CRICKET SKILLS DEVELOPMENT

2021-172

Team Members

Introduction

• Cricket is a game played all over the world regardless of the gender and age.
• An emotion, a religion, something more than a game.
• No proper coaching available.

​

​

Introduction

• The proposed system will help the players to improve their cricketing skills in both batting and bowling.
• Classify various types of batting shots, accuracy of a shot, comparison between two players.
• Identifying bowls length, bowls' speed and wicket taking ability.
• Users will be able to find statistics based on their performance.

​

Proposed system “Cricket4U”

Research Problem

• There is no much intervention of technology in domestic cricket.
• Do we record the best performances of the players.
• Novel approach to cricket domain

​

​

Objectives

Main Objective

• To develop an application to improve the cricket skills of emerging cricketers.

​

Sub Objective

• To identify a human body movement action with related to cricketing shots.
• To identify a bowler’s length and the balls pitching position.
• Comparing the captured body movements with professional cricket shots.
• Calculating the balls wicket taking percentage according to the balls pitching length.

​

Research gap

• No application available for cricket.
• Existing system only have classification of cricket shots, classifying cricket bowlers.
• Implementing a novel approach to calculate the bowling speed.
• Assisting user for improvement

​

System Overview

Gannt �Chart

Work Breakdown Structure

Commercialization

• In order to unlock more international players, user need to switch to premium account.
• Advertisement during the loading process.
• There is no application in the domain Cricket.
• Promoting Application video in YouTube.

​

Budget

R.VITHURSON  | IT18142556

​

BSc Hons information Technology specialization in Software Engineering

R.Vithurson | IT18142556 | Project id- 2021-172

Introduction

• Taking a video as an input through Mobile Application.
• Capturing the Body Movement of the user.
• Converting video into frames.
• Extracting Coordinates from frames.

​

​

​

​

R.Vithurson | IT18142556 | Project id- 2021-172

Background & Research gap

•  Many researchers have tried identifying the cricket shot using existing images & clips .

​

•    No Application developed to compare Users input and a trained model in the cricket domain.

​

​

.​

R.Vithurson | IT18142556 | Project id- 2021-172

R.Vithurson | IT18142556 | Project id- 2021-172

Research Problem

• Lack of resources in rural Areas.

​

• No technical solution to provide proper guidance for users in Cricket Domain

R.Vithurson | IT18142556 | Project id- 2021-172

Research Questions

• How to split the video into frames to capture the body movement?
• What are the ways of capturing user's body movement ?
• How to extract the coordinates from the video?

R.Vithurson | IT18142556 | Project id- 2021-172

Objectives

• Main Objectives
• Capturing User's Body Movement.

​

• Sub-Objectives
• Getting input video from User through Mobile Application.
• Capturing User's body movement using openCV.
• Extracting coordinates from captured body Movement .

​

​

​

​

R.Vithurson | IT18142556 | Project id- 2021-172

System Diagram

R.Vithurson | IT18142556 | Project id- 2021-172

Methodology

• Taking User's video as input and Converting video as frames ..
• By using Human Pose Estimation in OpenCV, we can identify body movement .
• From  captured Human body movement we can extract coordinates.
• Coordinates will be sent to model to comparison.

​

​

R.Vithurson | IT18142556 | Project id- 2021-172

Functional & Non-Functional Requirements

Functional Requirements

• Identifying Human Body Movement
• Extracting coordinates from captured Movement

​

Non-Functional Requirements

• Accurate Body Detection
• Better User Experience

R.Vithurson | IT18142556 | Project id- 2021-172

Technologies to be used

Technologies

• Capturing key points of body-Human Pose Estimation, OpenCV
• Mobile Application- React Native.

