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博碩士論文 etd-0907109-231811 詳細資訊
Title page for etd-0907109-231811
論文名稱
Title
基於語義分鏡分佈觀點之棒球節目統計理解系統
Statistical Understanding of Broadcast Baseball Videos from the Perspective of Semantic Shot Distribution
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
69
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2009-07-06
繳交日期
Date of Submission
2009-09-07
關鍵字
Keywords
運動視訊分析、廣告偵測、語意鴻溝
sport video analysis, semantic gap, commercial detection
統計
Statistics
本論文已被瀏覽 5720 次,被下載 803
The thesis/dissertation has been browsed 5720 times, has been downloaded 803 times.
中文摘要
近年來,由於運動節目的娛樂及廣告效益,運動視訊分析吸引了許多研究者的關注。而運動視訊分析的目的是去定義對於觀眾而言何者是感興趣的部分。現有的方法主要是藉由領域知識來做視訊分解,在過去十年內,運動視訊被廣泛地研究,使用適當的技術達到有效率地的分析。然而,許多一直以來都存在的議題如語意鴻溝以及廣告偵測仍然等待有效的解決方式。在我們的研究中,利用語意分析相鄰投球場景間之距離,在此處我們稱之為鴻溝距離。不同棒球比賽其鴻溝距離則會呈現出獨特的分佈曲線,藉此我們可以利用鴻溝距離來分析每場比賽的本質的意義。
Abstract
Recently, sport video analysis has attracted lots of researcher’s attention because of its entertainment applications and potential commercial benefits. Sport video analysis aims to identify what trigged the excitement of audiences. Previous methods rely mainly on video decomposition using domain specific knowledge. The study and development of suitable and efficient techniques for sport video analysis have been conducted extensively over the last decade. However, several longstanding challenges, such as semantic gap and commercial detection are still waiting to be solved. In this work, we consider using semantic analysis to adjacent pitch scenes which we called “gap length.” Difference kinds of baseball games show its specific distribution for gap length, which depicts the potential significance of each baseball game.
目次 Table of Contents
CHAPTER 1 Introduction…………………………………………………………...1
1.1 Overview of Sports Video…………………………………………………1
1.2 Overview of Baseball Video…………..……………………………………5
1.3 Motivation……………………………………………………………….....9
1.4 The Organization of the Thesis…………………………………………...11
CHAPTER 2 Background Review………………………………………………..12
2.1 Playfield Detection………………………………………………..…….14
2.2 Ball Trajectory Tracking……………………...……………………….....16
2.3 Highlight Event Detection………………………………………………20
CHAPTER 3 Pitch Shot Extraction for Semantic Gap Length Analysis….……...26
3.1 Automatic Pitch Shot Extraction…..........……………………………...29
3.1.1 Adaptive Shot Change Detection.......…………………..………......30
3.1.2 Commercial Exclusion.......………………………………..………...32
3.1.3 Non-pitch Shot Exclusion………………..…….………..………...34
3.1.4 Self-validation………........………………………………..………...35
3.1.5 Pitch Shot Extraction ……………………………………..………...37
3.2 Semantic Analysis of Gap Length in each Half Inning ………………...38
CHAPTER 4 Experimental Results…………........................................................42
4.1 Experimental Results of Automatic Pitch Shot Extraction.......................42
4.2 Experimental Results of Gap Length and Intensity Distribution…….….....47
CHAPTER 5 Conclusions and Future Work…………...…………………………….53
5.1 Conclusions…………………………………………………………….....53
5.2 Future Work……………………………………………………………….55
Bibliography………………………………………………………………………….56
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