An intelligent multimedia information system for multimodal content extraction and querying

Date

2018-01-01

Author

Yazıcı, Adnan
KOYUNCU, Murat
Yilmaz, Turgay
Sattari, Saeid
SERT, MUSTAFA
Gulen, Elvan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

Subject Keywords

Multimedia applications, Prototype multimedia system, Multimedia platform, Video data, Semantic content extraction, Multimedia databases, Multimedia data fusion, Multimedia querying, Multimedia information retrieval

URI

https://hdl.handle.net/11511/49124

Collections

Department of Computer Engineering, Article