PoolTracker DDR

I spent most of this week putting our project together. This included integrating the different components together and coming up with a plan for the impending demo on Monday. In particular, most work was focused on our stroke classification algorithm and tuning our model to get a higher accuracy. Additionally, I made minor adjustments to our web app front end to improve the user interface.

For the upcoming week, I hope to have a smooth demo and a strong report to finish up the course.

This week my aim was to have an UI working from end-to-end. To that end, I focused on the web app with Jack and it is now working completely. Furthermore, we made some progress w.r.t. the stroke classification task and we now have some naive classification techniques which we plan to build upon.

In the upcoming final week, our plan is to tweak the classification and tracking algorithms as much as possible to have a well functioning project in the end.

This week the focus was on getting the web application done to completion. I worked on redesigning some of the UI and writing the logic for the web app backend. The web app can now be used to visualize entire workouts and import/export workouts.

For the upcoming week, the aim is to have our MVP project completed to demo to our TAs and professor on Wednesday. To that end, I will work on getting the stroke classification code completely set up. I will also work on debugging the existing tracking algorithm.

This week most of our time was dedicated to getting prepared for the demo. As a reflection, we think the demo went well and the components that we wanted to showcase for the demo are working as per our initial specification. Based on the TA feedback, we will start working towards improving our front end further and getting stroke classification going.

The immediate next step if to improve our tracking capabilities and setting up a way by which we can start doing stroke classification. We expect the upcoming week and a majority of the remainder of the semester to be spent doing this.

 

This week the majority of the time was spent in fine-tuning our tracking algorithm in order to showcase for our demo. In particular, a realization that we made was that we might need to do our tracking by combining different traditional algorithms that may be suitable to our context. I have been working to get this working smoothly.

For the upcoming week, I’m going to focus on setting up the infrastructure for stroke classification. This involve coming up with a way by which we can analyze our footage, encode the information and feed it into a classifier. This classifier, as was also suggested by a TA, would most likely be an SVM.

This week most of the progress that I made was directly with the group. I worked with Jack, on fine-tuning the Tracking algorithm by incorporating some preprocessing steps that would improve the reliability of our tracker. Furthermore, I worked on creating the interface between the front end and the back end by writing some of the url bindings for our web app. Currently, we are able to detect wall touches and send + visualize the time data on our web-app.

For the upcoming week, our focus is to have a fully functional demo except for stroke classification (for which we have some code set up as well).

This week, the majority of the progress came on the web app side of things. We designed the overall UI of our web app and at the same time got it to respond to requests from the processor back end.

Additionally, we started to spend some time with different tracking algorithms in order to check what works well and what doesn’t work well for our particular problem domain. We have a couple interesting solutions to solve the problems that we face.

By the upcoming demo in 2 weeks, we plan to get our tracking completely working so that the only thing that we have as a remainder after carnival is the stroke classification task as well as minor tweaks to our project.

This week almost all of the time that I spent on this project was spent on working on the same problems as the rest of my group. As a result, I worked on implementing the web app and at the same time getting some tracking algorithms tested.

For the upcoming two week, my personal aim is to get tracking working completely. Additionally, I will continue to assist my group with the web app.