BilVideo: Design and Implementation of a Video Database Management System

Dönderler, Mehmet Emin; Şaykol, Ediz; Arslan, Ümüt; Ulusoy, Özgür; Güdükbay, Uğur

doi:10.1007/s11042-005-2715-7

Cited by 48 publications

(32 citation statements)

References 35 publications

(36 reference statements)

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“…Video databases are among those applications, which require powerful and flexible modeling and querying facilities. There are research efforts on utilizing knowledge-base systems or rule-based approach for video databases [32,33,34,35,48,49]. Among these, [33] defines spatial inference rules which allow to deduce heterogeneous spatial relations by using existing ones.…”

Section: Introductionmentioning

confidence: 99%

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An intelligent fuzzy object-oriented database framework for video database applications

Ozgur

Koyuncu

Yazıcı

2009

Fuzzy Sets and Systems

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Video database applications call for flexible and powerful modeling and querying facilities, which require an integration or interaction between database and knowledge base technologies. It is also necessary for many real life video database applications to incorporate uncertainty, which naturally occurs due to the complex and subjective semantic content of video data. In this thesis study, firstly, a fuzzy conceptual data model is introduced to represent the semantic content of video data. UML (Unified Modeling Language) is utilized and extended to represent uncertain information along with video specific properties at the conceptual level. Secondly, an intelligent fuzzy object-oriented database framework is presented for video database applications. The introduced fuzzy conceptual model is mapped to the presented framework, which is an adaptation of the previously proposed IFOOD architecture. The framework provides modeling and querying of complex and rich semantic content and knowledge of video data including uncertainty.Moreover, it allows (fuzzy) semantic, temporal, (fuzzy) spatial, hierarchical, regional and trajectory queries, based on the video data model. We think that the presented conceptual data model and framework can be adapted to any application domain related to video databases. Keywords

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Section: Introductionmentioning

confidence: 99%

“…Among these, [33] defines spatial inference rules which allow to deduce heterogeneous spatial relations by using existing ones. In [34,49], an architecture for a video database application supporting spatio-temporal and semantic querying is proposed. The spatial relations are stored as Prolog facts in a knowledge base.…”

Section: Introductionmentioning

confidence: 99%

An intelligent fuzzy object-oriented database framework for video database applications

Ozgur

Koyuncu

Yazıcı

2009

Fuzzy Sets and Systems

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show abstract

“…BilVideo is the video database management system provides full support for queries on spatio-temporal, low level features and semantic on the video data [7] [8]. It is domain independent and to handle the spatio-temporal queries a knowledge-base is used that consists of a fact-base and comprehensive set of rules which reduce the number of facts.…”

Section: Literature Surveymentioning

confidence: 99%

Fuzzy Ontology and Rule based Model for Automatic Semantic Content Extraction from Videos using k-Means Algorithm

Nikam¹,

Nandwalkar²

2015

IJCA

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Video based applications disclosed need for efficiently extracting and modeling the video contents. The video features can be classified into normal data, relative features and logic content. Semantic level understanding is required for core content of video. So to get video content automatic semantic content framework is proposed. In proposed system a semantic content extraction system that allows the user to query and regain objects, events, and concepts that are extracted automatically. VISCOM is a video semantic content model which contains classes and relations between classes. Objects and events are represented by some VISCOM classes and other classes are used in the automatic semantic content extraction framework. VISCOM classes collect the semantic content types and relations.Ontology based fuzzy video data semantic model which uses spatial and temporal relations in event and concept definition is proposed. Extracted objects from consecutive representative frames are processed to extract temporal relations. Additional rules to lower spatial relation computation cost and to define some difficult situations more successfully are used. To extract objects from video we apply k-means clustering algorithm. By, which we get the more relevant objects related to user query.

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“…Although there has been some study on using object-oriented databases for storing and retrieving images (Dönderler, 2005;Grosky and Stanchev, 2001) not much investigation has been done using the object oriented approach in conjunction with the concept of object versioning. To show the potential benefit of the approach, it is sufficient to consider a typical CCTV monitoring a car park where the background of the scene does not change and the background object can be stored in the database as a generic object, any changes to the scene, for instance a car entering a car park, can be stored in the database as versions instead of storing the whole object, background and changes, again (for simplicity at this point we are assuming stable weather conditions).…”

Section: Object Oriented Model For the Management Of Digital Imagesmentioning

confidence: 99%

An Integrated Model for the Versioning of Image Objects

Khaddaj¹

2010

Journal of Computer Science

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Problem statement: The efficient management and retrieval of the enormous volumes of information generated by many imaging applications is still a challenging problem. Approach: In this study we are particularly interested with the use of object oriented techniques for the management of digital images. Indeed, it is widely accepted that the use of data abstraction in object oriented modeling enables real world objects to be well represented in information systems. Results: Object orientation is well suited for digital images management systems, which require the ability to handle multiple type content. This study proposes a conceptual model, based on object versioning techniques, which represents the semantics in order to allow the continuity and pattern of changes of images to be determined over time. Conclusion/Recommendations: By first storing a generic image object and then storing any changes to the object as versions, a major reduction in storage can be achieved.

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BilVideo: Design and Implementation of a Video Database Management System

Cited by 48 publications

References 35 publications

An intelligent fuzzy object-oriented database framework for video database applications

An intelligent fuzzy object-oriented database framework for video database applications

Fuzzy Ontology and Rule based Model for Automatic Semantic Content Extraction from Videos using k-Means Algorithm

An Integrated Model for the Versioning of Image Objects

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