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Publication Metadata only Comparison of LTE 800 MHz and LTE 2600 MHz frequency bands in terms of cell coverage, LTE 800 MHz ve LTE 2600 MHz frekans bantlarinin hücre kapsama bakimindan karşilaştirilmasi(2011) Tura, Ömer; Yüksel, Güray; Soysal, Alkan; Tura, Ömer, Bahçeşehir Üniversitesi, Istanbul, Turkey; Yüksel, Güray,; Soysal, Alkan, Bahçeşehir Üniversitesi, Istanbul, TurkeyIn this study, we compared 800 MHz and 2600 MHz bands in terms of cell coverage which will be used in 3GPP (Third generation Partnership Project) LTE (Long term Evolution) release 8. In RF planning, 800 MHz frequency band is used in the rural areas since coverage is crucial in such areas, and 2600 MHz frequency band is used in the urban areas in which capacity is more necessary than coverage. We used Atoll as an RF planning tool to simulate the two frequency bands for comparison in terms of coverage. The results are evaluated with respect to the furthest distance from the base station where the signal level threshold is obtained. © 2011 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Face recognition-based IMDB plug-in for movies, Filmler için yüz tanima tabanli IMDB eklentisi(2011) Ulukaya, Sezer; Kayim, Güney; Ekenel, Hazim Kemal; Ulukaya, Sezer, Bahçeşehir Üniversitesi, Istanbul, Turkey; Kayim, Güney, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ekenel, Hazim Kemal, Boğaziçi Üniversitesi, Bebek, TurkeyIn this paper, we present an initial study on an IMDB plug-in for cast identification in movies. In the system, training face images are collected by using Google image search. While watching a movie, the user clicks on the face of the person he is interested to acquire information. Afterwards, the system first tries to detect close to frontal faces, if it cannot find any, then it runs a profile face detector. The found face are then tracked backwards and forwards in the shot and this way a face sequence is obtained. Matching is performed between the extracted face sequence from the movie and the face image sets collected from the web. IMDB page links of the closest three persons resulted from the matching process is then presented to the user. In this study, we addressed the following three interesting points: matching between face sequence and face image sets, the effect of automatically collected noisy training images from the web on the performance, and finally, the performance effect of utilizing prior information of cast list and performing the classification within a limited number of classes. Experiments have shown that matching between face sequence and face image sets is a difficult problem. © 2011 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only A comparison of geometrical facial features for affect recognition, Duygu tanima i̇çi̇n geometri̇k yüz özni̇teli̇kleri̇ni̇n karşilaştirilmasi(2011) Ulukaya, Sezer; Erdem, Cigdem Eroglu; Ulukaya, Sezer, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Cigdem Eroglu, Bahçeşehir Üniversitesi, Istanbul, TurkeyIn this work, we compare two different geometric feature extraction methods derived from coordinates of facial points tracked by Active Appearance Models. The compared feature extraction methods differ in their use of coordinates or distances between facial points and whether they use the information of a neutral facial expression. Experiments on the extended Cohn-Kanade database show that the coordinate-based features using the neutral frame information gives the best emotion recognition results (%94) using a SVC classifier with a polynomial kernel. © 2011 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only GPS aided Extended Kalman Filter based localization for unmanned vehicles, İnsansiz araçlar i̇çi̇n GPS destekli̇ Geni̇şleti̇lmi̇ş Kalman Fi̇ltresi̇ tabanli konumladirma(2012) Tuna, Gürkan; Güngör, Vehbi Çağrı; Gülez, Kayhan; Tuna, Gürkan, Trakya Üniversitesi, Edirne, Turkey; Güngör, Vehbi Çağrı, Bahçeşehir Üniversitesi, Istanbul, Turkey; Gülez, Kayhan, Kontrol Ve Otomasyon Mühendisliǧi Bölümü, Yıldız Teknik Üniversitesi, Istanbul, TurkeyThis paper presents design considerations of a GPS-aided localization system for unmanned vehicles used in outdoor applications. The system proposed in this paper is based on Extended Kalman Filter (EKF) and also integrates Global Positioning System (GPS) measurements. Localization and navigation systems are base components of all unmanned vehicles since they give unmanned vehicles the ability of perceiving the environment