This was a student intern project that I took over to turn into a useful application for use within the company. Even though this wasn't a research project, we thought it would be a good way to make Barco Labs better known throughout the company, as many employees viewed us as an "ivory tower" doing esoteric research of little practical value. The Smart Meeting Room App (SMRA) had the very practical benefit of finding and scheduling meeting rooms on the Barco campus.
Visual Studio Code
Visual Studio Code (a.k.a. VSCode) description TBD...
Experiences using this skill are shown below:
By 2019, our machine-learning research project was now integrating and managing multiple cameras and video sources and as a result it was becoming increasingly difficult to configure using config. files only. I was given the task of creating a professional-looking desktop UI that could be accessed from a web browser on company locked-down PCs. It was decided that there would be no support for mobile devices and the GUI would be package as a Docker image.
An earlier version of our machine-learning person tracking software was too slow to keep up on every video frame. (This was before our team attempted to use GPU acceleration with more efficient person tracking software.) This resulted in jumpy video transitions while tracking someone. I was given the task of finding a way of applying video motion smoothing so the resulting video framing would be smooth and professional looking.
Since I had already computed the homography and object segmentation for the text readability prototype, it was just a matter of using the OpenCV library to apply perspective warping on that video stream (from a computed perspective transform based on the homography matrix) so that one video stream could be seamlessly inserted into the other to create an augmented reality mashup. The result was a much clearer rendering of the projected content as seen in the composite video stream by remote users.
I was given the task of researching automatic white-balance algorithms with the goal of calibrating multiple video cameras to the same color balance. The problem was that when switching between multiple cameras covering the same scene, a noticeable color shift was observed in the video stream, especially when the cameras were of different manufacture.
I was given the task of researching and prototyping various computer vision algorithms to determine whether the text appearing within a given video frame was readable or not.