We present methods and systems for authoring by linking---generating multimedia documents by creating richly typed links between component media assets. As an example we describe our Sticky Video functionality in the MEERCAT system for linking photo and video media. We do so within the framework of a hierarchy of possible link-based authoring systems from manual to programmatic link creation and document authoring. We discuss mechanisms for accurately situating links between rich media components and flexibly typing those links to allow both better human information browsing and searching and automatic authoring. We describe issues in realtime distributed authoring and the use of metadata channels. In particular we present the concept of authoring by meeting, the automatic creation of multimedia documents from business meetings.
We present a prototype system for managing and searching collections of personal digital images. The system allows the collection to be stored across a mixture of local and remote computers and managed seamlessly. It provides multiple ways of organizing and viewing the same collection. It also provides a search function that uses features based on face detection and low-level color, texture and edge features combined with digital camera capture settings to provide high-quality search that is computed at the server but available from all other networked devices accessing the photo collection. Evaluations of the search facility using human relevancy experiments are provided.
In this paper, we describe a system for performing browsing and retrieval on a collection of web images and associated text on an HTML page. Browsing is combined with retrieval to help a user locate interesting portions of the corpus, without the need to formulate a query well matched to the corpus. Multi-modal information, in the form of text surrounding an image and some simple image features, is used in this process. Using the system, a user progressively narrows a collection to a small number of elements of interest, similar to the Scatter/Gather system developed for text browsing. We have extended the Scatter/Gather method to use multi-modal features. With the use of multiple features, some collection elements may have unknown or undefined values for some features; we present a method for incorporating these elements into the result set. This method also provides a way to handle the case when a search is narrowed to a part of the space near a boundary between two clusters. A number of examples illustrating our system are provided.
KEYWORDS: Video, RGB color model, Databases, Video processing, Image segmentation, Video compression, Computing systems, Standards development, Data conversion, Computer science
As a first step to creating a video database, a video sequence has to be segmented into several subsequences based on significant changes in the scene. This enables the media user to identify the whole or a part of the sequence and to retrieve scenes of interest from a large video database. Researchers in the past have used a histogram based inter-frame difference approach to identify significant scene changes. To determine which is the best color coordinate system for video indexing, we have evaluated the histogram based indexing method using different color coordinate systems -- RGB, HSV, YIQ, L*a*b*, L*u*v* & Munsell -- and compared the results for accuracy of indexing with reference to subjective indexing. Since it is difficult to determine the exact threshold value to obtain reasonably good results, we also propose a vide segmenting method called hierarchical histogram based indexing that segments a video sequence into several levels of subsequences using different levels of threshold.
KEYWORDS: Databases, Video, Information visualization, Image retrieval, Computing systems, Prototyping, Visualization, Video processing, Geographic information systems, Data processing
We present a prototype video database system designed to accept video sequences as well as still images. The system indexes these sequences based on scene changes, creates a primitive structure of these sequences, and searches this structure for queried objects using specific color features. A video sequence input to the database is first indexed into subsequences using a color histogram difference method. A hierarchical structure is created by thresholding the sequences at various levels of inter-frame difference. For every subsequence that is identified, the first frame in that subsequence, the representative frame, is entered into the database. The system then automatically generates a description for the frame in terms of its color histogram features. Subsequently, the video sequence may be searched for objects (specified as regions of other video sequence frames or still images) using color similarity matching.
Conference Committee Involvement (1)
Imaging and Printing in a Web 2.0 World
19 January 2010 | San Jose, California, United States
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