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Publication Metadata only Denoising embolic Doppler ultrasound signals using Dual Tree Complex Discrete Wavelet Transform(2010) Serbes, Görkem; Aydın, Nizamettin; Serbes, Görkem, Department of Electrical Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Aydın, Nizamettin, Department of Computer Engineering, Yıldız Teknik Üniversitesi, Istanbul, TurkeyEarly and accurate detection of asymptomatic emboli is important for monitoring of preventive therapy in stroke-prone patients. One of the problems in detection of emboli is the identification of an embolic signal caused by very small emboli. The amplitude of the embolic signal may be so small that advanced processing methods are required to distinguish these signals from Doppler signals arising from red blood cells. In this study instead of conventional discrete wavelet transform, the Dual Tree Complex Discrete Wavelet Transform was used for denoising embolic signals. Performances of both approaches were compared. Unlike the conventional discrete wavelet transform discrete complex wavelet transform is a shift invariant transform with limited redundancy. Results demonstrate that the Dual Tree Complex Discrete Wavelet Transform based denoising outperforms conventional discrete wavelet denoising. Approximately 8 dB improvement is obtained by using the Dual Tree Complex Discrete Wavelet Transform compared to the improvement provided by the conventional Discrete Wavelet Transform (less than 5 dB). © 2010 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only INTERSPEECH 2009 emotion recognition challenge evaluation, INTERSPEECH 2009 duygu tanima yarişmasi deǧerlendirmesi(2010) Bozkurt, Elif; Erzin, Engin; Erdem, Cigdem Eroglu; Erdem, Tanju Tanju; Bozkurt, Elif, Koç Üniversitesi, Istanbul, Turkey; Erzin, Engin, Koç Üniversitesi, Istanbul, Turkey; Erdem, Cigdem Eroglu, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Tanju Tanju, Özyeğin Üniversitesi, Istanbul, TurkeyIn this paper we evaluate INTERSPEECH 2009 Emotion Recognition Challenge results. The challenge presents the problem of accurate classification of natural and emotionally rich FAU Aibo recordings into five and two emotion classes. We evaluate prosody related, spectral and HMM-based features with Gaussian mixture model (GMM) classifiers to attack this problem. Spectral features consist of mel-scale cepstral coefficients (MFCC), line spectral frequency (LSF) features and their derivatives, whereas prosody-related features consist of pitch, first derivative of pitch and intensity. We employ unsupervised training of HMM structures with prosody related temporal features to define HMM-based features. We also investigate data fusion of different features and decision fusion of different classifiers to improve emotion recognition results. Our two-stage decision fusion method achieves 41.59 % and 67.90 % recall rate for the five and two-class problems, respectively and takes second and fourth place among the overall challenge results. ©2010 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only MIMO systems with non-exact CSI, Eksik kanal bilgisi Altinda MIMO sistemler(2010) Soysal, Alkan; Soysal, Alkan, Bahçeşehir Üniversitesi, Istanbul, TurkeyMultiple antenna systems are known to provide very large data rates, when the perfect channel state information is available at the receiver. However, this requires the receiver to perform a noise-free, multi-dimensional channel estimation, without using communication resources. In practice, any channel estimation is noisy and uses system resources. We shall examine the trade-off between improving channel estimation and increasing the achievable data rate. Lower and upper bounds for the capacity of the system will be derived. ©2010 IEEE. © 2011 Elsevier B.V., All rights reserved.Publication Metadata only Air drums: A computer vision based drums simulator, Bilgisayarla görü tabanli davul benzetimcisi(2010) Fidan, Kaan Can; Kehribar, İhsan; Şahin, M. Tuǧçe; Cosar, Serhan; Ünay, Devrim; Fidan, Kaan Can, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey; Kehribar, İhsan, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey; Şahin, M. Tuǧçe, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey; Cosar, Serhan, Mühendislik ve Doǧa Bilimleri Fakültesi, Sabancı Üniversitesi, Tuzla, Turkey; Ünay, Devrim, Bahçeşehir Üniversitesi, Istanbul, TurkeyThe aim of this paper is to present a novel system which tracks the motion of a drummer and generates the corresponding drum sounds. The input video sequence from a camera is processed in real-time by using local and adaptive color segmentation and Kalman filter based tracking. The Kalman filter is used to predict the hits so that we can overcome the processing delays and provide a more-realistic drumming experience. We use a local and adaptive search to detect the effective points of the drum sticks, which ensures robustness to background clutter and reduces the computational burden. We have developed a working demo and evaluated its performance by comparing with the output signal of an electronic drum pad. We observed that the timing errors have an average of -8.4 ms and a standard deviation of 5.4 ms in a real drumming experiment consisting of 121 hits. ©2010 IEEE. © 2011 Elsevier B.V., All rights reserved.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 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 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.