News Video Indexing Essay

3354 Words Sep 23rd, 2013 14 Pages
News Video Indexing and Retrieval System Using Feature-Based Indexing and Inserted-Caption Detection Retrieval

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News Video Indexing and Retrieval System Using Feature-Based Indexing and InsertedCaption Detection Retrieval
Akshay Kumar Singh, Soham Banerjee, Sonu Kumar and Asst. Prof. Mr. S. Ghatak Computer Science and Engineering, Sikkim Manipal Institute of Technology, Majitar, India.


Abstract—Data compression coupled with the availability of high bandwidth networks and storage capacity have created the overwhelming production of multimedia content, this paper briefly describes techniques for content-based analysis, retrieval and filtering of News Videos and focuses on basic methods for extracting features and information
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Compared with other video features, information in caption text is highly compact and structured, thus is more suitable for video indexing. However, extracting captions embedded in video frames is a difficult task. In comparison to OCR for document images, caption extraction and recognition in videos involves several new challenges. First, captions in videos are often embedded in complex backgrounds, making caption detection much more difficult. Second, characters in captions tend to have a very low resolution since they are usually made small to avoid obstructing scene objects in a video frame . Indexing can be classified into 2 types I: feature based. II: Annotation based.

Here we are going to give you a brief explanation about feature based indexing which can be further classified into: 1. Segment Based. 2. Object Based. 3. Index Based. Finding the required video and its Retrieval can be successfully carried out by identifying and using the best video query scheme among the group of video queries available. Some of the queries scheme for video retrieval that is worth mentioning are: 1. Query content 2. Query using matching 3. Query function 4. Query behavior 5. Query temporal unit, etc. In query content we try to specify the content of video in the query, in order to retrieve the most suitable match video. It is further classified on the type of contents that is used in the query for video retrieval. Semantic (information) query is

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