Efficient and effective handling of video documents depends on the availability of indexes. Manual indexing is unfeasible for large video collections. In this paper we survey several methods aiming at automating this time and resource consuming process. Good reviews on single modality based video indexing have appeared in literature. Effective indexing, however, requires a multimodal approach in which either the most appropriate modality is selected or the different modalities are used in collaborative fashion. Therefore, instead of separately treating the different information sources involved, and their specific algorithms, we focus on the similarities and differences between the modalities. To that end we put forward a unifying and multimodal framework, which views a video document from the perspective of its author. This framework forms the guiding principle for identifying index types, for which automatic methods are found in literature. It furthermore forms the basis for categorizing these different methods.

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Indexing video data is essential for providing content based access. In this paper, we consider how database technology can offer an integrated framework for modeling and querying video data. As many concerns in video (e.g., modeling and querying) are also found in databases, databases provide an interesting angle to attack many of the problems. From a video applications perspective, database systems provide a nice basis for future video systems. More generally, database research will provide solutions to many video issues even if these are partial or fragmented. From a database perspective, video applications provide beautiful challenges. Next generation database systems will need to provide support for multimedia data (e.g., image, video, audio). These data types require new techniques for their management (i.e., storing, modeling, querying, etc.). Hence new solutions are significant. This paper develops a data model and a rule-based query language for video content based indexing a...

Multimedia information retrieval is a challenging problem because multimedia information is not inherently structured. Jabber is an experimental system that attempts to bring some structure to this task. Jabber allows users to retrieve records of videoconferences based upon the concepts discussed. In this paper we introduce ConceptFinder, a sub-system within Jabber, and show how it is able to process the spoken text of a meeting into meeting topics. ConceptFinder can make subtle distinctions among different senses of the same words, and is able to summarize a set of related words, giving a name to each topic. Users can then use this name to query or browse the stored multimedia, through Jabber's user interface. By presenting information that closely matches a user's expectations, the challenge of multimedia retrieval is rendered more tractable. Keywords Multimedia indexing, information retrieval and browsing, concept clustering INTRODUCTION Multimedia holds tremendous appeal becau...

One of the key aspects of videos is the temporal relationship between video frames. In this paper we propose a tree-based model for specifying the temporal semantics of video data. We present a unique wayofintegrating our video model into an object database management system which has richmultimedia temporal operations. We further showhow temporal histories are used to model video data, explore the video objectbase using object-oriented techniques. Such a seamless integration gives a uniform interface to end users. The integrated video objectbase management system supports a broad range of temporal queries.

We propose a novel architecture for a video database system

In our earlier work, we proposed an architecture for a Web-based Video Database Management System (VDBMS) providing an integrated support for spatio-temporal and semantic queries. In this paper, we focus on the task of spatio-temporal query processing, and also propose an SQL-like video query language that has the capability to handle a broad range of spatio-temporal queries. The language is rule-based in that it allows users to express spatial conditions in terms of Prolog-type predicates.

A constraint of existing content-based video data models is that each modeled semantic description must be associated with time intervals exactly within which it happens and semantics not related to any time interval are not considered. Consequently, users are provided with limited query capabilities. This paper is aimed at developing a novel model with two innovations: (1) Semantic contents not having related time information can be modeled as ones that do# (2) Not only the temporal feature of semantic descriptions, but also the temporal relationships among themselves are components of the model. The query system is by means of reasoning on those relationships.

It's a long time since video post production became digital, yet the issue of collaborative video authoring has not been seriously investigated so far.

Declarative query languages are an important feature of database management systems and have played an important role in their success. As database management technology enters the multimedia information system area, the availability of special-purpose query languages for multimedia applications will be equally important. In this report, we survey multimedia query languages and query models. Particularly, we look at those systems from the point of view of well-defined queries, fuzzy queries, visual queries, and query presentations. Several research issues, such as generic multimedia query languages, incremental queries, fuzzy queries, spatio-temporal queries, feature storage and organization, are also identified. In our opinion these are vital issues for the success and development of a multimedia query language.