Sport climbing is becoming an increasingly popular competitive sport as well as a recreational activity. For this reason, indoor sport climbing operators are constantly trying to improve their services and optimally use their infrastructure. One way to support such a task is to track the climbing activities performed by visitors while climbing. This paper considers a scenario in which a sensor is attached to a piece of climbing equipment that connects the climbing rope to the bolt anchors (quickdraws) and a camera is overlooking a climbing wall. Within this scenario, this paper explores two approaches to detect when a climber finishes a climb and pulls the rope from the wall: 1) a hybrid approach in which sensors and cameras are used and 2) a video-based approach where only cameras are used. The evaluation resulted in recognition precision of 91% for the hybrid and 76% for the video-based approach, respectively. This paper also discusses advantages and disadvantages of analysed approaches and points out future research directions to allow the automatic tracking of climbing activities.

Video and Sensor-Based Rope Pulling Detection in Sport Climbing

Ivanova, I.;Andric, M.;
2020-01-01

Abstract

Sport climbing is becoming an increasingly popular competitive sport as well as a recreational activity. For this reason, indoor sport climbing operators are constantly trying to improve their services and optimally use their infrastructure. One way to support such a task is to track the climbing activities performed by visitors while climbing. This paper considers a scenario in which a sensor is attached to a piece of climbing equipment that connects the climbing rope to the bolt anchors (quickdraws) and a camera is overlooking a climbing wall. Within this scenario, this paper explores two approaches to detect when a climber finishes a climb and pulls the rope from the wall: 1) a hybrid approach in which sensors and cameras are used and 2) a video-based approach where only cameras are used. The evaluation resulted in recognition precision of 91% for the hybrid and 76% for the video-based approach, respectively. This paper also discusses advantages and disadvantages of analysed approaches and points out future research directions to allow the automatic tracking of climbing activities.
2020
9781450381499
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/358598
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