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Yayın A precision estimation method for volumetric changes(IEEE, 2019-06) Akça, Mehmet Devrim; Stylianidis, Efstratios; Gruen, Armin W.; Altan, Mehmet Orhan; Hofer, Martin; Smagas, Konstantinos; Sanchez Martin, Victor; Walli, Andreas; Jimeno, Elisa; Garcia, AlejandroEarth surface changes are often computed by comparing the sequences of digital elevation models (DEMs) so called the DEM of difference (DoD) method. We present an operational DEM generation, co-registration and DoD comparison software in which the surface changes are quantified in metric units of volume. A practical method, which is based on the law of error propagation, is developed to estimate the theoretical precisions of volumetric changes. The proposed pipeline can estimate the change of object volumes (in terms of loss and gain) together with their precision numbers. Change of the forest volume in a fire effected region in a test site is analyzed for the validation. The method can be used for various change detection applications related to forestry as well as other topics such as earthworks, geomorphology, mining, and urbanization.Yayın Quality assessment of 3D building data(Wiley-Blackwell Publishing, 2010-12) Akça, Mehmet Devrim; Freeman, Mark; Sargent, Isabel; Gruen, Armin W.Three-dimensional building models are often now produced from lidar and photogrammetric data. The quality control of these models is a relevant issue both from the scientific and practical points of view. This work presents a method for the quality control of such models. The input model (3D building data) is co-registered to the verification data using a 3D surface matching method. The 3D surface matching evaluates the Euclidean distances between the verification and input data-sets. The Euclidean distances give appropriate metrics for the 3D model quality. This metric is independent of the method of data capture. The proposed method can favourably address the reference system accuracy, positional accuracy and completeness. Three practical examples of the method are provided for demonstration.Yayın ViLDAR-Visible light sensing-based speed estimation using vehicle headlamps(IEEE, 2019-11) Abuella, Hisham; Miramirkhani, Farshad; Ekin, Sabit; Uysal, Murat; Ahmed, SamirThe introduction of light emitting diodes (LED) in automotive exterior lighting systems provides opportunities to develop viable alternatives to conventional communication and sensing technologies. Most of the advanced driver-assist and autonomous vehicle technologies are based on Radio Detection and Ranging (RADAR) or Light Detection and Ranging (LiDAR) systems that use radio frequency or laser signals, respectively. While reliable and real-time information on vehicle speeds is critical for traffic operations management and autonomous vehicles safety, RADAR or LiDAR systems have some deficiencies especially in curved road scenarios where the incidence angle is rapidly varying. In this paper, we propose a novel speed estimation system so-called the Visible Light Detection and Ranging (ViLDAR) that builds upon sensing visible light variation of the vehicle's headlamp. We determine the accuracy of the proposed speed estimator in straight and curved road scenarios. We further present how the algorithm design parameters and the channel noise level affect the speed estimation accuracy. For wide incidence angles, the simulation results show that the ViLDAR outperforms RADAR/LiDAR systems in both straight and curved road scenarios.
