I am again a little annoyed by the TU/e helpdesk, for not having VPN profiles ready to download for those that already have a VPN client installed. The only option you normally have is downloading a Cisco client that comes with the profiles. So I took the liberty to extract the profiles from this auto-extractor to upload the .pcf files to import in your VPN client.
I just received my grade for the first of two papers I have to write before receiving my Master’s degree. It’s good and I enjoyed the research, so why not post it online?
The study is a wee bit too small to be submitted to a conference paper, but too large to be completely forgotten, so I’m posting it online. The study tried to study the occurrence of choice overload in a movie recommender system and whether or not diversifying the set of recommendations alleviates choice overload. The results were not really conclusive, but good enough to base a second study on. And enough questions rose to base a master thesis research on. So go ahead and read it if you want to.
During my stay at NUS I followed a course on Computer Vision by Terence Sim. The course was partly a project that I did with Florian Kock and Samuel Martin. Our self-assigned subject was an image stabilization algorithm. This page shows you the result of our algorithm and the slides of the final presentation. The slides can be seen by clicking on the image to the right.
Below is a result video of our algorithm. The algorithm is based on removing the high-frequency movements found in video. In order to do so, three steps had to be taken.
Step 1: Finding the movement In order to find the movement, we calculated the difference in position, rotation and zooming of every two succeeding frames. This was done by finding corresponding points in every two frames, selecting the best ones and calculating the homography. Finding corresponding points was done with the Shi-Tomasi algorithm to find valuable features to track and the pyramidical Lucas-Kanade optical flow calculation. Because the result was still pretty noisy, we iterated the calculation of the homography, removing the points that had a too large error at every step.
Step 2: Averaging the movement For every frame a moving average was taken in order to remove the high-frequency movement. Because of the use of homographies, this was not as straightforward. This lead to homographies that, once applied to the original frames, correct the movement by removing the unwanted movement, but keeping the intended movement.
Step 3: Compensating for the movement In the last and final step, all the frames were transformed according to the calculated homographies. An extra step is taken by cropping the image so that the image is filled entirely in every frame.
The result The result is shown below. The first frame is the uncorrected movement. In the middle frame the frames are corrected, it shows that every frame can be rotated, shifted and enlarged in order to compensate for the shaking. The last frame is the final result where a number of pixels are taken from the sides and top and bottom.
Wow, this has been a crazy week. So much information to process, people to meet, pictures to take.
Lectures and courses
I’ve been following so many lectures on so many papers. It’s been crazy. Subjects ranged from “A comparison between Heuristics Evalutation Methods” to “User Research using Mechanical Turk”. I’ve been trying to attend to a lot of usability lectures, some of which were really interesting and some of which were plain bad. It was nice to see the difference between academic work and corporate work.
On the general however, it’s just like school. A lot of people sitting and listening to a lecture. Some people taking notes on paper, some taking notes on their macbook pros and some just taking pictures of the projected slides. Continue reading “the end of CHI”
Well… a conference. What the hell is something like that supposed to be like?
I had an extensive preparation prior to getting in Florence that consisted of booking a flight, getting accomodation and partying the night before departure with crazy exchange students in Eindhoven. Needless to say, the first day in Florence was hectic.
I did make it to the apartment yesterday quite effortlesly (somewhat to my surprise). I did however completely misunderstood Karolien’s Belgian accent for Italian, which lead to me speaking English to someone who’s talking Dutch to me. And while writing this, I realize I haven’t explained that to her yet… But the apartment is way too nice for a shitty student like myself. I’m there together with 3 phd students from my faculty, who I don’t know that well. I think that this might be different when the week is over. I’ve got my own bedroom, with nice kingsize bed. And I’ve got my own bathroom, with bidet. We’re sharing a living room and kitchen, together with the conversations and thoughts that come naturally. Continue reading “CHI – day 1”