glass using OpenCV
In this example, image showing in tablet has delay (blutooth), Google Glass preview is much faster than that of tablet. But, still have lag.
I'm working on an application for sharing SurfaceView's draws with other android devices in real time (as a streaming). So all the connected devices on the net should be able to get the same canvas, draw in real time and see the modifications of each others.
I didn't found a way to do that. I thought about capturing screen shots and share them, but it will not allow multi-users modification.
How can I manage that? Is there an API or something like that?
I couldn't find from where to start.
I intend to work on a project, where I have to detect fingerprint from an image captured by android's camera.
I have no prior knowledge on fingerprint processing. Is there any open source library in android to accomplish the task? If not, then from which point can I have to start to gain adequate knowledge about fingerprint detection and processing?
I have not worked with image processing before. So there is so much to cover up, i can do that. But I want to know the exact starting point so that I don't have to circle around ...
Any links, papers or books related on this topic will be very convenient.
Thanks in advance!
How will the phone camera take an image like this? Fingerprints are acquired using specialized sensors.
If you're talking about getting fingerprint data from a normal photograph of a finger, I doubt you'll be able to distinguish between fingerprints accurately.