Browsing by Subject "Video databases"

Now showing 1 - 6 of 6

Open Access
Automatic detection of salient objects and spatial relations in videos for a video database system
(Elsevier BV, 2008-10) Sevilmiş, T.; Baştan M.; Güdükbay, Uğur; Ulusoy, Özgür
Multimedia databases have gained popularity due to rapidly growing quantities of multimedia data and the need to perform efficient indexing, retrieval and analysis of this data. One downside of multimedia databases is the necessity to process the data for feature extraction and labeling prior to storage and querying. Huge amount of data makes it impossible to complete this task manually. We propose a tool for the automatic detection and tracking of salient objects, and derivation of spatio-temporal relations between them in video. Our system aims to reduce the work for manual selection and labeling of objects significantly by detecting and tracking the salient objects, and hence, requiring to enter the label for each object only once within each shot instead of specifying the labels for each object in every frame they appear. This is also required as a first step in a fully-automatic video database management system in which the labeling should also be done automatically. The proposed framework covers a scalable architecture for video processing and stages of shot boundary detection, salient object detection and tracking, and knowledge-base construction for effective spatio-temporal object querying. © 2008 Elsevier B.V. All rights reserved.
Open Access
BilVideo: Design and implementation of a video database management system
(Springer, 2005) Dönderler, M. E.; Şaykol, E.; Arslan, U.; Ulusoy, Özgür; Güdükbay, Uğur
With the advances in information technology, the amount of multimedia data captured, produced, and stored is increasing rapidly. As a consequence, multimedia content is widely used for many applications in today's world, and hence, a need for organizing this data, and accessing it from repositories with vast amount of information has been a driving stimulus both commercially and academically. In compliance with this inevitable trend, first image and especially later video database management systems have attracted a great deal of attention, since traditional database systems are designed to deal with alphanumeric information only, thereby not being suitable for multimedia data. In this paper, a prototype video database management system, which we call BilVideo, is introduced. The system architecture of BilVideo is original in that it provides full support for spatio-temporal queries that contain any combination of spatial, temporal, object-appearance, external-predicate, trajectory-projection, and similarity-based object-trajectory conditions by a rule-based system built on a knowledge-base, while utilizing an object-relational database to respond to semantic (keyword, event/activity, and category-based), color, shape, and texture queries. The parts of BilVideo (Fact-Extractor, Video-Annotator, its Web-based visual query interface, and its SQL-like textual query language) are presented, as well. Moreover, our query processing strategy is also briefly explained. © 2005 Springer Science + Business Media, Inc.
Open Access
An efficient query optimization strategy for spatio-temporal queries in video databases
(2002-07) Ünel, Gülay
The interest for multimedia database management systems has grown rapidly due to the need for the storage of huge volumes of multimedia data in computer systems. An important building block of a multimedia database system is the query processor, and a query optimizer embedded to the query processor is needed to answer user queries efficiently. Query optimization problem is widely studied for conventional database systems, however it is a new research area for multimedia database systems. Due to the differences in query processing strategies, query optimization techniques used in multimedia database systems are different from those used in traditional databases. In this thesis, query optimization problem in video database systems is outlined and a query optimization strategy is proposed as a solution to this problem. Reordering algorithms, to be applied on query execution tree, are also described. Finally, the performance results obtained by testing the proposed algorithms are presented.
Open Access
Natural language querying for video databases
(Elsevier Inc., 2008-06-15) Erozel, G.; Cicekli, N. K.; Cicekli, I.
The video databases have become popular in various areas due to the recent advances in technology. Video archive systems need user-friendly interfaces to retrieve video frames. In this paper, a user interface based on natural language processing (NLP) to a video database system is described. The video database is based on a content-based spatio-temporal video data model. The data model is focused on the semantic content which includes objects, activities, and spatial properties of objects. Spatio-temporal relationships between video objects and also trajectories of moving objects can be queried with this data model. In this video database system, a natural language interface enables flexible querying. The queries, which are given as English sentences, are parsed using link parser. The semantic representations of the queries are extracted from their syntactic structures using information extraction techniques. The extracted semantic representations are used to call the related parts of the underlying video database system to return the results of the queries. Not only exact matches but similar objects and activities are also returned from the database with the help of the conceptual ontology module. This module is implemented using a distance-based method of semantic similarity search on the semantic domain-independent ontology, WordNet. © 2008 Elsevier Inc. All rights reserved.
Open Access
Query processing for an MPEG-7 compliant video database
(2008) Çam, Hayati
Based on the recent advancements in multimedia, communication, and storage technologies, the amount of audio-visual content stored is increased dramatically. The need to organize and access the growing multimedia content led researchers to develop multimedia database management systems. However, each system has its own way of describing the multimedia content that disables interoperability among other systems. To overcome this problem and to be able to standardize the description of audio-visual content stored in those databases, MPEG-7 standard has been developed by MPEG (Moving Picture Experts Group). In this thesis, a query language and a query processor for an MPEG-7 compliant video database system is proposed. The query processor consists of three main modules: query parsing module, query execution module, and result fusion module. The query parsing module parses the XML based query and divides it into subqueries. Each sub-query is then executed with related query execution module and the final result is obtained by fusing the results of the sub-queries according to user defined weights. The prototype video database system BilVideo v2.0, which is formed as a result of this thesis work, supports spatio-temporal and low level feature queries that contain any weighted combination of keyword, temporal, spatial, trajectory, and low level visual feature (color, shape and texture) queries. Compatibility with MPEG-7, low-level visual query support, and weighted result fusion feature are the major factors that highly differentiate between BilVideo v2.0 and its predecessor, BilVideo.
Open Access
A semantic data model and query language for video databases
(2002) Arslan, Umut
Advances in compression techniques, decreasing cost of storage, and high—speed transmission have facilitated the way video is created, stored and distributed. As a consequence, video is now being used in many application areas. The increase in the amount of video data deployed and used in today’s applications not only caused video to draw more attention as a multimedia data type, but also led to the requirement of efﬁcient management of video data. Management of video data paved the way for new research areas, such as indexing and retrieval of videos with respect to their spatio—temporal, visual and semantic contents. In this thesis, semantic content of video is studied, where video metadata, activities, actions and objects of interest are considered within the context of video semantic content. A data model is proposed to model video semantic content, which is extracted from video data by a video annotation tool. A video query language is also provided to support semantic queries on video data. The outcome of this thesis work will be used in a project, which proposes a video database system architecture with spatio—temporal, object—trajectory and object—apperance query facilities so as to build a complete video search system to query video data by its spatio—temporal, visual and semantic features.