• Title/Summary/Keyword: 축구 선수

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Inductive Content Analysis of Mental Toughness Factors of Korean Football Players (한국형 축구선수 정신력요인에 대한 귀납적 내용분석)

  • Yoo, Ha-Na;Choi, Jae-Won
    • Journal of Convergence for Information Technology
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    • v.12 no.4
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    • pp.166-176
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    • 2022
  • The purpose of this study was to investigate the construct of Korean Version of Mental Toughness through Open-ended Questionnaire for soccer Players and coach. Data collection was inductively analyzed by distributing open questionnaires to 100 soccer players belonging to the Korean Football Association and 100 soccer coaches who participated in the training for obtaining a soccer coach's license. The resulting results are as follows. First, as a result of the inductive content analysis of korean version soccer players mental toughness, 11 factors were derived in the detailed area and 6 factors in the general area. Secondly, in the results on the mental toughness of Korean version soccer players according to soccer players and coaches, both players and coaches were found to be the highest factor, kkangdagu. I hope that the results of this study will be used as basic data for efforts to reduce the improving performance for soccer players and coaches.

The Basic Motion Recognition of A Soccer Player Using Fuzzy Sets (퍼지 집합을 이용한 축구 선수의 기본 동작 인식)

  • 김광용;양영규
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.371-373
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    • 1999
  • 축구경기는 세계적으로 널리 알려진 스포츠이다. 특히, 한국과 일본은 2002년 월드컵을 개최하는 나라이다. 이와 같은 배경에서, 우리는 퍼지 논리를 이용하여 축구 선수들의 기본적인 동작(Motion)을 인식하는 알고리즘을 제안한다. 여기서 기본 동작이란, 걷기, 뛰기, 드리블하기, 서있기 등으로 정의한다. 만약 우리가 축구경기 장면 비디오를 통해 동작 인식을 필요로 한다면, 특징 패턴은 축구선수들의 양다리 각과 한 축구선수와 공과의 거리가 중요 요소가 될 것이다. 이 논문은 축구 선수 및 공의 추적(Tracking)을 통해 전처리된 데이터를 얻을 수 있다고 가정한다. 실험결과를 통해 축구선수 뿐만 아니라 스포츠 경기에서 선수들의 기본 동작 인식에 퍼지 논리를 적용할 수 있음을 알 수 있었다.

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Influence of Participation Sports of Parents on Soccer Player Role Socialization (부모가 축구선수역할사회화에 미치는 영향)

  • Song, Kang-Young;Kim, Hong-Seol
    • The Journal of the Korea Contents Association
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    • v.11 no.12
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    • pp.423-430
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    • 2011
  • The purpose of this study was to examine if influence parents on soccer player role socialization. The participants of the study are 149 who are university soccer players. The stratified cluster random sampling method has been used in this study. The material collection device was the brochure named [Influence parents on soccer player role socialization]. The result of reliability check up was Cronbach's ${\alpha}$. 8847~.7306. To analyze materials, the "ANOVA" and "regression analysis" were used as statistic analysis techniques. The conclusion based on above study method and the result of material analysis are here below. 1. Participation of parents influence on status of team internal. 2. Participation of parents influence on position of team. 3. Participation of parents influence on career of get a prize.

A Face Recognition Based Player Identification via ULBP and SRC in Soccer Videos (축구 비디오에서 ULBP와 SRC를 이용한 얼굴인식기반의 선수 식별)

  • Jung, Ho-Seok;Lee, Jong-Uk;Lee, Han-Sung;Park, Dai-Hee
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06a
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    • pp.446-449
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    • 2011
  • 얼굴 인식 성능을 저해하는 환경으로 인한 축구 비디오에서의 낮은 선수 인식률과 제한된 해공간의 문제점을 해결하는 차원에서 본 논문에서는 다음과 같은 특징을 갖는 얼굴 인식 기반의 축구선수 인식 방법론을 제안한다: 1) 조명 변화에 민감하지 않은 얼굴 표현 방법인 ULBP를 사용하여 얼굴 인식 성능을 향상시킨다; 2) 얼굴 인식 성능을 저해하는 다양한 환경에서도 이미 강인한 성능이 검증된 SRC를 선수 식별 과정에 적용함으로써 안정적이고 높은 선수 식별 성능을 보장한다; 3) 클로즈업 샷뿐만 아니라 미디엄 샷의 정면, 준정면, 측면 얼굴 이미지를 대상으로 선수 식별의 해공간을 확장한다; 4) SRC의 점증적 갱신 학습 능력으로 축구 선수 얼굴 데이터베이스의 변화에도 능동적으로 적응한다. 실제 2010년 남아프리카 공화국 월드컵의 스페인 경기를 대상으로 제안된 방법론의 성능을 실험적으로 검증한다.

Predicting Soccer Players' Wage Grades Using Big Data and Artificial Intelligence (빅데이터 및 인공지능을 활용한 축구선수 연봉등급 예측)

  • Hyeon-Seong Jeong;Jin-hwa Kim;Dae-Won Hyun
    • Journal of Industrial Convergence
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    • v.22 no.8
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    • pp.19-28
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    • 2024
  • This study proposes a new method for predicting the wage grades of soccer players using big data and artificial intelligence. Predicting the salaries of soccer players is a crucial task that involves accurately assessing players' performance and potential, and reflecting this in their salaries to enhance the economic efficiency of the soccer industry. This research analyzes player ability data provided by FIFA 22 and employs various big data and artificial intelligence techniques to predict players' salary grades. Key methodologies used include decision trees, artificial neural networks, random forests, and boosting, which were utilized to compare the accuracy of the salary prediction models. The results show that the random forest and boosting methods exhibited the highest prediction accuracy. This study demonstrates the process and utility of using big data and artificial intelligence technologies to predict soccer players' salary grades, offering a new perspective on the soccer industry.

