Visualization of Stone Trajectories in Live Curling Broadcasts using Online Machine Learning

Takahashi, Masaki; Yokozawa, Shinsuke; Mitsumine, Hideki; Mishina, Tomoyuki; Matsuhisa, Yasuyuki; Muramatsu, Sawako

doi:10.1145/3123266.3123351

Cited by 4 publications

(4 citation statements)

References 14 publications

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“…Twenty-one studies evaluated technological/artificially intelligent devices developed and implemented within the sport of curling. Thirty-eight percent ( n = 8) of these studied the design and implementation of robotic machines across multifaceted aspects of curling ( 35 , 39 , 41 , 44 – 49 ). Of the artificially intelligent (AI) curling robots, fabricated features included throwing controls to test precision and throwing accuracy, AI-based strategy simulators, vision technology to recognize the curling field and stone configuration/trajectory, and sweeping systems to deliver path planning strategies for sweeping ( 35 , 47 – 49 ).…”

Section: Resultsmentioning

confidence: 99%

“…Other devices monitored musculoskeletal analysis of upper body kinematics and release velocity ( 44 ), as well as a digital curling system, used as a framework to compare curling strategies ( 33 ). Artificial infrastructure from four studies was evaluated with respect to their ability to monitor real-time position measurements and trajectory behavior of the curling stone, including an infrared camera ( 42 ), a prototype of a curling stone launcher ( 41 ), smart glasses ( 40 ), and a kernelized correlation filter tracker ( 39 ).…”

Section: Resultsmentioning

confidence: 99%

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An examination of studies related to the sport of curling: a scoping review

Zacharias,

Robak,

Passmore

2024

Front. Sports Act. Living

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IntroductionThere has been growth in research in the sport of curling over the past few decades. The need for a scoping review is warranted. This study's purpose was to identify and synthesize research evidence regarding quantitative variables for a series of components within the sport of curling.MethodsA scoping review of studies published and established within four databases was performed. One independent reviewer selected studies based on a systematic procedure. Inclusion criteria for studies were: (1) interventions that focused on the sport of curling; (2) quantitative in nature; (3) written in English; and (4) published within a peer-reviewed journal, a conference presentation, or a published thesis.ResultsSearching identified 8,467 articles and 94 met the inclusion criteria. Data were organized and synthesized based on the devised research variables from the sport of curling: The curl mechanism of the curling stone; the impact of sweeping on stone trajectory; curling delivery mechanics; wheelchair curling; technology analysis; strategy and tactics; psychological factors; injury occurrences; facility and arena infrastructure; and assessment of curling training and ability. The findings confirm the strong knowledge base that exists across game variables and unveil controversy between the underlying physics that produces curl, as well as the mechanisms of sweeping responsible for manipulating the stone trajectory.ConclusionsKnowledge derived from this review can assist researchers, coaches, and curlers in addressing the specific variables of the sport that influence stone trajectory and game results. Such awareness will expose gaps in the current understanding and foster new research endeavors to further the knowledge of the sport.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

An examination of studies related to the sport of curling: a scoping review

Zacharias,

Robak,

Passmore

2024

Front. Sports Act. Living

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“…6 Takahashi et al used the Kernelized Correlation Filter (KCF) tracker to detect the location of the stone as a way to visualize its trajectory during a curling game broadcast. 7 Therefore, this paper proposes a method to automatically track the position of stones in curling sport videos using computer vision technology. The authors extract the optimal feature vector of the mean-shift tracking algorithm by obtaining the optimal histogram from the color and edge information of the curling stone, thereby adaptively controlling the number of bins in the histogram.…”

Section: Introductionmentioning

confidence: 99%

“…6 Takahashi et al used the Kernelized Correlation Filter (KCF) tracker to detect the location of the stone as a way to visualize its trajectory during a curling game broadcast. 7…”

Section: Introductionmentioning

confidence: 99%

Curling stone tracking based on an enhanced mean-shift algorithm using optimal feature vector

Kim

Han

2020

Proceedings of the Institution of Mechanical Engineers, Part P:

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Computer vision technology can automatically detect and recognize objects on the ground or on a court, such as balls, players, and lines, using camera sensors. These are non-contact sensors, which do not interfere with an athlete’s movement. The game elements detected by such measuring equipment can be used for game analysis, judgment, context recognition, and visualization. This paper proposes a method to automatically track the position of stones in curling sport images using computer vision technology. The authors extract the optimal feature vector of the mean-shift tracking algorithm by obtaining the optimal histogram from the color and edge information of the curling stone, thereby adaptively controlling the number of bins in the histogram. After evaluating the performance of the curling stone tracking method among 1424 image frames from curling sport videos, the authors found that the proposed method improved detection rate (overlap threshold = 0.9) by 14.85% compared to the general mean-shift method.

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スポーツ中継における放送技術

Imamura¹,

Mishina²

2018

IEICE Commun. Mag.

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Visualization of Stone Trajectories in Live Curling Broadcasts using Online Machine Learning

Cited by 4 publications

References 14 publications

An examination of studies related to the sport of curling: a scoping review

An examination of studies related to the sport of curling: a scoping review

Curling stone tracking based on an enhanced mean-shift algorithm using optimal feature vector

スポーツ中継における放送技術

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