​

Tools

• Version Control System – GIT
• Project Management- Azure Boards

​

​

​

​

R.Vithurson | IT18142556 | Project id- 2021-172

Work Breakdown Structure

R.Vithurson | IT18142556 | Project id- 2021-172

Gantt Chart

R.Vithurson | IT18142556 | Project id- 2021-172

References

[1] A. Jalal, A. Nadeem and S. Bobasu, "Human Body Parts Estimation and Detection for Physical Sports Movements," 2019 2nd International Conference on Communication, Computing and Digital systems (C-CODE), Islamabad, Pakistan, 2019, pp. 104-109, doi: 10.1109/C-CODE.2019.8680993.

[2] R. R. Bharath and G. Dhivya, "Moving object detection, classification and its parametric evaluation," International Conference on Information Communication and Embedded Systems (ICICES2014), Chennai, India, 2014, pp. 1-6, doi: 10.1109/ICICES.2014.7033891.

R.Vithurson | IT18142556 | Project id- 2021-172

IT18125344 | Mithelan Devanandan

BSc Hons in Information Technology Specializing in Software Engineering

Mithelan.D | IT18125344 | Project Id- 2021-172

Introduction 

• Identifying the cricket shot performed by the user.
• User can be able to compare their cricket shot with an international player.
• Mobile Application for all the people who have an interest on cricket.

​

​

Mithelan.D | IT18125344 | Project Id- 2021-172

29

Background & Research Gap

• Many researchers have tried classifying the cricket shot as a novel approach.
• Some have used motion vector to identify the co-ordinates.
• There is no smartphone application that enables users to review their cricket abilities.

Mithelan.D | IT18125344 | Project Id- 2021-172

Mithelan.D | IT18125344 | Project Id- 2021-172

• 81.3 % like to compare their shots with an international player

• 50.4 % like to track their performance.

Research Problem

• There is no application available for cricket shot detection.
• Statistics of a player.
• Can everyone go for training?

​

​

​

​

​

​

​

Mithelan.D | IT18125344 | Project Id- 2021-172

Research  Questions 

​

• How to detect the Cricket shot?
• How to compare the cricket Shots?
• How to capture the body coordinates?

Mithelan.D | IT18125344 | Project Id- 2021-172

Objectives

Main Objectives

• Identifying the type of cricket shot is played.
• Comparing the cricket shot with an international player.

​

Sub-Objectives

• Comparing the co-ordinates of the cricket shot using CNN.
• Obtaining photos of international cricket players’ cricket shots and train them.
• Obtaining the body co-ordinates from the user.
• Assist the user

​

​

​

Mithelan.D | IT18125344 | Project Id- 2021-172

System Diagram

Mithelan.D | IT18125344 | Project Id- 2021-172

Methodology

• Obtaining the images/videos of cricket shots[1]
• By using Human Pose Estimation, we can get the co-ordinates.
• Convolutional neutral network can be used for classification of cricket shots with user.
• Model will be deployed to server.

Mithelan.D | IT18125344 | Project Id- 2021-172

Methodology

• Obtaining the images/videos of particular international cricket players.
• 2000+ images needed to train.
• Training them after obtaining co-ordiantes using Human Pose Estimation.
• Using convolutional neutral network, we can get the accuracy of the shot.

​

Mithelan.D | IT18125344 | Project Id- 2021-172

Functional and Non-functional Requirements

Functional Requirements

• Assisting user with his/her statistics.
• Accuracy of the shot.

​

Non-Functional Requirements

• Performance
• Usability 
• Security

Mithelan.D | IT18125344 | Project Id- 2021-172

Technologies to be used

Technologies

Capturing key points of body-Human Pose Estimation -openCV

For classifying the shots – Convolutional Neutral Network

Mobile Application- React Native.

​

Version Control System – GIT

Project Management- Azure Boards

​

​

​

Mithelan.D | IT18125344 | Project Id- 2021-172

Work Breakdown Structure

Mithelan.D | IT18125344 | Project Id- 2021-172

Gantt Chart

Mithelan.D | IT18125344 | Project Id- 2021-172

References

[1] M. Zeeshan Khan, M. A. Hassan, A. Farooq and M. U. Ghanni Khan, "Deep CNN Based Data-Driven Recognition of Cricket Batting Shots," 2018 International Conference on Applied and Engineering Mathematics (ICAEM), Taxila, Pakistan, 2018, pp. 67-71, doi: 10.1109/ICAEM.2018.8536277.

