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Öğe A novel approach to obtain trajectories of targets from laser scanned datasets(Ieee, 2015) Galip, Feyza; Çaputcu, Mehmet; İnan, Rüveyda Hilal; Sharif, Haidar; Karabayır, Aykut; Kaplan, Sezin; Uyaver, ŞahinLaser scanner has several bons when compared with video camera. It does not record real world videos except scanned points. As a result, processing of data becomes faster and easier. Over and above, it takes away the problem of private life conservation. This paper proposes a new and competent computer vision based approach for detecting and tracking targets (e.g., pedestrians and vehicles) from laser scanned datasets. Laser scanned data points from each scan have been deemed as a video frame. Blobs are extracted and then computer vision techniques (e.g., Kalman filter, Hungarian algorithms, and etc.) are applied to recognize and track the kind of targets. Scanned datasets, collected from two kinds of laser scanners, were used to conduct experiments. Full trajectories of pedestrians, vehicles, and noises were resulted in three dimensional spaces. Experimental results give evidence of the efficacy of our proposed framework.Öğe A proof of concept for home automation system with implementation of the Internet of Things standards(International University of Sarajevo, 2018) Sharif, Haidar; Despot, Ivan; Uyaver, ŞahinWho does not want a home having comfortability, security, safety, and reliability? A system of interconnected devices and sensors with internet of things standards can communicate independently with less or no human interaction. With such a system, everyday tasks (e.g., control of light, heat, humidity, air flow, and etc.) in and around our living units can be simplified. It also adds a list of desirable states, e.g., economy, peace of mind, comfortability, convenience, logistics, security, safety, and reliability. In this paper, an approach for home automation system that brings miscellaneous tasks in our living units into one centralized action point and functions with remotely controlled devices (e.g., smartphone, iPad, laptop, and etc.) has been implemented. The necessity to visit individual device involved in corresponding task has been perished. The proposed model is free of construction impediments as it deems to be developing a system alongside the architecture of the household. It is a proof of concept. So its potential serviceability for many real world applications is extremely high. © 2018, International University of Sarajevo.Öğe A simple approach to count and track underwater fishes from videos(Ieee, 2015) Sharif, Haidar; Galip, Feyza; Güler, Adil; Uyaver, ŞahinFishes are of great importance to the ecosystem. Behavior of fishes is interesting. Counting and tracking of fishes can provide good knowledge about the behavior of fishes. Counting and behavior quantifying of fishes within a turbulence or trawl environment are challenging tasks. The traditional methods are not only inefficient but also expensive. Thus counting and tracking under water fishes from videos are emerging topic for ichthyologists. This paper addresses a simple method to count and track underwater fishes from videos. It is a hybrid of background subtraction, Hungarian algorithm, and Kalman filter. It enables tracking of fishes whose number can vary over time. Theoretical runtime of the tracking algorithm is O(n(3)) with problem size n. Experimental results demonstrate its effectiveness.Öğe Classification and detection of various geographical features from satellite imagery(International University of Sarajevo, 2018) Sharif, Haidar; Uyaver, Şahin; Zerdo, ZaidIt is a challenging task to classify and detect various geographical features from the satellite imagery of the Earth as well as the celestial bodies. This paper puts forward several pixel based classification algorithms to classify geographical features from the satellite images of the Earth. The recorded experimental results, from a total of 606 satellite images to classify miscellaneous geographical features, demonstrate that the maximum algorithmic performances can approximate to 87%. This paper also addresses a simple algorithm based on edge approximation and circular Hough transformation to detect craters from the satellite imagery of celestial bodies. An online available dataset to detect craters evaluates the performance of the algorithm. In general, all the proposed algorithms are straightforward but in many ways effective. © 2018, International University of Sarajevo.Öğe Classification of geographical features from satellite imagery(Springer Verlag, 2019) Sharif, Haidar; Uyaver, Şahin; Sharif, Haris Uddin; İnce, İbrahim Furkan; Zerdo, ZaidIt is a challenging task to classify heterogeneous geographical features from satellite imagery. This paper addresses 31 straightforward classification algorithms based on predominantly pixels to classify miscellaneous geographical features from satellite imagery. The addressed algorithms can extract and process the features of a large dataset with high-resolution images expeditiously. A total of 606 red-green-blue satellite images of the Bosnian city of Banja Luka are exercised to comprehend their performances for classifying cemeteries, fields, houses, industries, rivers, and trees. The recorded experimental results demonstrate that the best average performance can come into possession of 87%. © Springer Nature Singapore Pte Ltd. 2019.Öğe Recognition of objects from laser scanned data points using SVM(Ieee Computer Soc, 2016) Galip, Feyza; Sharif, Haidar; Çaputcu, Mehmet; Uyaver, ŞahinNowadays, laser scanners are operated for data collection instead of video cameras. Laser scanners do not record real world videos except scanned points. Thus it takes away problems of private life conservation. Plus data processing gets very fast and easy. But from laser scanned data points, recognition of objects is a challenging task. This paper points to the usability of SVM to recognize pedestrians and vehicles from laser scanned data points. Data points from each scan are esteemed as a video frame. Moving blobs are extracted and then SVM is used to recognize each blob as either a pedestrian or a vehicle. Experimental results show that SVM can be actually and robustly used to recognize objects from laser scanned data points.
