Vision-Based Global Localization of Points of Gaze in Sport Climbing

Author:

Nguyen Tan-Nhu1,Seifert Ludovic23,Hacques Guillaume2,Hammami Kölbl Maroua2,Chahir Youssef4ORCID

Affiliation:

1. School of Engineering, Eastern International University, Nam Ky Khoi Nghia Street, Hoa Phu Ward, Thu Dau Mot City, Binh Duong Province, Vietnam

2. CETAPS UR3832, Faculty of Sport Science, University of Rouen Normandy, Rouen, France

3. Institut Universitaire de France (IUF), Paris, France

4. Normandie University, UNICAEN, ENSICAEN, CNRS GREYC UMR CNRS 6072, 14000 Caen, France

Abstract

Investigating realistic visual exploration is quite challenging in sport climbing, but it promises a deeper understanding of how performers adjust their perception-action couplings during task completion. However, the samples of participants and the number of trials analyzed in such experiments are often reduced to a minimum because of the time-consuming treatments of the eye-tracking data. Notably, mapping successive points of gaze from local views to the global scene is generally performed manually by watching eye-tracking video data frame by frame. This manual procedure is not suitable for processing a large number of datasets. Consequently, this study developed an automatic method for solving this global point of gaze localization in indoor sport climbing. Particularly, an eye-tracking device was used for acquiring local image frames and points of gaze from a climber’s local views. Artificial landmarks, designed as four-color-disk groups, were distributed on the wall to facilitate localization. Global points of gaze were computed based on planar homography transforms between the local and global positions of the detected landmarks. Thirty climbing trials were recorded and processed by the proposed methods. The success rates (Mean[Formula: see text]±[Formula: see text]SD) were up to 85.72%[Formula: see text]±[Formula: see text]13.90%, and the errors (Mean[Formula: see text]±[Formula: see text]SD) were up to [Formula: see text][Formula: see text]m. The proposed method will be employed for computing global points of gaze in our current climbing dataset for understanding the dynamics intertwining of gaze and motor behaviors during the climbs.

Funder

French National Agency of Research

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. LOCALIZATION METHOD OF HUMAN SKELETAL SEQUENCE MOVEMENTS IN ICE SPORTS;Journal of Mechanics in Medicine and Biology;2024-03

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