[2] A. Semwal, D. Mishra, V. Raj, J. Sharma and A. Mittal, "Cricket Shot Detection from Videos," 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Bengaluru, India, 2018, pp. 1-6, doi: 10.1109/ICCCNT.2018.8494081.

[3] B. Yao and L. Fei-Fei, "Modeling mutual context of object and human pose in human-object interaction activities," 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, 2010, pp. 17-24, doi: 10.1109/CVPR.2010.5540235.

​

Mithelan.D | IT18125344 | Project Id- 2021-172

IT18190762| A.Manoj Karthik

BSc Hons in Information Technology Specializing in Information technology  

IT18190762 | A.M.Karthik | 2021-172

Introduction

• Identify the bowlers bowling length 
• Identifying the bowling speed.
• Providing the users performance report.

IT18190762 | A.M.Karthik | 2021-172

• IT18190762 | A.M.Karthik | 2021-172

Background and Research Gap

• There are many researches which were conducted in the past by many researchers.
• Most of them focus on classifying the bowler [1], foot overstep no-ball detection [2].
• But none of the researches were implemented on a mobile phone.

​

​

IT18190762 | A.M.Karthik | 2021-172

Research Problem

• As the intervention technology in international cricket is very high especially in bowling.
• But how many of those technologies are used by the domestic cricketers or players in coaching classes ?
• Is it possible to tract records manually ?

IT18190762 | A.M.Karthik | 2021-172

Research Question

• How to identify the bowlers’ length ?
• How to identify the bowlers bowling speed ?
• How to deliver the tracked records ?

​

​

IT18190762 | A.M.Karthik | 2021-172

Objectives

Main Objectives

• To identify a bowler’s bowling length and the balls speed.
• Providing a detailed report.

​

Sub - Objectives

• Getting the video file as input from user
• Identifying the pitching location using TensorFlow
• Fetching the bowling speed using CNN.

​

IT18190762 | A.M.Karthik | 2021-172

System Diagram

IT18190762 | A.M.Karthik | 2021-172

Methodology

• Getting the input from the user as a video file.
• Identifying the object using TensorFlow object detection API.
• Identifying the pitching position using CNN
• Identifying the speed of the moving ball using CNN.
• Providing the trained data to the model for comparison.

IT18190762 | A.M.Karthik | 2021-172

IT18190762 | A.M.Karthik | 2021-172

Technologies to be used

• TensorFlow object detection API – To detect the moving ball
• Convolutional Neural networks – To divide it into frames and find the speed.
• React Native – To develop the mobile application
• Version Control System – GIT
• Project Management- Azure boards

IT18190762 | A.M.Karthik | 2021-172

Work Breakdown Structure

IT18190762 | A.M.Karthik | 2021-172

Gantt Chart

IT18190762 | A.M.Karthik | 2021-172

Functional & Non-Functional Requirements

Functional Requirements

• Creating a standard UI
• Ability to read the added video clip

​

Non-Functional Requirements

• Security – securing data of users
• Reliability- Providing accurate information
• Scalability – Able to use it for a long period of even when the usage is high

​

IT18190762 | A.M.Karthik | 2021-172

References

1. M. N. Al Islam, T. B. Hassan and S. K. Khan, "A CNN-based approach to classify cricket bowlers based on their bowling actions," 2019 IEEE International Conference on Signal Processing, Information, Communication & Systems (SPICSCON), Dhaka, Bangladesh, 2019, pp. 130-134, doi: 10.1109/SPICSCON48833.2019.9065090.
2. A. Z. M. E. Chowdhury, M. S. Rahim and M. A. U. Rahman, "Application of computer vision in Cricket: Foot overstep no-ball detection," 2016 3rd International Conference on Electrical Engineering and Information Communication Technology (ICEEICT), Dhaka, 2016, pp. 1-5, doi: 10.1109/CEEICT.2016.7873086.
3. S. Mane and S. Mangale, "Moving Object Detection and Tracking Using Convolutional Neural Networks," 2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, India, 2018, pp. 1809-1813, doi: 10.1109/ICCONS.2018.8662921.
4. P. Cika, M. Zukal, Z. Libis and M. K. Dutta, "Tracking and speed estimation of selected object in video sequence," 2013 36th International Conference on Telecommunications and Signal Processing (TSP), Rome, Italy, 2013, pp. 881-884, doi: 10.1109/TSP.2013.6614066.

