Computer Vision in Sports

Computer Vision in Sports edited by Thomas B. Moeslund, Graham Thomas, Adrian Hilton.

The first book of its kind devoted to this topic, this comprehensive text/reference presents state-of-the-art research and reviews current challenges in the application of computer vision to problems in sports. Opening with a detailed introduction to the use of computer vision across the entire life...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Moeslund, Thomas B. (Editor), Thomas, Graham (Editor), Hilton, Adrian (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2014.
Edition:1st ed. 2014.
Series:Advances in Computer Vision and Pattern Recognition,
Springer eBook Collection.
Subjects:
Optical data processing.
Artificial intelligence.
Application software.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Introduction to the Use of Computer Vision in Sports
  • Part I: Where is the Ball?
  • Ball Tracking for Tennis Video Annotation
  • Plane Approximation-Based Approach for 3D Reconstruction of Ball Trajectory for Performance Analysis in Table Tennis
  • On-Field Testing and Evaluation of a Goal-Line Technology System
  • Part II: Where Are the Players?
  • Occlusion Detection via Structured Sparse Learning for Robust Object Tracking
  • Detecting and Tracking Sports Players with Random Forests and Context-Conditioned Motion Models
  • Geometry Reconstruction of Players for Novel-View Synthesis of Sports Broadcasts
  • Estimating Athlete Pose from Monocular TV Sports Footage
  • Part III: What Are They Playing?
  • Action Recognition in Realistic Sports Videos
  • Classification of Sports Types Using Thermal Imagery
  • Event-Based Sports Videos Classification Using HMM Framework
  • Part IV: What's Going On?
  • Representing Team Behaviours from Noisy Data Using Player Role
  • Recognizing Team Formation in American Football
  • Real-Time Event Detection in Field Sport Videos.

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