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Author: Yilmaz, TurgayCOAR Access Rights: metadata only access

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Now showing 1 - 3 of 3
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    Article
    Citation - WoS: 13
    Citation - Scopus: 14
    An Intelligent Multimedia Information System for Multimodal Content Extraction and Querying
    (Springer, 2018) Yazici, Adnan; Koyuncu, Murat; Yilmaz, Turgay; Sattari, Saeid; Sert, Mustafa; Gulen, Elvan
    This paper introduces an intelligent multimedia information system, which exploits machine learning and database technologies. The system extracts semantic contents of videos automatically by using the visual, auditory and textual modalities, then, stores the extracted contents in an appropriate format to retrieve them efficiently in subsequent requests for information. The semantic contents are extracted from these three modalities of data separately. Afterwards, the outputs from these modalities are fused to increase the accuracy of the object extraction process. The semantic contents that are extracted using the information fusion are stored in an intelligent and fuzzy object-oriented database system. In order to answer user queries efficiently, a multidimensional indexing mechanism that combines the extracted high-level semantic information with the low-level video features is developed. The proposed multimedia information system is implemented as a prototype and its performance is evaluated using news video datasets for answering content and concept-based queries considering all these modalities and their fused data. The performance results show that the developed multimedia information system is robust and scalable for large scale multimedia applications.
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    Conference Object
    Citation - WoS: 3
    Flexible Content Extraction and Querying for Videos
    (Springer-verlag Berlin, 2011) Demir, Utku; Koyuncu, Murat; Yazici, Adnan; Yilmaz, Turgay; Sert, Mustafa
    In this study, a multimedia database system which includes a semantic content extractor, a high-dimensional index structure and an intelligent fuzzy object-oriented database component is proposed. The proposed system is realized by following a component-oriented approach. It supports different flexible query capabilities for the requirements of video users, which is the main focus of this paper. The query performance of the system (including automatic semantic content extraction) is tested and analyzed in terms of speed and accuracy.
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    Conference Object
    Citation - WoS: 1
    A Framework for Fuzzy Video Content Extraction, Storage and Retrieval
    (Ieee, 2010) Koyuncu, Murat; Yilmaz, Turgay; Yildirim, Yakup; Yazici, Adnan
    This study presents a new comprehensive framework for semantic content extraction from raw video, storage of the extracted data and retrieval of the stored data. Objects, spatial relations between objects, events and temporal relations between events, which are considered as semantic contents of the video, are extracted automatically to a certain extend with the developed approach. Extraction process is supported by manual annotation when automatic extraction is not satisfactory. The extracted information is stored in an intelligent fuzzy object-oriented database in which the database is enhanced with a fuzzy knowledge-based system. Domain specific deduction rules can be defined to derive new information about semantic contents of the video. The database is also supported by an access structure to increase retrieval efficiency. The proposed framework is capable of handling uncertain data arising from annotation process or video nature.