I am working on an app in iOS that will occur an event if camera detects some changes in image or we can say motion in image. Here I am not asking about face recognition or a particular colored image motion, And I got all result for OpenCV when I searched, And I also found that we can achieve this by using gyroscope and accelerometer both , but how??
I am beginner in iOS.So my question is , Is there any framework or any easy way to detect motion or motion sensing by camera.And How to achieve?
For Example if I move my hand before camera then it will show some message or alert.
And plz give me some useful and easy to understand links about this.
Thanx
If all you want is some kind of crude motion detection, my open source GPUImage framework has a GPUImageMotionDetector within it.
This admittedly simple motion detector does frame-to-frame comparisons, based on a low-pass filter, and can identify the number of pixels that have changed between frames and the centroid of the changed area. It operates on live video and I know some people who've used it for motion activation of functions in their iOS applications.
Because it relies on pixel differences and not optical flow or feature matching, it can be prone to false positives and can't track discrete objects as they move in a frame. However, if all you need is basic motion sensing, this is pretty easy to drop into your application. Look at the FilterShowcase example to see how it works in practice.
I don't exactly understand what you mean here:
Here I am not asking about face recognition or a particular colored
image motion, because I got all result for OpenCV when I searched
But I would suggest to go for opencv as you can use opencv in IOS. Here is a good link which helps you to setup opencv in ios.
There are lot of opencv motion detection codes online and here is one among them, which you can make use of.
You need to convert the UIImage ( image type in IOS ) to cv::Mat or IplImage and pass it to the opencv algorithms. You can convert using this link or this.
Related
I am trying to differentiate between camera motion and tool motion in a surgical video.
I have tried optical flow using opencv farneback and pass the results to an ML model to learn but no success.a major issue is getting good keypoints in case of camera motion. Is there an alternate technique to distinguish between camera motion and tool/tissue movement? Note: camera motion happens only in 10% of the video
I wish I could add a comment (too new to be able to comment), as I don't have a good answer for you.
I think it really depends on the nature of the input image. Can you show some typical input images here?
What is your optical flow result look like? I thought you might get some reasonable results.
Have you tried some motion estimation method, to analyze if there is global movement across different frames, or there is only some local movements?
I'm creating motion detect app for ios. when camera on live any object passes the camera like person , animal. than i want detect motion feature. how's it possible?
I suggest you get familiar with the AVFoundation framework to understand how to get live video frames using the camera of an iOS device. A good starting point is Apple's famous sample AVCam, which should get you familiar with all the camera concepts.
As the next step, figure out how to do the movement detection. The simplest algorithm for that would be the background subtraction. The idea is to subtract two consecutive frames one from another. The areas without movement just cancel each other and become black, while the areas with movements show some nonzero values.
Here's an example of background subtraction in the OpenCV framework.
If in the end, you decide to use OpenCV (which is a classic Computer Vision framework which I definitely recommend), then you'll need to integrate OpenCV into your iOS app. You can see a short tutorial here.
I tried to show you some pointers which could get you going. The problem (how you presented it) is definitely not an easy one, so good luck!
Does anyone know how to reproduce the new Notes new scanning feature in iOS 11??
Is AVFoundation used for the camera?
How is the camera detecting the shape of the paper/document/card?
How do they place the overlay over in real time?
How does the camera know when to take the photo?
What's that animated overlay and how can we achieve this?
Does anyone know how to reproduce this?
Not exactly :P
Is AVFoundation used for the camera? Yes
How is the camera detecting the shape of the paper/document/card?
They are using the Vision Framework to do rectangle detection.
It's stated in this WWDC session by one of the demonstrators
How do they place the overlay over in real time?
You Should check out the above video for this as he talks about doing something similar in one of the demos
How does the camera know when to take the photo?
I'm not familiar with this app but it's surely triggered in the capture session, no?
Whats that animated overlay and how can we achieve this?
Not sure about this but I'd imagine it's some kind of CALayer with animation
Is Tesseract framework used for the image afterwards?
Isn't Tesseract OCR for text?
