Spatio-temporal querying in video databases

Koprulu, Mesru; Cicekli, Nihan Kesim; Yazıcı, Adnan

doi:10.1016/j.ins.2003.08.011

Cited by 25 publications

(14 citation statements)

References 25 publications

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“…Modelling of moving objects has become a topic of increasing interest in the area of video databases, as has been studied for example in Koprulu, Cicekli and Yazici (2004), where a video data model that supports spatio-temporal querying in videos, focused on the semantic content of video streams, has been presented. In Li (1997), a way of modelling single object trajectories and relative spatio temporal relations between multiple moving objects based on the Interval Calculus is presented.…”

Section: Qualitative Representation and Reasoning About Space And Timementioning

confidence: 99%

Geographical information systems

Fischer¹

2016

Image Processing and GIS for Remote Sensing

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Section: Qualitative Representation and Reasoning About Space And Timementioning

confidence: 99%

Geographical information systems

Fischer¹

2016

Image Processing and GIS for Remote Sensing

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“…To reduce the work for manual selection and labelling of objects significantly by detecting and tracking the salient objects. Extended Advanced video information system (AVIS) is data model that allows efficient and effective presentation of spatial-temporal properties of objects which focused on the semantic content of video streams [9]. It is object based video data model and application independent.…”

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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“…Due to the complexity of video data, there have been many video data models proposed for video databases [1,2,8,10,15,16,[22][23][24]. Some of the existing work use annotation based modeling.…”

Section: Introductionmentioning

confidence: 99%

“…The video data model [22] identifies spatial properties of objects with rectangular areas (regions) resembling MBRs (minimum bounding rectangles). It is possible to compute and query spatial relationships between two rectangular areas, hence the objects covered by those rectangles.…”

Section: Introductionmentioning

confidence: 99%

“…The model allows us to perform spatio-temporal queries on the video and also provide the inclusion of fuzziness in spatial and spatio-temporal queries. Our video data model [22] previously had only a graphical query interface. Later, the system is integrated with a natural language interface in which the user can express queries in English.…”

Section: Introductionmentioning

confidence: 99%

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Natural language querying for video databases

Erozel¹,

Cicekli²,

Çiçekli³

2008

Information Sciences

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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.

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Spatio-temporal querying in video databases

Cited by 25 publications

References 25 publications

Geographical information systems

Geographical information systems

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

Natural language querying for video databases

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