Search Results

Now showing 1 - 7 of 7
  • Article
    Citation - WoS: 9
    Citation - Scopus: 11
    Food Index: a Multidimensional Index Structure for Similarity-Based Fuzzy Object Oriented Database Models
    (Ieee-inst Electrical Electronics Engineers inc, 2008) Yazici, Adnan; Ince, Cagri; Koyuncu, Murat
    A fuzzy object-oriented data model is a fuzzy logic-based extension to an object-oriented database model that permits uncertain data to be explicitly represented. The fuzzy object-oriented database (FOOD) model is one of the proposed models in the literature to handle uncertainty in object-oriented databases. Several kinds of fuzziness are dealt with in the FOOD model, including fuzziness at attribute level and between object and class and between class and superclass relations. The traditional index structures do not allow efficient access to both crisp and fuzzy objects for fuzzy object-oriented databases since they are not efficient enough in processing both crisp and fuzzy queries. In this study, we propose a new index structure, namely a FOOD index (FI), to deal with different kinds of fuzziness in fuzzy object-oriented databases and to support multidimensional indexing. In this paper, we describe this proposed index structure and show how it supports various types of flexible queries, and evaluate its performance for exact, range, and fuzzy queries.
  • Article
    Citation - WoS: 33
    Citation - Scopus: 41
    Visual and Auditory Data Fusion for Energy-Efficient and Improved Object Recognition in Wireless Multimedia Sensor Networks
    (Ieee-inst Electrical Electronics Engineers inc, 2019) Koyuncu, Murat; Yazici, Adnan; Civelek, Muhsin; Cosar, Ahmet; Sert, Mustafa
    Automatic threat classification without human intervention is a popular research topic in wireless multimedia sensor networks (WMSNs) especially within the context of surveillance applications. This paper explores the effect of fusing audio-visual multimedia and scalar data collected by the sensor nodes in a WMSN for the purpose of energy-efficient and accurate object detection and classification. In order to do that, we implemented a wireless multimedia sensor node with video and audio capturing and processing capabilities in addition to traditional/ordinary scalar sensors. The multimedia sensors are kept in sleep mode in order to save energy until they are activated by the scalar sensors which are always active. The object recognition results obtained from video and audio applications are fused to increase the object recognition performance of the sensor node. Final results are forwarded to the sink in text format, and this greatly reduces the size of data transmitted in network. Performance test results of the implemented prototype system show that the fusing audio data with visual data improves automatic object recognition capability of a sensor node significantly. Since auditory data requires less processing power compared to visual data, the overhead of processing the auditory data is not high, and it helps to extend network lifetime of WMSNs.
  • 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.
  • Article
    Citation - WoS: 16
    Citation - Scopus: 26
    An Intelligent Fuzzy Object-Oriented Database Framework for Video Database Applications
    (Elsevier, 2009) Ozgur, Nezihe Burcu; Koyuncu, Murat; Yazici, Adnan
    Video database applications call for flexible and powerful modeling and querying facilities, which require an integration or interaction between database and knowledge-based 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 study, firstly, we introduce a fuzzy conceptual data model to represent the semantic content of video data. For that purpose, UML (unified modeling language) is utilized and extended to represent uncertain information along with video specific properties. Secondly, we present an intelligent fuzzy object-oriented database framework for video database applications. The introduced fuzzy conceptual model is used in this framework, which provides modeling of complex and rich semantic content and knowledge of video data including uncertainty. Moreover, it supports various flexible queries including (fuzzy) semantic, temporal and (fuzzy) spatial queries, based on the video data model. We think that the presented conceptual data model and the framework can be used for any video database application. (C) 2009 Elsevier B.V. All rights reserved.
  • Article
    Citation - WoS: 7
    Citation - Scopus: 12
    A FUZZY CONCEPTUAL MODEL FOR MULTIMEDIA DATA WITH A TEXT-BASED AUTOMATIC ANNOTATION SCHEME
    (World Scientific Publ Co Pte Ltd, 2009) Kucuk, Dilek; Burcuozgur, N.; Yazici, Adnan; Koyuncu, Murat
    The size of multimedia data is increasing fast due to the abundance of multimedia applications. Modeling the semantics of the data effectively is crucial for proper management of it. In this paper, we present a fuzzy conceptual data model for multimedia data which is also generic in the sense that it can be adapted to all multimedia domains. The model takes an object-oriented approach and it handles fuzziness at different representation levels where fuzziness is inherent in multimedia applications and should be properly modeled. The proposed model also has the nice feature of representing the structural hierarchy of multimedia data as well as the spatial and temporal relations of the data. The model is applied to the news video domain and implemented as a fuzzy multimedia database system where it turns out to be effective in representing the domain and thereby provides an evidence for the general applicability of the model. The model is accompanied by an automatic multimedia annotation scheme which makes use of information extraction techniques on the corresponding multimedia texts.
  • Conference Object
    Fuzzy Semantic Web Architecture for Activity Detection in Wireless Multimedia Sensor Network Applications
    (Atlantis Press, 2019) Ozdin, Ali Nail; Yazici, Adnan; Koyuncu, Murat; Information Systems Engineering
    This study aims to increase the reliability of activity detection in Wireless Multimedia Sensor Networks (WMSNs) by using Semantic Web technologies extended with fuzzy logic. The proposed approach consists of three layers: the sensor layer, the data layer, and the Semantic Web layer. The sensor layer comprises a WMSN comprising sensor nodes with multimedia and scalar sensors. The data layer retrieves and stores data from the sink of WMSN. At the top of the architecture, there is a semantic web layer that includes a semantic web application server, a fuzzy reasoning engine, and a semantic knowledge base. When a new entity is detected at the sensor layer, the associated data produced by the sensors and the sink are collected in the data layer and transmitted to the semantic web application server where the data is converted into subjects, predicates, and objects, according to the ontology conceived and recorded in RDF format. Then, the fuzzy reasoning engine is automatically activated and fuzzy rules are executed to determine if there is an activity in the monitored area. Our implementation confirms that extended semantic Web technologies with fuzzy logic can have a significant impact on the detection of activities in WMSNs.
  • Article
    Citation - WoS: 30
    Citation - Scopus: 48
    A Fusion-Based Framework for Wireless Multimedia Sensor Networks in Surveillance Applications
    (Ieee-inst Electrical Electronics Engineers inc, 2019) Yazici, Adnan; Koyuncu, Murat; Sert, Seyyit Alper; Yilmaz, Turgay
    Multimedia sensors enable monitoring applications to obtain more accurate and detailed information. However, the development of efficient and lightweight solutions for managing data traffic over wireless multimedia sensor networks (WMSNs) has become vital because of the excessive volume of data produced by multimedia sensors. As part of this motivation, this paper proposes a fusion-based WMSN framework that reduces the amount of data to be transmitted over the network by intra-node processing. This framework explores three main issues: 1) the design of a wireless multimedia sensor (WMS) node to detect objects using machine learning techniques; 2) a method for increasing the accuracy while reducing the amount of information transmitted by the WMS nodes to the base station, and; 3) a new cluster-based routing algorithm for the WMSNs that consumes less power than the currently used algorithms. In this context, a WMS node is designed and implemented using commercially available components. In order to reduce the amount of information to be transmitted to the base station and thereby extend the lifetime of a WMSN, a method for detecting and classifying objects on three different layers has been developed. A new energy-efficient cluster-based routing algorithm is developed to transfer the collected information/data to the sink. The proposed framework and the cluster-based routing algorithm are applied to our WMS nodes and tested experimentally. The results of the experiments clearly demonstrate the feasibility of the proposed WMSN architecture in the real-world surveillance applications.