臺灣博碩士論文加值系統

現代人生活忙碌，想要每天都有一個固定的時間收看新聞已經是一件非常不容易的事，況且每天都發生那麼多大大小小的新聞，有社會新聞、娛樂新聞、政治新聞、體育新聞等等，如何可以在短時間內將一天所發生的新聞都輕鬆的瀏覽一遍，再選擇您所想要深入了解的新聞呢?我們在這裡提出了一個想法，就是利用影音多媒體內容分析來建立一段影片的索引與搜尋。
如果想要在一段新聞出分辨出是主撥撥報新聞的片段或是新聞片段，可以經由搜尋主撥的人臉這個動作來分辨出現在這個片段是主撥撥報新聞的片段或是新聞片段，因為現有的人臉辨識方法都需要大量複雜的數學運算才能有效的辨識出人臉，如果想要完成Real-Time 的處理，硬體需求可能會很高。
在本研究中，我們提出一個新的且計算量較小的方法來判別主撥是否存在，這個方法主要著重於人臉膚色偵測，主撥衣服顏色偵測以及利用主撥撥報新聞與新聞片段切換時所產生的一些條件來研究這個題目。

In this thesis, we designed a scheme for TV news segmentation via video content analysis techniques and explored the efficient visual features. The scheme can be divided into three parts, such as anchorperson shot change detection based on skin color, probable anchorperson segment detection and anchorperson detection.
An anchorperson shot surely contains face region, and this feature is informative and important for anchorperson shot change detection. In order to reduce computational complexity for face detection, we only use skin color information as the major tool for searching face region. Otherwise, the anchorperson shot time should be shorter than that of a report shot time. As a result, we make use of the properties above also called time constraint method to discover the probable anchorperson segments. However, the probable anchorperson segment might involve the report segment, it will effect the detect precision. Here, we exploit the region histogram based on non-skin color method to exclude report segments.
According to simulation results, our proposed method can efficiently decompose TV news into anchorperson shots and report segments. The proposed method can easily apply to software and hardware based personal video recorder for efficiently accessing the large amount of TV news video in the near future.

1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . 1
1.2 Background . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Organization of the thesis and chapter overview . . . 5
2 Skin region processing 7
2.1 Substitute for face detection algorithm . . . . . . . . . 7
2.2 Color space transformation . . . . . . . . . . . . . . 7
2.3 Skin-color decision rule . . . . . . . . . . . . . . 11
2.4 Comparisions of skin-color region . . . . . . . . . . 13
2.5 Skin region processing . . . . . . . . . . . . . . . 15
3 Tv news segmentation system 20
3.1 System overview . . . . . . . . . . . . . . . . . . . 20
3.2 Shot change detection based on skin-color . . . . . . 21
3.2.1 Shot change detection . . . . . . . . . . . . . . 21
3.2.2 Skin-color based and time constraint . . . . . . 22
3.3 Excluding the report segment from probable anchorper-
son segments . . . . . . . . . . . . . . . . . . . . . . 26
3.3.1 Region histogram based on non-skin color . . . 26
3.3.2 Self-recognizing algorithm . . . . . . . . . . . . 28
3.3.3 Modi‾cation pattern algorithm . . . . . . . . . 31
3.4 News story segmentation . . . . . . . . . . . . . . . 35
3.4.1 Anchorperson detection . . . . . . . . . . . . . 35
4 Experimental results 37
4.1 Shot change detection based on skin color . . . . . . 37
4.2 Proposed scheme evaluation . . . . . . . . . . . . . . . 41
5 Conclusions and future works 52

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