Hi,
Just a quicky about OpenCV and Windows Presentation Framework interoperability. It’s really easy with a simple Managed C++ wrapper. What I’ll show is how to transfer an OpenCV cv::Mat into WPF’s BitmapSource. Let’s see how it’s done.
Author: Roy
Hi,
I’ll present a quick and simple implementation of image recoloring, in fact more like color transfer between images, using OpenCV in C++ environment. The basis of the algorithm is learning the source color distribution with a GMM using EM, and then applying changes to the target color distribution. It’s fairly easy to implement with OpenCV, as all the “tools” are built in.
I was inspired by Lior Shapira’s work that was presented in Eurographics 09 about image appearance manipulation, and a work about recoloring for the colorblind by Huang et al presented at ICASSP 09. Both works deal with color manipulation using Gaussian Mixture Models.
Update 5/28/2015: Adrien contributed code that works with OpenCV v3! Thanks! https://gist.github.com/adriweb/815c1ac34a0929292db7
Let’s see how it’s done!
ICP – Iterative closest point, is a very trivial algorithm for matching object templates to noisy data. It’s also super easy to program, so it’s good material for a tutorial. The goal is to take a known set of points (usually defining a curve or object exterior) and register it, as good as possible, to a set of other points, usually a larger and noisy set in which we would like to find the object. The basic algorithm is described very briefly in wikipedia, but there are a ton of papers on the subject.
I’ll take you through the steps of programming it with OpenCV.
This is a tutorial on using Graph-Cuts and Gaussian-Mixture-Models for image segmentation with OpenCV in C++ environment.
Update 10/30/2017: See a new implementation of this method using OpenCV-Python, PyMaxflow, SLIC superpixels, Delaunay and other tricks.
Been wokring on my masters thesis for a while now, and the path of my work came across image segmentation. Naturally I became interested in Max-Flow Graph Cuts algorithms, being the “hottest fish in the fish-market” right now if the fish market was the image segmentation scene.
So I went looking for a CPP implementation of graphcut, only to find out that OpenCV already implemented it in v2.0 as part of their GrabCut impl. But I wanted to explore a bit, so I found this implementation by Olga Vexler, which is build upon Kolmogorov’s framework for max-flow algorithms. I was also inspired by Shai Bagon’s usage example of this implementation for Matlab.
Let’s jump in…
Update: check out my new post about this https://www.morethantechnical.com/2012/10/17/head-pose-estimation-with-opencv-opengl-revisited-w-code/
Hi
Just wanted to share a small thing I did with OpenCV – Head Pose Estimation (sometimes known as Gaze Direction Estimation). Many people try to achieve this and there are a ton of papers covering it, including a recent overview of almost all known methods.
I implemented a very quick & dirty solution based on OpenCV’s internal methods that produced surprising results (I expected it to fail), so I decided to share. It is based on 3D-2D point correspondence and then fitting of the points to the 3D model. OpenCV provides a magical method – solvePnP – that does this, given some calibration parameters that I completely disregarded.
Here’s how it’s done
Hi
Been working hard at a project for school the past month, implementing one of the more interesting works I’ve seen in the AR arena: Parallel Tracking and Mapping (PTAM) [PDF]. This is a work by George Klein [homepage] and David Murray from Oxford university, presented in ISMAR 2007.
When I first saw it on youtube [link] I immediately saw the immense potential – mobile markerless augmented reality. I thought I should get to know this work a bit more closely, so I chose to implement it as a part of advanced computer vision course, given by Dr. Lior Wolf [link] at TAU.
The work is very extensive, and clearly is a result of deep research in the field, so I set to achieve a few selected features: Stereo initialization, Tracking, and small map upkeeping. I chose not to implement relocalization and full map handling.
This post is kind of a tutorial for 3D reconstruction with OpenCV 2.0. I will show practical use of the functions in cvtriangulation.cpp, which are not documented and in fact incomplete. Furthermore I’ll show how to easily combine OpenCV and OpenGL for 3D augmentations, a thing which is only briefly described in the docs or online.
Here are the step I took and things I learned in the process of implementing the work.
Update: A nice patch by yazor fixes the video mismatching – thanks! and also a nice application by Zentium called “iKat” is doing some kick-ass mobile markerless augmented reality.
Hi All
It looks like it’s finally here – a way to grab the raw data of the camera frames on the iPhone OS 3.x.
Update: Apple officially supports this in iOS 4.x using AVFoundation, here’s sample code from Apple developer.
A gifted hacker named John DeWeese was nice enough to comment on a post from May 09′ with his method of hacking the APIs to get the frames. Though cumbersome, it looks like it should work, but I haven’t tried it yet. I promise to try it soon and share my results.
Way to go John!
Some code would be awesome…
Roy.
Hi
In the past few weeks I have been working hard at a few projects for end-of-term at Uni. One of the projects is what I called “SmartHome”, for Embedded computing [link] course, is a home monitoring [link] application. In the course the students were given an LPC2148 arm7-MCU (NXP) based education board, implemented by Embedded Artists [link]. My partner Gil and I decided to work with ZigBee extension modules [link] to enable remote communication.
Here are the steps we took to bring this project to life.
Hi
I wanted to do the simplest recoloring/color-transfer I could find – and the internet is just a bust. Nothing free, good and usable available online… So I implemented the simplest color transfer algorithm in the wolrd – Histogram Matching.
Here’s the implementation with OpenCV
Categories
Links of the week
http://www.runnersworld.com/article/1,7124,s6-240-319–13001-0,00.html
Shoes tying hacks
http://www.engadget.com/2010/01/18/misa-digital-guitar-cuts-the-strings-brings-the-noise/
Very nice! A digital guitar…
http://www.newscientist.com/article/dn18036
An interesting concept – see-through walls w/ augmentd reality
http://gizmodo.com/5452140/one-third-of-us-11+year+olds-have-cellphones
The “Youth market”‘s little brother – the “Toddler market” – is booming
http://gizmodo.com/5451876/rumor-apple-iphone-os-40-features-detailed
Some goodies from iPhone OS 4 – where is video-pixel-bytes access already?!
http://lifehacker.com/5452786/memorize-now-helps-you-commit-long-passages-to-memory
I like! A helper webapp to memorize text
http://gizmodo.com/5452684/voice-band-iphone-app-converts-bah-ba-ba-bah-into—
This is awesome.
http://gizmodo.com/5453436/googles-html5-youtube-videos-dont-need-flash
YouTube without flash: I tried it on Chrome, the video was choppy, volume control didn’t work proerly and the progressing download & play made the position marker bounce around. But in the end, anything that replaces Flash, and Adobe’s reign over internet interactive animation, is good..
C ya’ll next week!
Roy.