An Optimization Based deep LSTM Predictive Analysis for Decision Making in Cricket

Nelikanti, Arjun; Reddy, G. Venkata Rami; Karuna, G.

doi:10.1007/978-981-15-9651-3_59

Cited by 4 publications

(3 citation statements)

References 20 publications

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“…The system imbrutes the varied actions taken during a cricket match, allowing the umpire and coach to make accurate decisions during the game. The study by Arjun Nelikanti et al ( 57 ) focuses on creating a system that helps the cricket on-field umpire make Leg before wicket options including using two cameras located at the on-field umpire's position to note the clip of the batter attempting to play the ball. At first, pre-processing yields data on ball movement.…”

Section: Literature Reviewmentioning

confidence: 99%

Information communication and technology in sports: a meticulous review

Reyaz

Ahamad

Naseem

et al. 2023

Front. Sports Act. Living

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IntroductionSports of all kinds even though have an alluring property of keeping their onlookers stuck to their place, the introduction of Technology, however, revolutionized it all together. Not only in legal sports but also the training and teaching methods have been reformed. The use of Information Communication and Technology (ICT) based technologies [Convolutional Neural Networks (CNN), Hawkeye, Computer vision, Artificial intelligence, etc.] has moderately increased the interactive nature of sports. Employing ICT-driven technologies have continuously been increasing performance levels due to which high effective performance levels have been achieved. In addition to offering information to the users, it also acts as a means for connecting and interacting with the remaining world. In this article, we provide a review of the studies considering the developments and impact of employing ICT technology on sports, especially cricket. The study has focussed on domain-specific developments in cricket sports: developments in the batting domain, bowling domain, and wicketkeeping as well.MethodsFor the study, the analysis has been done following the PRISMA guidelines.ResultsThe study found that even though the researchers have done justifiable work in employing technology in sports as a whole but the domain-specific contribution in sports like cricket is not at the level as is need of the hour. In addition to the mentioned domains in the study, the research should gain speed in other domains like domain-specific Talent Identification for both genders, different age groups, diverse sports, etc.Discussionundoubtedly, the sports domain is employing technology at a vast level but a few domains like sports talent identification especially related to the most famous games like cricket require an immediate and intense focus of the researchers. Since this domain is still carrying out a traditional coach-oriented approach. There is an acute need to revolutionize the domain by incorporating modern technologies into it.

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Section: Literature Reviewmentioning

confidence: 99%

Information communication and technology in sports: a meticulous review

Reyaz

Ahamad

Naseem

et al. 2023

Front. Sports Act. Living

View full text Add to dashboard Cite

show abstract

“…In many aspects of cricket as well, computer vision techniques can effectively replace manual analysis. A cricket match has many observable elements including bat-ting shots [114][115][116][117][118][119][120][121], bowling performance [122][123][124][125][126][127], number of runs or score depending on ball movement, detecting and estimating the trajectory of the ball [128], decision making on placement of players' feet [129], outcome classification to generate commentary [130,131], detecting umpire decision [132,133]. Predicting an individual cricketer's performance [134,135] based upon his past record can be critical in team member selection at international competitions.…”

Section: Cricketmentioning

confidence: 99%

A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions

2022

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Recent developments in video analysis of sports and computer vision techniques have achieved significant improvements to enable a variety of critical operations. To provide enhanced information, such as detailed complex analysis in sports such as soccer, basketball, cricket, and badminton, studies have focused mainly on computer vision techniques employed to carry out different tasks. This paper presents a comprehensive review of sports video analysis for various applications: high-level analysis such as detection and classification of players, tracking players or balls in sports and predicting the trajectories of players or balls, recognizing the team’s strategies, and classifying various events in sports. The paper further discusses published works in a variety of application-specific tasks related to sports and the present researcher’s views regarding them. Since there is a wide research scope in sports for deploying computer vision techniques in various sports, some of the publicly available datasets related to a particular sport have been discussed. This paper reviews detailed discussion on some of the artificial intelligence (AI) applications, GPU-based work-stations and embedded platforms in sports vision. Finally, this review identifies the research directions, probable challenges, and future trends in the area of visual recognition in sports.

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“…e above way of calculating the probability distribution reduces the amount of computation and improves real-time tracking [22,23].…”

Section: Applying the Cam Shift Algorithm To Track Targetsmentioning

confidence: 99%

Improved Cam Shift Algorithm for Detecting Athletes' Action Targets in Sports Videos

Yuan

2022

Mathematical Problems in Engineering

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The detection and tracking of athletes in sports videos is of great importance, as it helps to automate the analysis of sports videos, thus providing advanced tools and instruments for sports training. The Cam Shift algorithm uses the colour information of objects to achieve tracking of moving targets, so it is very important to choose a suitable colour space when obtaining the colour information of objects. To this end, this paper improves the Cam Shift algorithm by converting the visual system mechanism to perceive the colour characteristics of the image processing, i.e., converting the video image from the RGB colour space to the HSV colour space, using the H (hue) component to model the target object. Experiments show that the improved athlete detection and tracking algorithm is more robust in practical applications. The improved tracking algorithm also has better real-time performance, with a processing speed of 20 fps during the experiments.

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An Optimization Based deep LSTM Predictive Analysis for Decision Making in Cricket

Cited by 4 publications

References 20 publications

Information communication and technology in sports: a meticulous review

Information communication and technology in sports: a meticulous review

A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions

Improved Cam Shift Algorithm for Detecting Athletes' Action Targets in Sports Videos

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