Özetçe-Bu makalede, kablosuz çoklu ortam sensor ağlarında, kamera tarafından tespit edilen hedeflerin personel katkısına gerek olmadan otomatik olarak tanımlaması amacıyla uygulanacak işlemler incelenmiştir. Çalışma kapsamında video sensörler tarafından elde edilen çoklu ortam verisinden hedefin sınıflandırması amacıyla çıkarılacak özellikler ve bu özelliklerden hedefin tipinin belirlenmesi için uygulanacak yöntemler önerilmektedir. Önerilen yöntemlerin kullanımı Matlab programı ile geliştirilen bir uygulama ile test edilmiş ve sonuçları sunulmuştur. Anahtar Kelimeler -Video; Sensör; Özellik Ç ıkarımı; Sınıflandırma.Abstract-In this paper, it is investigated the processes for automatic identification of the targets without personnel intervention in wireless multimedia sensor networks. Methods to extract the features of the object from the multimedia data and to classify the target type based on the extracted features are proposed within the scope of this study. The success of the proposed methods are tested by implementing a Matlab application and the results are presented in this paper
Video texts -if available-constitute a valuable source for automatic semantic annotation of large video archives. In this paper, we present our attempts towards the improvement of a text-based semantic annotation and retrieval system for Turkish news videos through automatic Web alignment and event extraction. The results of our initial experiments turn out to be promising and these two features are incorporated into the existing system. Although the ideas of automatic Web alignment and text-based event extraction are not the novel contributions of the current paper, to the best of our knowledge, their first implementation and employment in a system for Turkish news videos is a significant contribution to related work on videos in lesser studied languages such as Turkish. Also overviewed in the current paper is the prospective version of the system encompassing components for several other tasks including topic segmentation, keyphrase extraction, news categorization and summarization to enhance the overall system.
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