A trajectory-based ball detection and tracking system with applications to shot-type identification in volleyball videos

Chakraborty, Bodhisattwa; Meher, Sukadev

doi:10.1109/spcom.2012.6290005

Cited by 16 publications

(5 citation statements)

References 8 publications

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“…The attack is an offense mode done by a team to trick the opposite team and gain score (Papageorgiou & Spitzley, 2003). The attack can be performed in open, semi, and quick technique which is categorized based on the height of the ball from the net (Chakraborty & Meher, 2012). Back attack and tip-ball are variations among those three categories based on the movement of the players; the back attack is when one of the three back players behind the attack line attacks the ball and send it over the net, while tip-ball is when a player uses one open hand or knuckles instead of the palm to direct the ball over the net resulting in a slower attack.…”

Section: Attackmentioning

confidence: 99%

Technical Performance Analyses of Volleyball Players using Volleyball Tactical Information Skill (VTIS)

Muhammad

Faruk

Sujatmiko

2020

MoHE

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The purpose of this study was to analyze the technical performance of team performance in an event of the main division in Indonesia. The sample of this study was the players’ performance of the winning team. The data were collected using the Volleyball Tactical Information Skill (VTIS) software which is originally developed by the researcher based on the Volleyball Information System (VIS). The data collected using the VTIS includes service, ball receive, attack, toss, block, and dig that was performed by each player throughout the game. The statistical data is presented on average and percentage. The statistical data obtained from VTIS has been proven to be useful and provides valuable information for the team's technical performance.

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Section: Attackmentioning

confidence: 99%

Technical Performance Analyses of Volleyball Players using Volleyball Tactical Information Skill (VTIS)

Muhammad

Faruk

Sujatmiko

2020

MoHE

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“…Bodhisattwa Chakraborty and Sukadev Meher, 2012 [14] had presented tracking algorithm based on ball detection for volleyball video by the various types of shots. The different shot of trajectory information the ball had been reviewed and location of the ball had been estimated.…”

Section: Literature Surveymentioning

confidence: 99%

Basketball Tracking using Mean Shift Algorithm

Margarat¹,

Sivasubramanian²

2019

IJRTE

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Video analysis plays a vital role in commercial application, sports and military systems. Various methods are presented in literature. Mean shift algorithm is presented in this paper for basket ball tracking because it is more efficient than other that is defined by histograms. The tracking is the important block in the detection and recognition of the basket ball. Different object tracking algorithms are investigated. The performance of tracking in two video sequences is performed and the method gives 91.3% precision for video sequence 1 and 93.6% for sequence 2

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“…An general overview of sports informatics technologies can be found in [1]. Our work relates to various works that detect and track certain objects in sports, e.g., tennis [25], table tennis [6], soccer [10,17,24], basketball [3], volleyball [4,5], or even pool billiard [18,19]. The best known multi camera technology that works with player and ball tracking is probably the "Hawk Eye" [13], widely used in tennis sports, not only to aid referees but also to collect statistical data (mostly for audiences and TV).…”

Section: Related Workmentioning

confidence: 99%

“…[6] extracts data without calibration and uses table and player tracking instead. [4] uses a very similar process to ours of subtracting a background picture to avoid noise. [18] follows our approach in pool billiard and differences between balls by color.…”

Section: Related Workmentioning

confidence: 99%

Using Video Analysis and Machine Learning for Predicting Shot Success in Table Tennis

Draschkowitz¹,

Draschkowitz²,

Hlavacs³

2015

EAI Endorsed Transactions on Creative Technologies

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Coaching professional ball players has become more and more difficult and requires among other abilities also good tactical knowledge. This paper describes a program that can assist in tactical coaching for table tennis by extracting and analyzing video data of a table tennis game. The here described application automatically extracts essential information from a table tennis match, such as speed, length, height and others, by analyzing a video of that game. It then uses the well known machine learning library "Weka" to learn about the success of a shot. Generalization is tested by using a training and a test set. The program then is able to predict the outcome of shots with high accuracy. This makes it possible to develop and verify tactical suggestions for players as part of an automatic analyzing and coaching tool, completely independent of human interaction.

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A trajectory-based ball detection and tracking system with applications to shot-type identification in volleyball videos

Cited by 16 publications

References 8 publications

Technical Performance Analyses of Volleyball Players using Volleyball Tactical Information Skill (VTIS)

Technical Performance Analyses of Volleyball Players using Volleyball Tactical Information Skill (VTIS)

Basketball Tracking using Mean Shift Algorithm

Using Video Analysis and Machine Learning for Predicting Shot Success in Table Tennis

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