Accomplishments this week
Most of my time this week went into the design report. Feedback asked us to justify our design choices with real comparisons, so I ran a few quick experiments on my laptop using our existing treadmill clips. No training was involved.
– Image subtraction vs. our pose model: Feedback asked whether simple image subtraction could replace deep learning, so I tested several classical methods on our two treadmill clips. The best one compared each frame with a photo of the empty belt and got 87.8% of checks right. However, it made 14 errors on settled states and flagged 11 of 20 people walking past as using a treadmill. The pose model got 98.6% right with zero errors, because it checks whether someone’s feet are actually on the belt instead of reacting to any change in the image.
– Delay: Our worst case of 3.5 s of delay breaks down into about 1 s where even the label was ambiguous (mid-step), 0.5 s of model lag, and 2 s of voting. Measured from when a person could actually tell, every change showed up within 2.5 s, well under our 5 s target.
– Voting rules and model size: Other voting windows made no fewer errors and only added delay, so we’re keeping 3 of 4 checks for “in use” and 5 of 6 for “available”. The larger YOLO11s-pose model gave the same results at about twice the CPU time, so we’re sticking with YOLO11n-pose.
– Test planning: I worked out how many trials we need to back up our accuracy targets: at least 36 error-free trials to support 92%. This set the size of our test plan.
I also double-checked our treadmill labels against the video.
Schedule status
The treadmill software is still ahead of schedule as a laptop prototype. However, since the design report took priority, I didn’t get to last week’s hardware tasks: the Jetson board check, the live camera-to-tablet test, recording new clips, and the recording permission. These are now my main risk. Our schedule has the first Jetson tests in the week of October 19, after fall break, so I’ll start with the board check since everything else depends on it.
Deliverables for next week
– Run the treadmill board check on the Jetson by October 21 (timing, memory, temperature), and compare it with my laptop results.
– Try a TensorRT export of the pose model, and keep it only if its results match.
– Run a live test from the C922 camera to the tablet, timing how long each change takes to appear.
– Submit the UC gym recording permission request, and confirm our backup gym.
– Record more treadmill clips with teammates, saving some for final testing only.