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Start date: 2010End date: 2019Type: search.filters.itemtype.Conference PaperSubject: search.filters.subject.Signal processingSubject: search.filters.subject.AlgorithmsItem Type: PublicationAuthor: search.filters.author.Aydin, Tarkan

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    Internal calibration of a camera and an inertial measurement unit, Kamera ve ataletsel ölçüm birimi iç kalibrasyonu
    (2013) Erdem, Tanju Tanju; Ercan, Ali Özer; Aydin, Tarkan; Erdem, Tanju Tanju, Özyeğin Üniversitesi, Istanbul, Turkey; Ercan, Ali Özer, Özyeğin Üniversitesi, Istanbul, Turkey; Aydin, Tarkan, Bahçeşehir Üniversitesi, Istanbul, Turkey
    In this paper, we address the problem of internal calibration of a camera and an inertial measurement unit (IMU). The internal calibration of a camera and an IMU requires the determination of the relative orientation and displacement between the camera and the IMU. Although the problem of orientation estimation is well studied, and there exists simple algorithms for it, current displacement estimation techniques require very special data collection setups or particular sensor movements. We propose a novel method for estimating the displacement between the camera and an IMU. Our method has a very simple data collection step and involves the solution of linear equations only. Experimental results with real data show the effectiveness of our proposed algorithm. © 2013 IEEE. © 2013 Elsevier B.V., All rights reserved.
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    Automatic scale and image selection for panoramic images, PANORAMIK GÖSTERİMLER IÇİN OTOMATİK RESİM VE ÖLÇEK SEÇİM
    (Institute of Electrical and Electronics Engineers Inc., 2016) Arıcan, Erkut; Aydin, Tarkan; Özden, Kemal Egemen; Arıcan, Erkut, Bilgisayar Mühendisliǧi Bölümü, Bahçeşehir Üniversitesi, Istanbul, Turkey; Aydin, Tarkan, Bilgisayar Mühendisliǧi Bölümü, Bahçeşehir Üniversitesi, Istanbul, Turkey; Özden, Kemal Egemen, Bilgisayar Mühendisliǧi Bölümü, Bahçeşehir Üniversitesi, Istanbul, Turkey
    We are presenting our work on automatic zoom level detection and minimal representative input frames subset selection for panoramic image applications. Thanks to the proposed techniques, the user can record videos from a single vantage point with free rotation and zooming motions, without a prohibitive recording time limit. The zoom level (or scale) of the input video frames are computed by mean-shift algorithm in a hierarchical structure. In order to select a minimal representative subset for excessive frames on a given zoom level, a greedy iterative algorithm is devised. Image matching is achieved by local image features and projective transformations. In addition to our recently proposed Multi-scale Panoramic Augmented Reality system, we expect the approach to be useful for other panoramic applications. © 2017 Elsevier B.V., All rights reserved.