Browsing by Author "Can, Tolga"

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    Bilkent university at TRECVID 2006
    (National Institute of Standards and Technology, 2006-11) Aksoy, Selim; Duygulu, Pınar; Akçay, Hüseyin Gökhan; Ataer, Esra; Baştan, Muhammet; Can, Tolga; Çavuş, Özge; Doǧgrusöz, Emel; Gökalp, Demir; Akaydın, Ateş; Akoǧlu, Leman; Angın, Pelin; Cinbiş, R. Gökberk; Gür, Tunay; Ünlü, Mehmet
    We describe our third participation, that includes one high-level feature extraction run, and two manual and one interactive search runs, to the TRECVID video retrieval evaluation. All of these runs have used a system trained on the common development collection. Only visual and textual information were used where visual information consisted of color, texture and edge-based low-level features and textual information consisted of the speech transcript provided in the collection.
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    Detection and tracking of repeated sequences in videos
    (2007) Can, Tolga
    In this thesis, we propose a new method to search different instances of a video sequence inside a long video. The proposed method is robust to view point and illumination changes which may occur since the sequences are captured in different times with different cameras, and to the differences in the order and the number of frames in the sequences which may occur due to editing. The algorithm does not require any query to be given for searching, and finds all repeating video sequences inside a long video in a fully automatic way. First, the frames in a video are ranked according to their similarity on the distribution of salient points and colour values. Then, a tree based approach is used to seek for the repetitions of a video sequence if there is any. These repeating sequences are pruned for more accurate results in the last step. Results are provided on two full length feature movies, Run Lola Run and Groundhog Day, on commercials of TRECVID 2004 news video corpus and on dataset created for CIVR Copy Detection Showcase 2007. In these experiments, we obtain %93 precision values for CIVR2007 Copy Detection Showcase dataset and exceed %80 precision values for other sets.
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    Reklamların belirlenmesi ve takibi
    (IEEE, 2007-06) Can, Tolga; Duygulu, Pınar
    Reklamlar ürünün tanıtımında önemli bir yoldur. Reklamların takibi pazarlamada çok önemli olsa da bu işi elle yapmak çok zaman gerektiren ve hataya çok açık bir iştir. Bu çalışmada, TV yayınlarında reklamların belirlenmesi ve takip edilmesine yönelik yeni bir yöntem sunulmaktadır. Logo belirleme yöntemi kullanılarak reklamlar %90’nın üzerinde doğruluk derecesiyle sınıflandırılabilmektedir. Bu sınıflandırmanın ardından reklamlar tekrar eden sıralılar belirlenerek takip edilebilmektedir. Bunların bir sonucu olarak reklamların takibi için değerli istatistikler elde edilebimektedir. Advertising is a powerful tool for promoting the products. Tracking of the commercials is important for planning marketing but performing this process manually is time consuming and error prone. In this study, we propose a method to detect and track commercials in news broadcasts. We classify the commercials with recall and precision values over 90% with a logo detection method. Then, we track the commercials by detecting repeating commercial sequences. Finally, valuable statistics are produced for monitoring the advertisement activities.
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    Searching for repeated video sequences
    (ACM, 2007-09) Can, Tolga; Duygulu, Pınar
    In this paper, we propose a new method to search different instances of a video sequence inside a long video and/or video collection. The proposed method is robust to view point and illumination changes which may occur since the sequences are captured in different times with different cameras, and to the differences in the order and the number of frames in the sequences which may occur due to editing. The algorithm does not require any query to be given for searching, and finds all repeating video sequences inside a long video in a fully automatic way. First, the frames in a video are ranked according to their similarity on the distribution of salient points and colour values. Then, a tree based approach is used to seek for the repetitions of a video sequence if there is any. Results are provided on a full length feature movie, Run Lola Run and on commercials of TRECVID 2004 news video corpus. Copyright 2007 ACM.