Yazar "Gudukbay, Ugur" seçeneğine göre listele

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    HandVR: a hand-gesture-based interface to a video retrieval system
    (Springer London Ltd, 2015) Genc, Serkan; Bastan, Muhammet; Gudukbay, Ugur; Atalay, Volkan; Ulusoy, Ozgur
    Using one's hands in human-computer interaction increases both the effectiveness of computer usage and the speed of interaction. One way of accomplishing this goal is to utilize computer vision techniques to develop hand-gesture-based interfaces. A video database system is one application where a hand-gesture-based interface is useful, because it provides a way to specify certain queries more easily. We present a hand-gesture-based interface for a video database system to specify motion and spatiotemporal object queries. We use a regular, low-cost camera to monitor the movements and configurations of the user's hands and translate them to video queries. We conducted a user study to compare our gesture-based interface with a mouse-based interface on various types of video queries. The users evaluated the two interfaces in terms of different usability parameters, including the ease of learning, ease of use, ease of remembering (memory), naturalness, comfortable use, satisfaction, and enjoyment. The user study showed that querying video databases is a promising application area for hand-gesture-based interfaces, especially for queries involving motion and spatiotemporal relations.
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    Mobile Image Search Using Multi-Query Images
    (Ieee, 2015) Calisir, Fatih; Bastan, Muhammet; Gudukbay, Ugur; Ulusoy, Ozgur
    Recent advances in mobile device technology have turned the mobile phones into powerfull devices with high resolution cameras and fast processing capabilities. Having more user interaction potential compared to regular PCs, mobile devices with cameras can enable richer content-based object image queries: the user can capture multiple images of the query object from different viewing angles and at different scales, thereby providing much more information about the object to improve the retrieval accuracy. The goal of this paper is to improve the mobile image retrieval performance using multiple query images. To this end, we use the well-known bag-of-visual-words approach to represent the images, and employ early and late fusion strategies to utilize the information in multiple query images. With extensive experiments on an object image dataset with a single object per image, we show that multi-image queries result in higher average precision performance than single image queries.
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    Mobile multi-view object image search
    (Springer, 2017) Calisir, Fatih; Bastan, Muhammet; Ulusoy, Ozgur; Gudukbay, Ugur
    High user interaction capability of mobile devices can help improve the accuracy of mobile visual search systems. At query time, it is possible to capture multiple views of an object from different viewing angles and at different scales with the mobile device camera to obtain richer information about the object compared to a single view and hence return more accurate results. Motivated by this, we propose a new multi-view visual query model on multi-view object image databases for mobile visual search. Multi-view images of objects acquired by the mobile clients are processed and local features are sent to a server, which combines the query image representations with early/late fusion methods and returns the query results. We performed a comprehensive analysis of early and late fusion approaches using various similarity functions, on an existing single view and a new multi-view object image database. The experimental results show that multi-view search provides significantly better retrieval accuracy compared to traditional single view search.