This app uses the BackgroundSubtractorMOG algorithm from OpenCV's android library to identify objects in motion from the camera and draws a red overlay around/over them. The ideal is to have nice contours drawn around the objects that are moving. A slider is also added for the user to adjust the learning rate, which may or may not have any effect on the contours.
In order to utilize the app, the latest version of OpenCV Manager (also found on Google Play) must be downloaded and installed correctly. This app has been successfully tested on Android 2.3.4 and Android 4.3.
At the moment this can considered an initial tech demo, please feel free to play around with it. The source code for this implementation can also be found in github link below!
This app compares the reference image to the images in the added list. It uses ORB feature detector with BRIEF descriptor extractors. It uses BRUTEFORCE_HAMMING method to match the descriptors. Also, based on preference, app can also check the homography of the matched keypoints with LMED (least of median squares) and remove the outliners to give a better result.
How to use:
1 - Move the vision wherever you want, take pics along the way by using ADD button.
2 - You can also take a reference picture, that you want to be recognized. When you click it, it will be shown on the right of the camera view.
3 - When you are done, and make sure you have added images and have a reference image, click the Find Match button. It will calculate the keypoints of each image and the reference image and apply the matching algorithm.
4 - After matching and comparing, it will show the best match among all matches.
5 - You can also use Homography Off/On switch to provide more accurate results.
6 - Also, you can use Images only/with matches switch to show which keypoints are matched. REMEMBER, you have to click find match again to see the effect of Homography and Matches switch.
This app is still in development, actually being used by another project but I put it on for cool demonstration!
Source code available: https://github.com/mustafaakin/image-matcher
Modes currently supported:
-HDR Capture & Tonemapping
-Neon Gradient Edges
ViewerCV is simply an *open source* demo app for fun...
!! There is no point to it !!
REQUIRES HARDWARE MENU BUTTON
(or long-press the app switcher button for menu)
More details at:
[ SEO: real-time, viewer, camera, live, computer vision, opencv ]
HowTo (Button info):
-'Menu' changes effect
-'Mode' cycles options for that effect
-'Menu>Settings' adjust resolution
You want to have Face Recognition function in application, but it too hard to implement or you can not afford?
Face Recognition SDK will help you solve these problem in few minutes.
Face Recognition SDK provide API, algorithm, basic screen to recognize the face . By use Face Recognition SDK will help you add Face Recognition function to your application quickly.
Face Recognition SDK include:
● API for face recognition based on Java Code. You don't need to understand about C/C++, OpenCV.
● Provide basic screen : Training Screen, Face Recognition Screen, Setting Screen.
● Allow you customize code, basic screen because we implement as Android Library.
● Face Recognition SDK based on OpenCV (http://opencv.org/)
● Support multi laguages: English – VietNamese - Japanese
Site to download source code of Face Recognition SDK:
For more information and feature request contact me on www.iisy.net
Project Website: http://boofcv.org
For instructions and a more detailed explanation:
Full source code:
Load scaled pictures
Color plane extraction - RGB, HSV, HSL, XYZ, YCrCb
Binary convolution functions like Dilate, Erode, etc
Save post-processed pictures
Simple edge detection should be fluent for everybody but face detection need more processing power.
Use Neon for colorspace transformation
Face detection optimization is done thanks to Bill Mc Cord
With CraftAR service you can craft your own Augmented Reality experiences by linking real world objects (like magazines or products) to websites, videos, or 3D models.
You can use the app right away by pointing at any of the demos provided by Catchoom.
How does the app work?
Point to an object in Catchoom's demo collection or one of your collections. Whatever experience you have previously crafted will pop-up from the object you point at.
· Image recognition of real world objects.
· Collection-specific matching.
· Open website related to matched item.
· Open AR experience related to matched item.
· Switch between Single Shot Mode (one picture) and Finder Mode (continuously scanning).
· View API Responses instead of the interactive content.
How to use the app with items in your own collection
Note that to use your own collections and items (objects that become interactive) you'll need to create an account at Catchoom's CraftAR service. You can start with a Free Trial.
1. Type in the 'token' corresponding to the collection you want to match against. This token is a unique string associated to one of your collections.
2. Take a picture with the camera.
3. The request will automatically be sent to CraftAR's Cloud Image Recognition Service.
4. With the response, an Augmented Reality experience will start or the API results will be shown in a table.
The Enabler takes care of a lot of boilerplate code, so your app's code can be simpler. It also includes a basic GUI for most functionality of the Android library.
The Enabler also has views that allow you to:
- Display all received simple vehicle messages from the VI.
- Display all received low-level CAN messages from the VI, if that functionality is enabled in the firmware.
- Send an arbitrary CAN message to the vehicle through the VI (requires firmware that supports this feature).
- Send a diagnostic request to the vehicle through the VI.
More information on getting started with OpenXC on Android is available at http://openxcplatform.com
This app sends crash reporting data to Bugsnag for the purposes of assisting the OpenXC maintainers with debugging. If you do not wish to have your crashes reported, please compile the app from the sources.
The source code for the OpenXC Enabler is available at https://github.com/openxc/openxc-android and is provided under the BSD license.
Detects 24 different languages. May fail for very short messages!
Supported languages are:
To all developers. Cheers :)
OpenCV library is used by other applications for image enhancement, panorama stitching, object detection and recognition, etc. OpenCV Manager provides the best version of the OpenCV for your hardware. It also receives the latest stability and performance updates for the library.