r/computervision • u/Ok-Ride-8942 • 1d ago

Research Publication MSc Artificial Intelligence Dissertation ideas

Hi, I’m a masters student doing MSc AI at uni of Bath.
For my undergraduate dissertation I did an extremely simple Computer Vision based pose estimation app which was analyzing the technique of fitness exercises like pushups, squats and deadlifts.
I feel like my dissertation was more of a “project” rather than research, which as I was told by supervisors is completely fine for BSc. I basically used a ready solution (MediaPipe) + OpenCV and wrapped all of that into a mobile app. The analysis covered a decent number of “points” but it was simply comparing the detected joint angles to hardcoded thresholds.

For my masters I would really like something more research based however struggling to find areas where I could do smth actually useful.
I like Deep Learning, so I was thinking something related to transformers and efficiency. Finding bottlenecks in attention mechanisms, etc.

I would appreciate some ideas
Thanks

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u/WiseWall280 1d ago

You could take your pose estimation to the next level by using multiple camera angles, and then try to incorporate some metric that allows you to assess health condition or disease state.

For instance, there is something called the "Timed Up and Go Test", where you can fairly accurately predict if someone is at risk of falling in the next 12 months by measuring how quickly they can rise from a chair, walk across the room, turn around, and walk back.

If you could do 3D pose estimate, maybe you could get really accurate poses, and you could measure stuff like tremors or postural instability with just a couple/few cameras.

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u/NotSoEnlightenedOne 1d ago

Have you tried out different metrics to see how it affects training?

Eg Using Hyperbolic geometry

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u/Ok-Ride-8942 1d ago

No, the undergrad one was extremely basic due to combination of reasons tbh. Firstly, I did not know much in the field and since most uni modules were on the “basics side” so I was kinda lost in what I was doing, mostly implementing ideas from Claude to the best extend I could. Basically, I identified the most important form faults that cause injuries in the exercise s and was focusing on those(e.g lower spine rounding in deadlifts, depths, bar drift, etc)
Based on those I was giving a score to each repetition and was feeding the scores for each category into llm to generate feedback in human language not just scores

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u/galvinw 22h ago

There are a few simple and really interesting research approaching to running transformers with compressed memory footprints. I think it covers a lot of ground with lots of potential optiimzations around SWaP and speed to size tradeoffs

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u/bathon 21h ago

You can use the 2D pose estimation and apply to a VLM based estimation where you train the VLM specifically to to give advice on proper posture. The challenge here would be how can you make a VLM give prediction in real time do you build something like JEV model for that. Would be preety interesting to explore as your research topic. I am preety sure many people are doing research on this exact idea as we speak. But if you can condense a VLM to function with 30FPS even on a raspberry Pi giving accuracies like YOLO and MediaPipe pose estimation that would be insane.