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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 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 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.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 Multipose face detection using Zernike moment invariants, Zernike moment deǧi̇şmezleri̇ i̇le pozdan baǧimsiz yüz tespi̇ti̇(2012) Karaali, Ali; Erdem, Cigdem Eroglu; Ulukaya, Sezer; Karaali, Ali, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Cigdem Eroglu, Bahçeşehir Üniversitesi, Istanbul, Turkey; Ulukaya, Sezer, Bahçeşehir Üniversitesi, Istanbul, TurkeyWe propose a new efficient technique for localization of faces in arbitrary images. The technique is based on segmentation of images into skin colored blobs, which is followed by computation of scale, translation and rotation invariant moment-based features to learn a statistical model of faces and non-face regions. The superiority of the method to the state-of-the-art face detection methods is its ability to detect non-frontal faces in a person independent way. Experimental results on CVL database show that the proposed algorithm gives higher true positive rates as compared to the well-known Viola-Jones face detector. © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.Publication Metadata only Estimation of the neutral face shape using Gaussian mixture models(2012) Ulukaya, Sezer; Erdem, Cigdem Eroglu; Ulukaya, Sezer, Department of Electrical and Electronic Engineering, Boğaziçi Üniversitesi, Bebek, Turkey, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Cigdem Eroglu, Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, TurkeyWe present a Gaussian Mixture Model (GMM) fitting method for estimating the unknown neutral face shape for frontal facial expression recognition using geometrical features. Subtracting the estimated neutral face, which is related to the identity-specific component of the shape leaves us with the component related to the variations resulting from facial expressions. Experimental results on the Extended Cohn-Kanade (CK+) database show that subtracting the estimated neutral face shape gives better emotion recognition rates as compared to classifying the geometrical facial features directly, when the person-specific neutral face shape is not available. We also experimentally evaluate two different geometric facial feature extraction methods for emotion recognition. The average emotion recognition rates achieved with the proposed neutral shape estimation method and coordinate based features is 88%, which is higher than the baseline results presented in the literature, although we do not use the person-specific neutral shapes (94% if we use), and any appearance based features. © 2012 IEEE. © 2012 Elsevier B.V., All rights reserved.Publication Metadata only A turkish audio-visual emotional database, Görsel-isitsel türkçe duygusal veritabani(2013) Önder, Onur; Zhalehpour, Sara; Erdem, Cigdem Eroglu; Önder, Onur, Bahçeşehir Üniversitesi, Istanbul, Turkey; Zhalehpour, Sara, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Cigdem Eroglu, Bahçeşehir Üniversitesi, Istanbul, TurkeyIn order to carry out research on audio-visual affect recognition, suitable databases are essential. In this work, we present a re-Acted audio-visual database in Turkish, consisting of recordings of subjects expressing various emotional and mental states. The database contains synchronous facial recordings of subjects with a frontal stereo camera and a half profile mono camera. The subjects first watch visual or audio-visual stimuli on a screen in front of them, which are designed and timed to elicit certain emotions and mental states. The subjects answer questions about the visual stimuli in an unscripted way. The target emotions that we want to elicit are the six basic ones (happiness, anger, sadness, disgust, fear, surprise) and additionally boredom. We also aim to elicit several mental states such as unsure (including confused, undecided), thinking, concentrating, interested (including curious), and complaining. The database also contains short acted recordings of each subject. © 2013 IEEE. © 2013 Elsevier B.V., All rights reserved.Publication Metadata only Auto-detection of unusual events in metro stations via security cameras, Metro istasyonlarindaki olaǧandişi durumlarin güvenlik kameralariyla otomatik tespiti(2013) Daǧli, Mehmet Ali; Erdem, Cigdem Eroglu; Daǧli, Mehmet Ali, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Cigdem Eroglu, Bahçeşehir Üniversitesi, Istanbul, TurkeyDue to the excess of the security cameras on the metro stations, staff is unable to track all of the cameras at same time. So that he may miss many of the important events. In order to detect these events automatically and generate warnings to the staff for preventing events before dangerous results occurred is the main goal of the research. With this study functions like train detection, yellow line intrusion, fallen passenger detection, restricted area violation and open door detection are realized. According to the 200 hours tests system reaches more than 99% success rate about detecting events. © 2013 IEEE. © 2013 Elsevier B.V., All rights reserved.Publication Metadata only A method for extraction of affective audio-visual facial clips from movies, Filmlerden duygusal yüz ifadeleri içeren video klipleri elde etmek için bir yöntem(2013) Turan, Çigdem; Kansin, Can; Zhalehpour, Sara; Aydin, Zafer; Erdem, Cigdem Eroglu; Turan, Çigdem, Bahçeşehir Üniversitesi, Istanbul, Turkey; Kansin, Can, Bahçeşehir Üniversitesi, Istanbul, Turkey; Zhalehpour, Sara, Bahçeşehir Üniversitesi, Istanbul, Turkey; Aydin, Zafer, Bahçeşehir Üniversitesi, Istanbul, Turkey; Erdem, Cigdem Eroglu, Bahçeşehir Üniversitesi, Istanbul, TurkeyIn order to design algorithms for affect recognition from facial expressions and speech, audio-visual databases are needed. The affective databases used by researchers today are generally recorded in laboratory environments and contain acted expressions. In this work, we present a method for extraction of audio-visual facial clips from movies. The database collected using the proposed method contains English and Turkish clips and can easily be extended for other languages. We also provide facial expresssion recognition results, which utilize local phase quantization based feature extraction and a support vector machine. Due to larger number of features compared to the number of examples, the affect recognition accuracy improves significantly when feature selection is also performed. © 2013 IEEE. © 2013 Elsevier B.V., All rights reserved.