Content-based news video story segmentation and video retrieval

2002 ◽  
Author(s):  
Huayong Liu ◽  
Dongru Zhou
Keyword(s):  
Video Retrieval ◽  
Story Segmentation ◽  
News Video

scholarly journals Assessing user behaviour in news video retrieval

2005 ◽  
Vol 152 (6) ◽  
pp. 911 ◽  
Author(s):  
L. Hollink ◽  
G.P. Nguyen ◽  
D.C. Koelma ◽  
A.Th. Schreiber ◽  
M. Worring
Keyword(s):  
Video Retrieval ◽  
User Behaviour ◽  
News Video

scholarly journals News Story Retrieval Based on Textual Query

2020 ◽  
Vol 9 (3) ◽  
pp. 2918-2922
Keyword(s):  
Language Processing ◽  
Video Retrieval ◽  
News Story ◽  
Indian Language ◽  
Text Data ◽  
News Stories ◽  
News Video ◽  
Text Query ◽  
Percent Accuracy ◽  
Value Decomposition

This paper presents news video retrieval using text query for Gujarati language news videos. Due to the fact that Broadcasted Video in India is lacking in metadata information such as closed captioning, transcriptions etc., retrieval of videos based on text data is trivial task for most of the Indian language video. To retrieve specific story based on text query in regional language is the key idea behind our approach. Broadcast video is segmented to get shots representing small news stories. To represent each shot efficiently, key frame extraction using singular value decomposition and rank of matrix is proposed. Text is extracted from keyframes for further indexing data. Next task is to process text using natural language processing steps like tokenization, punctuation and extra symbols removal as well as stemming of words to root words etc. Due to unavailability of stemming and other methods of preprocessing of text in Guajarati language, we have given basic stemming technique to reduce dictionary size for efficient indexing of text data. With proposed system 82.5 percent accuracy is achieved on Gujarati news video dataset ETV.

Automatic Topics Segmentation for News Video by Clustering of Histogram of Orientation Gradients Faces

2021 ◽  
Vol 18 (3) ◽  
Author(s):  
Mounira Hmayda ◽  
Ridha Ejbali ◽  
Mourad Zaied
Keyword(s):  
Video Retrieval ◽  
Multimedia Data ◽  
Single Linkage ◽  
Social Community ◽  
Video Sharing ◽  
News Program ◽  
Tv News ◽  
Large Audience ◽  
News Video ◽  
Pertinent Information

TV stream is a major source of multimedia data. The proposed method aims to enable a good exploitation of this source of video by multimedia services social community, and video-sharing platforms In this work, we propose an approach to the automatic topics segmentation of news video. The originality of the approach is the use of Clustering of Histogram of Orientation Gradients (HOG) faces as prior knowledge. This knowledge is modeled as images which governs the structuring of TV stream content. This structuring is carried out on two levels. The first consists in the identification of anchorperson by Single-Linkage Clustering of HOG faces. The second level aims to identify the topics of news program due to the large audience because of the pertinent information they contain. Experiments comparing the proposed technique to similar works were carried out on the TREC Video Retrieval Evaluation (TRECVID) 2003 database. The results show significant improvements to TV news structuring exceeding 96 %.

Large-scale news video retrieval via visualization

2006 ◽  
Author(s):  
Hangzai Luo ◽  
Jianping Fan ◽  
Yuli Gao ◽  
William Ribarsky ◽  
Shin'ichi Satoh
Keyword(s):  
Large Scale ◽  
Video Retrieval ◽  
News Video
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