Abstract
Rock climbing is a sport in which blind people have traditionally found it extremely difficult to excel due to the high degree of visual problem solving required, and also the requirement to climb with a sighted assistant. We present a system which automates the role of the sighted assistant in order to provide blind people with the freedom to climb and train on their own. We address climbing-specific limitations of a state-of-the-art skeleton tracking system, and discuss the ways in which we mitigated these limitations using post-processing techniques tuned specially for a climbing scenario. We also describe the auditory feedback system used to instruct the blind climber, and demonstrate that a user can learn to follow it in a relatively short time by showing a significant improvement in performance over just a few trials with the system.
| Original language | English |
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| Title of host publication | 2020 Winter Conference on Applications of Computer Vision (WACV ’20) |
| Publisher | IEEE Computer Society |
| Number of pages | 8 |
| Publication status | Accepted/In press - 9 Dec 2019 |