If you're looking for handwriting recognition, you might want to look for a MNIST model
Use Apple’s rectangle detection SDK, which provides an easy-to-use API that can identify rectangles in still images or video sequences in near-realtime. The algorithm works very well in simple scenes with a single prominent rectangle in a clean background, but is less accurate in more complicated scenes, such as capturing small receipts or business cards in cluttered backgrounds, which are essential use-cases for our scanning feature.
An image processor that identifies notable features (such as faces and barcodes) in a still image or video.
https://developer.apple.com/documentation/coreimage/cidetector
I am trying to create a Panorama app for iPhone/iPad.
The image stitching bit is OK, I'm using openCV libraries and the results are pretty acceptable.
But I'm a bit stuck on developing the UI for assisting the user while capturing the panorama.
Most apps (even on Android) would provide user with some sort of a marker that translates/rotates exactly matching the movement of the user's camera.
[I'm using the iOS 7 - default camera's panorama feature as a preliminary benchmark].
However, I'm way off the mark till date.
What I've tried:
I've tried using the accelerometer and gyro data for tracking the marker. With this approach -
I've applied an LPF on the accelerometer data and used simple
Newtonian mechanics (with a carefully tuned damping factor) to
translate the marker on the screen. Problem with this approach: very erratic data. Marker tends to jump and wobble between points. Hard to tell between smooth movement and jerk.
I've tried using a complimentary filter between LPF-ed gyro and
accelerometer data to translate the blob. Problem with this approach: Slightly better than the first approach, but still quite random.
I've also tried using image processing to compute optical flow. I'm
using openCV's
goodFeaturesToTrack(firstMat, cornersA, 30, 0.01, 30);
to get the trackable points from a first image (sampled from camera
picker) and then using calcOpticalFlowPyrLK to get the positions
of these points in the next image.
Problem with this approach: However, the motions vectors obtained from tracking these points are too noisy to compute the resultant
direction of motion accurately.
What I think I should do next:
Perhaps compute the DCT matrix from accelerometer and gyro data and
use some algorithm to filter one output with the other.
Work on the image processing algorithms, use some different techniques
(???).
Use Kalman filter to fuse the state prediction from
accelerometer+gyro with that of the image processing block.
The help that I need:
Can you suggest some easier way to get this job done?
If not, can you highlight any possible mistake in my approach? Does it really have to be this complicated?
Please help.
I would like some hints, maybe more, on detecting a custom image marker in a real-time video feed. I'm using OpenCV, iPhone and the camera feed.
By custom image marker I'm referring to a predefined image, but it can be any kind of image (not a specific designed marker). For example, it can be a picture of some skyscrapers.
I've already worked with ARTags and understand how they are detected, but how would I detect this custom image and especially find out its position & orientation?
What makes a good custom image to be detected successfully?
Thanks
The most popular markers used in AR are
AR markers (a simple form of QR codes) - those detected by AR tookit & others
QR codes. There are plenty of examples on how to create/detect/read QR.
Dot grids. Similar with the chess grids used in calibration. It seems their detection can be more robust than the classical chess grid. OpenCV has codes related to dot grid detection in the calibration part. Also, the OpenCV codebase offers a good starting point to extract 3D position and orientation.
Chess grids. Similar to dot grids. They were the standard calibration pattern, and some people used them for marker detection of a long time. But they lost their position to dot grids recently, when some people discovered that dots can be detected with better accuracy.
Note:
Grids are symmetrical. I bet you already know that. But that means you will not be able to
recover full orientation data from them. You will get the plane where the grid lies, but nothing more.
Final note:
Code and examples for the first two are easily found on the Internet. They are considered the best by many people. If you decide to use the grid patterns, you have to enjoy some math and image processing work :) And it will take more.
This answer is valid no more since Vuforia is now a paid engine.
I think you should give Vuforia a try. It's a AR engine that can use any image you want as a marker. What makes a good marker for Vuforia is high frequency images.
http://www.qualcomm.com/solutions/augmented-reality
Vuforia is a free to use engine.