UNSW capstone · Computer vision
Coach Cane
For people who are blind or have low vision, learning to use the white cane.
- The problem
Learning to use a white cane takes lessons with a specialist trainer, and many visually impaired individuals live far from one.
- The idea
Coach Cane brings the lesson to them. The trainee stands in front of a laptop camera, and the trainer joins over a live video call.
- The coach
While they practise, the computer watches how they hold and swing the cane, and says tips out loud, like “speed up”, so nothing depends on seeing the screen.
- Type
- Capstone, COMP9900
- Year
- 2026
- Team
- Five · I built the computer vision
- For
- Blind and low-vision trainees
- Status
- Prototype, handed to the client
- Arc
- 58°
- 25–85°
- Rate
- 0.80
- 0.55–1.8 /s
- Off midline
- 0.06
- ≤ 0.4 shoulders
- Wrist roll
- 52°
- ≤ 110°
SpokenGood technique.
Illustration · simulated readings
My part
All of the computer vision
Everything between the webcam and the spoken tip: how Coach Cane sees, what it measures and what it says.
- 01
See
Google's MediaPipe finds 33 points on the body and 21 on each hand, 30 times a second, right in the browser.
- 02
Measure
My own geometry turns those points into angles, measured against the trainee's shoulders and hips, so it works wherever the laptop sits.
- 03
Judge
It weighs a few seconds of movement at a time, never a single frame, so one glitch can't set off a tip.
- 04
Speak
One tip at a time, the most important first. When it isn't sure, it stays quiet rather than guess.
What it checks
- Framingthe whole trainee in view, at the right distance
- Gripa handshake grip, palm sideways, thumb on top
- Index fingerstraight along the cane
- Wristflicks side to side, never rolls
- Hand positioncentred in front of the body
- Sweep widthabout 60°, from 11 to 1 o'clock
- Sweep speedsteady, neither too slow nor too fast
- Sweep evennessthe same on both sides
- The cane itselffound in the camera image, even far away
Tools and skills: MediaPipe Pose, MediaPipe Hands, Pose estimation, Hand tracking, Geometric feature engineering, Body-frame coordinates, Ridge detection, Ray casting, Frame differencing, Time-windowed statistics, Percentile filtering, Median filtering, Hysteresis, Rule-based decision engine, Web Speech API, Evaluation harness, Threshold calibration on client video, Unit testing (33 tests), Debugging from raw measurements, TypeScript, Real-time in-browser processing, Canvas, React, Vite, WebRTC, WebSocket, FastAPI, PostgreSQL, Docker