Automatic detection of salient objects and spatial relations in videos for a video database system
buir.contributor.author | Ulusoy, Özgür | |
buir.contributor.author | Güdükbay, Uğur | |
dc.citation.epage | 1396 | en_US |
dc.citation.issueNumber | 10 | en_US |
dc.citation.spage | 1384 | en_US |
dc.citation.volumeNumber | 26 | en_US |
dc.contributor.author | Sevilmiş, T. | en_US |
dc.contributor.author | Baştan M. | en_US |
dc.contributor.author | Güdükbay, Uğur | en_US |
dc.contributor.author | Ulusoy, Özgür | en_US |
dc.date.accessioned | 2016-02-08T10:07:37Z | |
dc.date.available | 2016-02-08T10:07:37Z | |
dc.date.issued | 2008-10 | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.description.abstract | 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. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T10:07:37Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2008 | en |
dc.identifier.doi | 10.1016/j.imavis.2008.01.001 | en_US |
dc.identifier.issn | 0262-8856 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/22998 | en_US |
dc.language.iso | English | en_US |
dc.publisher | Elsevier BV | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/j.imavis.2008.01.001 | en_US |
dc.source.title | Image and Vision Computing | en_US |
dc.subject | Camera focus estimation | en_US |
dc.subject | Knowledge-base construction | en_US |
dc.subject | Multimedia databases | en_US |
dc.subject | Object labeling | en_US |
dc.subject | Salient object detection and tracking | en_US |
dc.subject | Administrative data processing | en_US |
dc.subject | Data storage equipment | en_US |
dc.subject | Feature extraction | en_US |
dc.subject | Management information systems | en_US |
dc.subject | Video recording | en_US |
dc.subject | Video signal processing | en_US |
dc.subject | Automatic detection | en_US |
dc.subject | Spatio-temporal queries | en_US |
dc.subject | Spatio-temporal relations | en_US |
dc.subject | Video database management | en_US |
dc.subject | Video databases | en_US |
dc.subject | Video processing | en_US |
dc.subject | Database systems | en_US |
dc.subject | Cameras | en_US |
dc.subject | Data processing | en_US |
dc.subject | Data storage | en_US |
dc.subject | Extraction | en_US |
dc.subject | Indexing | en_US |
dc.subject | Information retrieval | en_US |
dc.subject | Information systems | en_US |
dc.subject | Labels | en_US |
dc.subject | Management | en_US |
dc.subject | Storage | en_US |
dc.title | Automatic detection of salient objects and spatial relations in videos for a video database system | en_US |
dc.type | Article | en_US |
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