in order to localize themselves and to navigate to a target. The advantage of the proposed system over a GPS based localization system is that the system works even if the GPS receiver does not receive any GPS signals. In this study, firstly proposed EKF-based localization system is explained, and then how to integrate GPS measurements into this localization system is explained. With simulation studies in MATLAB, the effectiveness of the system is shown. The simulations show that the proposed localization system gives accurate results with negligible positional errors. © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.Publication Metadata only A hybrid facial expression recognition method based on neutral face shape estimation, Yüz i̇fadesi̇ tanima i̇çi̇n nötr yüz şekli̇ni̇n kesti̇ri̇lmesi̇ne dayali hi̇bri̇t bi̇r yöntem(2012) Ulukaya, Sezer; Erdem, Cigdem Eroglu; Ulukaya, Sezer, Boğaziçi Üniversitesi, Bebek, Turkey, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Cigdem Eroglu, Bahçeşehir Üniversitesi, Istanbul, TurkeyIn order to recognize the facial expression of a person, the knowledge of the neutral facial expression of that person is useful but may not always be available.We present a method based on Gaussian mixture models (GMM) to estimate the unknown neutral facial expression of an expressive face. The estimated neutral face is then subtracted from the features of the expressive image and classified using support vector classifiers (SVC). Experimental results on the extended Cohn-Kanade (CK+) database give an emotion recognition rate of 88% using geometric features only and 92% if appearance based features are also included. © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.Publication Metadata only Feature extraction for facial expression recognition by canonical correlation analysis, Kanoni̇k korelasyon anali̇zi̇ i̇le yüz i̇fadesi̇nden duygu tanima i̇çi̇n özni̇teli̇ k çikarimi(2012) Sakar, C. Okan; Kursun, Olcay; Karaali, Ali; Erdem, Cigdem Eroglu; Sakar, C. Okan, Bahçeşehir Üniversitesi, Istanbul, Turkey; Kursun, Olcay, Istanbul Üniversitesi, Istanbul, Turkey; Karaali, Ali, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Cigdem Eroglu, Bahçeşehir Üniversitesi, Istanbul, TurkeyAlthough several methods have been proposed for fusing different image representations obtained by different preprocessing methods for emotion recognition from the facial expression in a given image, the dependencies and relations among them have not been much investigated. In this study, it has been shown that covariates obtained by Canonical Correlation Analysis (CCA) that extracts relations between different representations have high predictive power for emotion recognition. As high prediction accuracy can be achieved using a small number of features extracted by it, CCA is considered to be a good dimensionality reduction method. For our simulations, we used the CK+ database and showed that covariates obtained from difference-images and geometric-features representations have high prediction accuracy. © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.Publication Metadata only Inertial sensor fusion for 3D camera tracking, 3B kamera taki̇bi̇ i̇çi̇n eylemsi̇zli̇k algilayicilarinin bi̇rleşti̇ri̇lmesi̇(2012) Özer, Nuri; Erdem, Tanju Tanju; Ercan, Ali Özer; Erdem, Cigdem Eroglu; Özer, Nuri, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Tanju Tanju, Özyeğin Üniversitesi, Istanbul, Turkey; Ercan, Ali Özer, Özyeğin Üniversitesi, Istanbul, Turkey; Erdem, Cigdem Eroglu, Bahçeşehir Üniversitesi, Istanbul, TurkeyIt is well known in a Bayesian filtering framework, the use of inertial sensors such as accelerometers and gyroscopes improves 3D tracking performance compared to using camera measurements only. The performance improvement is more evident when the camera undergoes a high degree of motion. However, it is not well known whether the inertial sensors should be used as control inputs or as measurements. In this paper, we present the results of an extensive set of simulations comparing different combinations of using inertial sensors as control inputs or as measurements. We show that it is better use a gyroscope as a control input while an accelerometer can be used as a measurement or control input. We also derive and present the extended Kalman filter (EKF) equations for a specific case of fusing accelerometer and gyroscope data that has not been reported before. © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.Publication Metadata only Inter-hemispheric