Title:	End-to-End Move Prediction System for Indoor Rock Climbing: Beta Caller
Authors:	Cardenas, Kevin Semwal, Sudhanshu Maher, James
Citation:	Journal of WSCG. 2024, vol. 32, no. 1-2, p. 13-20.
Issue Date:	2024
Publisher:	Václav Skala - UNION Agency
Document type:	article článek article
URI:	http://hdl.handle.net/11025/57340
ISSN:	1213 – 6972 1213 – 6980 (CD-ROM) 1213 – 6964 (on-line)
Keywords:	umělá inteligence;počítačové vidění;interakce člověka s počítačem;detekce objektu;odhad pozice;predikce lidského pohybu;horolezectví
Keywords in different language:	artificial intelligence;computer vision;human computer interaction;object detection;pose estimation;human motion prediction;rock climbing
Abstract in different language:	We developed Beta Caller, an end-to-end system supporting the sport of rock climbing for climbers with visual impairment. Beta Caller provides real-time, audible instructions containing a prediction for the climber’s next move while they are actively climbing a rock wall. This system leverages computer vision techniques to collect key information about the climber’s environment, enabling Beta Caller to make move predictions on climbing walls it has never encountered before. Neural networks are used to predict where the climber should move next, based on information provided by the computer vision models. The predicted move is translated into a verbal message guiding the climber to the next hold and then transmitted via wireless headphones using a text-to-speech model. This novel idea makes one of the fastest growing sports in the world even more appealing and approachable to climbers with visual impairment, however, this tool can be utilized by all climbers to improve their climbing skills. Beta Caller achieved 80.08% accuracy predicting which limb the climber should move next and, when predicting the location of the next hold, Beta Caller achieved a bounding box error of only 6.79%. These results pioneer a strong foundation shaping the future landscape of rock climbing prediction tools for visually impaired climbers
Rights:	© Václav Skala - UNION Agency
Appears in Collections:	Volume 32, number 1-2 (2024)

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