IT18190762 | A.M.Karthik | 2021-172

IT18188196 | A.Narthanan

​

BSc Hons in Information Technology Specializing in Software Engineering

IT18188196 | A. Narthanan | 2021-172

Introduction

• Identify the wicket taking percentage of the user's ball
• Providing suggestion to increase the wicket taking percentage

IT18188196 | A. Narthanan | 2021-172

Background & Research Gap

• Previous researches in cricket domain are based on identifying cricket shots. But no researches are done in cricket domain to identify the length and speed of the ball and provide suggestion to improve the wicket taking percentage.

​

​

​

​

​

IT18188196 | A. Narthanan | 2021-172

Research Problem

• There is no application to identify the wicket taking percentage of the user.
• There is no application to provide suggestion to improve the wicket taking percentage.

​

​

IT18188196 | A. Narthanan | 2021-172

Research Questions

• How to retrieve user's coordinates?
• How to identify the suitable class?
• How to provide the wicket taking percentage to the user?
• How to provide suggestions to increase the wicket taking percentage?

​

​

​

Objectives

 Sub Objectives

• Providing the wicket taking percentage of the user.
• Providing suggestions to improve the wicket taking percentage.

•  Retrieving the user's coordinates and speed of the ball
•  Identifying the relevant class based on the retrieved information.
•  Provide the wicket taking percentage of the identified class.
•  Identifying the closest class with higher taking percentage and provide the coordinates of that class to the user in a detailed view. 

Main Objective

IT18188196 | A. Narthanan | 2021-172

    System Diagram

IT18188196 | A. Narthanan | 2021-172

IT18188196 | A. Narthanan | 2021-172

Methodology

Classification Table

Total No of Classes  =  no of slots X no of speed ranges

​

                                   =        8          X           8

​

                                   =        64

WTC =  ( No of wickets in one classification  / Total No of balls)  X 100

IT18188196 | A. Narthanan | 2021-172

Methodology

Functional and Non -Functional Requirements

Functional Requirements 

• User should be able to upload their bowling videos.
• System should identify the wicket taking percentage of the ball and should provide suggestion to improve the wicket taking percentage. 

​

Non-Functional Requirements

• Accuracy – Since users are dependent on the application to improve their skill, accuracy must be maintained throughout the system. 
• Security – Since users upload their personal information, security must be maintained
• Performance - Since all the inputs are videos, even though high memory power is needed performance of the application should be good. 

IT18188196 | A. Narthanan | 2021-172

Technologies to be Used

• TensorFlow based object detection API – To Detect The Object
• Convolutional Neural Network – To Track the Object
• Open CV
• React Native – For Mobile Application
• Version Control System - GIT

​

​

IT18188196 | A. Narthanan | 2021-172

Work Breakdown Structure

IT18188196 | A. Narthanan | 2021-172

Gantt

Chart

IT18188196 | A. Narthanan | 2021-172

References

1. S. Mane and S. Mangale, "Moving Object Detection and Tracking Using Convolutional Neural Networks," 2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, India, 2018, pp. 1809-1813, doi: 10.1109/ICCONS.2018.8662921.

​

• Enrique J. Fernandez-Sanchez*, Javier Diaz and Eduardo Ros, "Background Subtraction Based on Color and Depth Using Active Sensors", Sensors, vol. 13, pp. 8895-8915, 2013.

​

IT18188196 | A. Narthanan | 2021-172

Thank You