Enhancing the Functionality of Interactive TV with Content-Based Multimedia Analysis.
ABSTRACT In this paper we describe how content-based analysis techniques can be used to provide much greater functionality to the users of an interactive TV (iTV) device. We describe several content-based multimedia analysis techniques and how some of these can be exploited in the iTV domain, resulting in the provision of a set of powerful functions for iTV users. To validate our ideas, we introduce an iTV application we developed which incorporates some of these techniques into a simple set of user features, in order to demonstrate the usefulness of content-based techniques for iTV. The contribution of this paper is not to provide an in-depth discussion on each of the individual content-based techniques, but rather to show how many of these powerful technologies can be incorporated into an interactive TV system.
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ABSTRACT: The paper presents an approach to segmenting broadcast TV news programmes automatically into individual news stories. We first segment the programme into individual shots, and then a number of analysis tools are run on the programme to extract features to represent each shot. The results of these feature extraction tools are then combined using a support vector machine trained to detect anchorperson shots. A news broadcast can then be segmented into individual stories based on the location of the anchorperson shots within the programme. We use one generic system to segment programmes from two different broadcasters, illustrating the robustness of our feature extraction process to the production styles of different broadcasters.O'Hare, Neil and Smeaton, Alan F. and Czirjek, Csaba and O'Connor, Noel E. and Murphy, Noel (2004) A generic news story segmentation system and its evaluation. In: ICASSP 2004 - IEEE International Conference on Acoustics, Speech, and Signal Processing, 17-21 May 2004, Montreal, Quebec, Canada. 01/2004;
Article: Video Abstracting[show abstract] [hide abstract]
ABSTRACT: We all know what the abstract of an article is: a short summary of a document, often used to preselect material relevant to the user. The medium of the abstract and the document are the same, namely text. In the age of multimedia, it would be desirable to use video abstracts in very much the same way: as short clips containing the essence of a longer video, without a break in the presentation medium. However, the state of the art is to use textual abstracts for indexing and searching large video archives. This media break is harmful since it typically leads to considerable loss of information. For example it is unclear at what level of abstraction the textual description should be; if we see a famous politician at a dinner table with a group of other politicians, what should the text say? Should it specify the names of the people, give their titles, specify the event, or just describe the scene as if it were a painting, emphasizing colors and geometry? An audio-visual abstract, to be interpreted by a human user, is semantically much richer than a text. We define a video abstract to be a sequence of moving images, extracted from a longer video, much shorter than the original, and preserving the essential message of the original.09/2000;
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ABSTRACT: Presents a review of 200 references in content-based image retrieval. The paper starts with discussing the working conditions of content-based retrieval: patterns of use, types of pictures, the role of semantics, and the sensory gap. Subsequent sections discuss computational steps for image retrieval systems. Step one of the review is image processing for retrieval sorted by color, texture, and local geometry. Features for retrieval are discussed next, sorted by: accumulative and global features, salient points, object and shape features, signs, and structural combinations thereof. Similarity of pictures and objects in pictures is reviewed for each of the feature types, in close connection to the types and means of feedback the user of the systems is capable of giving by interaction. We briefly discuss aspects of system engineering: databases, system architecture, and evaluation. In the concluding section, we present our view on: the driving force of the field, the heritage from computer vision, the influence on computer vision, the role of similarity and of interaction, the need for databases, the problem of evaluation, and the role of the semantic gapIEEE Transactions on Pattern Analysis and Machine Intelligence 01/2001; · 4.80 Impact Factor