atrophy better correlates with expert ratings than hemispheric cortical atrophy, İnterhemi̇sferi̇k atrofi̇ ölçümleri̇ hemi̇sferi̇k korti̇kal atrofi̇ ölçümleri̇ i̇le karşilaştirildiǧinda uzman derecelendi̇ rmesi̇ i̇le daha uyumludur(2012) Başkaya, Osman; Kandemir, Melek; Tepe, Muzaffer Savaş; Acar, M.; Unal, Gozde Bozkurt; Yalçıner, Zehra Betül; Ünay, Devrim; Başkaya, Osman, Bahçeşehir Üniversitesi, Istanbul, Turkey; Kandemir, Melek,; Tepe, Muzaffer Savaş, Radyoloji Departmani, Istanbul, Turkey; Acar, M., Radyoloji Departmani, Istanbul, Turkey; Unal, Gozde Bozkurt, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey; Yalçıner, Zehra Betül,; Ünay, Devrim, Bahçeşehir Üniversitesi, Istanbul, TurkeyBrain atrophy is one of the parameters considered by experts for rating dementia from neuro-imaging findings. Research efforts have focused on measuring brain atrophy from images through experts' visual assessment or computer-based approaches. However, agreement between the visual assessment and computer-based measurement of atrophy is not yet investigated. Accordingly, this paper presents an automated method for cerebral atrophy assessment from cross-sectional MRI through hemispheric volume loss. For this purpose, the proposed method quantifies inter-hemispheric distance, and the distance between the cranium and the brain parenchyma, separately. Discriminative power of the proposed method is evaluated on two datasets with experts' visual gradings: Yue et al.'s data and a newly created reference dataset. Results show that inter-hemispheric atrophy better correlates with visual grades, and inconsistencies at the skull-stripping or brain tissue extraction steps can degrade the agreement between computer-based measurements and expert gradings. © 2012 IEEE. © 2013 Elsevier B.V., All rights reserved.Publication Metadata only Developing an occlusion-resistant automatic fall detection system for smart environments, Akilli ortamlar i̇çi̇n oklüzyon koşullarinda çalişabi̇len otomati̇k düşme durumu algilama si̇stemi̇(2012) Özcan, Davut; Ergün, Övgü Öztürk; Özcan, Davut, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ergün, Övgü Öztürk, Bahçeşehir Üniversitesi, Istanbul, TurkeyThis paper proposes an occlusion resistant automatic fall detection framework for smart environments. There are two major contributions of the proposed method. First, synchronized RGB and depth data are utilized together to capture both apperance and geometrical characteristics of human silhouettes in the environment. Second, unlike existing methods, a single Kinect sensor is mounted on a ceiling and plan-view of the room is captured to avoid occlusions rising from furnitures. For each frame, silhouette of person is extracted from depth data. From silhouette data, depth histogram, bounding box, distribution of average and highest depth values are calculated. The system learns these parameters for different regions of the room to classify human poses into three categories as standing, fall down and other poses. Experimental results show successful application of the proposed framework to detect falls under complex situations. © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.Publication Metadata only A validation method for comparing classifiers on imbalanced datasets, Dengesi̇z veri̇ kümeleri̇ üzeri̇nde siniflandiricilarin karşilaştirilmasi i̇çi̇n bi̇r sinama yöntemi̇(2012) Erdogdu Sakar, Betul; Sakar, C. Okan; Gürgen, Fïkret S.; Sertbaş, Ahmet; Kursun, Olcay; Erdogdu Sakar, Betul, Bahçeşehir Üniversitesi, Istanbul, Turkey; Sakar, C. Okan, Bahçeşehir Üniversitesi, Istanbul, Turkey; Gürgen, Fïkret S., Boğaziçi Üniversitesi, Bebek, Turkey; Sertbaş, Ahmet, Istanbul Üniversitesi, Istanbul, Turkey; Kursun, Olcay, Istanbul Üniversitesi, Istanbul, TurkeyIn this study, to compare the robustness and learning capability of the classifiers on imbalanced datasets, a cross validation method that generates class-imbalanced training sets is proposed. The method will also be used to evaluate the accuracies of methods developed for dealing with the class-imbalance problem. The proposed method is used to generate imbalanced datasets from three biomedical datasets. Then, k-Nearest Neighbor, Support Vector Machines and Multi Layer Perceptron classifiers are compared using various settings of their hyper-parameters that affect their complexities. The experimental results show that SVMs are simply the most robust of all when applied to imbalanced datasets. © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.