This week I spent working on getting my poster ready for printing. Other than that I also spent several hours preparing my paper for the evaluation draft due Friday. Not there yet but making progress.

I spent most of this week writing the most recent draft, and then putting together a first draft of the poster. Spent some time debugging, but my focus was on the paper and poster.

This week I continued debugging my code. I now have everything I need working working. It’s not as good as I think it can be, but it is fully operational. Spent a little time starting paper revisions and that’s next up.

This week I turned in a new draft of my paper and fixed a few bugs. I am now ready to collect most of the data I’ll need.

This week I

-implemented feedback from the first draft

-started writing the rest of the paper

-did some minor debugging and commenting

Over this week I worked on finishing a first draft of my paper. Also I worked on debugging code and trying to install some packages.

I tested that the last of my dependencies is on the cluster and functional. Started implementing the second major piece of my approach, SURF. Taking a little longer than expected but not a major delay.

Changed a piece of my pipeline and created some issues. Working on fixing those, and hopefully improving the overall functionality in the process.

This week I finished my implementation of the SIFT algorithm, starting to work on implementing SURF next.

Also looking ways to organize images to improve accuracy. Currently planning to get keypoints, then organize photos based on similar keypoints rather than locality.

This week I made a first draft of an outline for the paper. Also worked on implementing the first of three algorithms I plan to use in my research, Scale Invariant Feature Transformation. While not completely finished I have most of the framework complete, and am just about where on schedule.

This week I worked on developing a script that takes a directory and determines if the contents are all images of the same type, and if they aren’t converts them to jpgs. I also meet with my adviser and starting working on an outline that will be due next week.

Found an advisor, and set up a meeting time to plan my project. Tested that the libraries I plan on using are available and functional on the cluster. Finally reviewed my project to make review the goals I’ve set myself are achievable and reasonable.

Got feedback for my second draft of my proposal. Ready to make these final changes and submit on time! Started installing the dependencies so that I can get familiar with the tools I’ll be using over the break. Not planning to commit too much effort into this in the midst of finals, but will redouble my efforts after the tests are over.

A much slower week than normal, I was swamped with a number of other pre break assignments so I wasn’t able to put much work into reading or revising this week. But I was able to work on revising my introduction and related works section. The focus for the coming week will be to make any final revisions in my paper, and see if there are one or two more papers worth adding in. Found a very good paper on field work that helps establish the background for my work.

Found an advisor, Ajit, and scheduled a meeting. Otherwise did a second look at a couple papers I had only done a first pass on. Otherwise waiting on feedback on my first draft and spent a little time looking at some potential test data if I find myself in need of other sources.

This week I just worked on writing the first draft of my proposal. Found several additional papers to bring myself up to the requirement and fleshed out my idea for what I want to do in a bit more detail. The new papers provided insight on several other computer vision algorithms that I might be able to use, time allowing. Got notes and incorporated those changes into my draft. Built a diagram for my proposal.

This week I filled out the quiz and started looking into what resources I’ll need for my project, image stitching. At the least I’ll need openCV, but probably imageMagick as well. Starting to think about how I should organize my project, and looking into how easy or hard parallelizing my procedure will be. A few of the papers I read referenced open image libraries they used and I’m thinking about looking into how hard it will be to get access to those.

Making heavy headway into literature review, but still adjusting to overleaf. My final topics are predicting matches in the premier league, and making a software that combines several CV methods in a robust wrapper for easy use. Found eight sources for both topics. Found surprisingly little continuity in methods predicting futbol games.

Prepared a presentation for class on my final two topics, image stitching and predicting premier league games. Started searching for additional topics so I can meet the 8 requirement for the imminent lit review.

Nothing much to report, worked on my annotated bibliography and am narrowing down my interest to just two of my three ideas. Currently leaning towards 2d stitching, potentially expanding it to include some 3d point cloud work as well, but that is only a thought at the moment. The amount of work that has gone into predicting premier league games has taken a lot of interesting directions, but I’m not sure thats what I want to focus on.

1)A piece of software that takes aspects of a soccer team and suggests players to sign or release based on statistics found online. This will include physical attributes, such as height, weight, 40 time, as well as statistics like shots on target and passes. This could be improved to search for specific words in scouting reports such as “dynamic” or “intelligent”.

2)Soccer is a dynamic and fluid game with many complexities that make it very difficult to predict. I’m interested in looking at how current predictions are made, such as at fivethirtyeight, and attempting to develop software to predict outcomes of matches.

3)Drones create opportunities to see the world with an unprecedented amount of freedom and flexibility. As they improve they’re able to fly higher and for longer, and cameras also improve to take images of incredible quality even from heights of more than 100 meters. The result is a lot of images. I’m interested in creating a robust piece of software that stitches large sets of images together reliably and quickly into a single 2D image.