An Exploration of the Causal Relationship among Transactional Leadership, Coaches' Emotional Intelligence, and Athlete Satisfaction in Soccer Teams (축구지도자의 변혁적 리더십과 정서지능, 선수만족의 인과관계 탐색)

  • Kim, Sang-Gyu;Choi, Man-Sik
    • The Journal of the Korea Contents Association
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    • v.14 no.9
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    • pp.450-462
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    • 2014
  • The main purpose of this study was to explore the causal relationships among transactional leadership, coaches' emotional intelligence, and athlete satisfaction in soccer teams. High school, university, and semi-professional soccer players(N=495) in Korea participated in a survey. Transactional leadership inventory, emotional intelligence test, and athlete satisfaction questionnaire previously developed to investigate was performed to utilize. The data were analyzed by structural equation model of the AMOS 18.0. The results were as follows; transactional leadership have meaningful influence on emotional intelligence and athlete satisfaction, and emotional intelligence have significant influences on athlete satisfaction. The mediating effect of leader's emotional intelligence between transactional leadership and athlete satisfaction was confirmed. Findings of this study can enhance our understanding of the emotional leadership to increase athlete satisfaction in Soccer players.

A Study on The Game Character Creation Using Genetic Algorithm in Football Simulation Games (축구 시뮬레이션 게임에서의 유전 알고리즘을 활용한 게임 캐릭터 생성 연구)

  • No, Hae-Sun;Rhee, Dae-Woong
    • Journal of Korea Game Society
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    • v.17 no.6
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    • pp.129-138
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    • 2017
  • In football simulation games, it is very important for the interest of the game to make the stats of the football players close to reality. As the management concept is introduced to the sports simulation game, when the user plays the game for a long time, the existing player character retires. Therefore, the game creates the environment of the game by creating a new player in the game. In this study, we propose a method to create a new player character by using genetic algorithm to have the optimal ability similar to existing players. We compare and evaluate the player character with the existing random generation method, the correction random method and the proposed algorithm, and verify the validity of the proposed method.

Development of Soccer Strategy Analysis Tool (축구 경기 분석 도구의 개발)

  • Kwon, O-Je;Jang, Dae-Sung;Li, Ki-Joune
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2010.09a
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    • pp.360-362
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    • 2010
  • 축구 경기는 22명의 선수와 하나의 공을 포함하는 대표적인 이동 객체 연구의 응용분야이다. 본 논문에서는 선수와 공의 궤적정보를 분석하여 축구 경기의 전략 및 전술을 분석하기 위한 도구, 본 논문에서는 이 도구를 SATO(Soccer strategy Analysis Tool)이라 한다,를 소개한다. SATO 시스템의 부분적인 결과로, 본 논문에서는 축구 경기에서 매우 중요한 공격적인 패스를 정의하고 SATO 시스템을 통해 이를 분석한다.

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Soccer Game Analysis I : Extraction of Soccer Players' ground traces using Image Mosaic (축구 경기 분석 I : 영상 모자익을 통한 축구 선수의 운동장 궤적 추출)

  • Kim, Tae-One;Hong, Ki-Sang
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.1
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    • pp.51-59
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    • 1999
  • In this paper we propose the technique for tracking players and a ball and for obtaining players' ground traces using image mosaic in general soccer sequences. Here, general soccer sequences mean the case that there is no extreme zoom-in or zoom-out of TV camera. Obtaining player's ground traces requires that the following three main problems be solved. There main problems: (1) ground field extraction (2) player and ball tracking and team indentification (3) player positioning. The region of ground field is extracted on the basis of color information. Players are tracked by template matching and Kalman filtering. Occlusion reasoning between overlapped players in done by color histogram back-projection. To find the location of a player, a ground model is constructed and transformation between the input images and the field model is computed using four or more feature points. But, when feature points extracted are insufficient, image-based mosaic technique is applied. By this image-to-model transformation, the traces of players on the ground model can be determined. We tested our method on real TV soccer sequence and the experimental results are given.

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A Study on the Pass Analysis of Football Game using Social Networking Analysis (사회연결망 분석을 활용한 축구경기 패스분석)

  • Lee, Hee-Hwa;Kim, Ji-Eung;Park, Jong-Chul
    • Journal of Digital Convergence
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    • v.15 no.7
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    • pp.479-487
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    • 2017
  • The purpose of this study was to identify the most influential soccer players by appling social network analysis. The subjects were the German national soccer team and the Korean national soccer team participated in the 2016 Brazil World Cup. The pass collected data provided by FIFA were analyzed by social network analysis using the Ucinet6 program and pass success rate. The results are as follows. First, the soccer player with a lot of passes had a high connection centrality in pass-through networks and high proximity. Second, the German national soccer team has appeared key players as Phillip Lahm and Kroos player, and a key player of the Korean national soccer team was Ki,S.Y. Third, the German national soccer team's quantitative indicator value of proximity center and pass success rate appeared higher than the Korean national soccer team's.