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Publication Metadata only 3D progressive compression with octree particles(Akademische Verlagsgesellsch Aka Gmbh, 2002) Schmitt, Francis; Department of Computer Engineering; N/A; Yemez, Yücel; Faculty Member; Department of Computer Engineering; College of Engineering; N/A; 107907; N/AThis paper improves the storage efficiency of the progressive particle-based modeling scheme presented in [14, 15] by using entropy coding techniques. This scheme encodes the surface geometry and attributes in terms of appropriately ordered oc-tree particles, which can then progressively be decoded and rendered by the-viewer by means of a fast direct triangulation technique. With the introduced entropy coding technique, the bitload of the multi-level representation for geometry encoding reduces to 9-14 bits per particle (or 4.5-7 bits per triangle) for 12-bit quantized geometry.Publication Metadata only 3D shape correspondence by isometry-driven greedy optimization(IEEE Computer Soc, 2010) N/A; Department of Computer Engineering; Sahillioğlu, Yusuf; Yemez, Yücel; PhD Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; 215195; 107907We present an automatic method that establishes 3D correspondence between isometric shapes. Our goal is to find an optimal correspondence between two given (nearly) isometric shapes, that minimizes the amount of deviation from isometry. We cast the problem as a complete surface correspondence problem. Our method first divides the given shapes to be matched into surface patches of equal area and then seeks for a mapping between the patch centers which we refer to as base vertices. Hence the correspondence is established in a fast and robust manner at a relatively coarse level as imposed by the patch radius. We optimize the isometry cost in two steps. in the first step, the base vertices are transformed into spectral domain based on geodesic affinity, where the isometry errors are minimized in polynomial time by complete bipartite graph matching. the resulting correspondence serves as a good initialization for the second step of optimization in which we explicitly minimize the isometry cost via an iterative greedy algorithm in the original 3D Euclidean space. We demonstrate the performance of our method on various isometric (or nearly isometric) pairs of shapes for some of which the ground-truth correspondence is available.Publication Metadata only 3D Shape recovery and tracking from multi-camera video sequences via surface deformation(IEEE, 2006) Skala, V.; N/A; Department of Computer Engineering; Sahillioğlu, Yusuf; Yemez, Yücel; PhD Student; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; 215195; 107907This paper addresses 3D reconstruction and modeling of time-varying real objects using multicamera video. The work consists of two phases. In the first phase, the initial shape of the object is recovered from its silhouettes using a surface deformation model. The same deformation model is also employed in the second phase to track the recovered initial shape through the time-varying silhouette information by surface evolution. The surface deformation/evolution model allows us to construct a spatially and temporally smooth surface mesh representation having fixed connectivity. This eventually leads to an overall space-time representation that preserves the semantics of the underlying motion and that is much more efficient to process, to visualize, to store and to transmit.Publication Metadata only Machine learning-based approach to identify formalin-fixed paraffin-embedded glioblastoma and healthy brain tissues(Spie-Int Soc Optical Engineering, 2022) N/A; Department of Electrical and Electronics Engineering; N/A; N/A; N/A; N/A; N/A; Department of Electrical and Electronics Engineering; Torun, Hülya; Batur, Numan; Bilgin, Buse; Esengür, Ömer Tarık; Baysal, Kemal; Kulaç, İbrahim; Solaroğlu, İhsan; Onbaşlı, Mehmet Cengiz; PhD Student; Undergraduate Student; PhD Student; Undergraduate Student; Faculty Member; Faculty Member; Faculty Member; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; Graduate School of Sciences and Engineering; School of Medicine; School of Medicine; School of Medicine; School of Medicine; College of Engineering; N/A; N/A; N/A; N/A; 119184; 170305; 102059; 258783Glioblastoma is the most malignant and common high-grade brain tumor with a 14-month overall survival length. According to recent World Health Organization Central Nervous System tumor classification (2021), the diagnosis of glioblastoma requires extensive molecular genetic tests in addition to the traditional histopathological analysis of Formalin-Fixed Paraffin-Embedded (FFPE) tissues. Time-consuming and expensive molecular tests as well as the need for clinical neuropathology expertise are the challenges in the diagnosis of glioblastoma. Hence, an automated and rapid analytical detection technique for identifying brain tumors from healthy tissues is needed to aid pathologists in achieving an error-free diagnosis of glioblastoma in clinics. Here, we report on our clinical test results of Raman spectroscopy and machine learning-based glioblastoma identification methodology for a cohort of 20 glioblastoma and 18 white matter tissue samples. We used Raman spectroscopy to distinguish FFPE glioblastoma and white matter tissues applying our previously reported protocols about optimized FFPE sample preparation and Raman measurement parameters. One may analyze the composition and identify the subtype of brain tumors using Raman spectroscopy since this technique yields detailed molecule-specific information from tissues. We measured and classified the Raman spectra of neoplastic and non-neoplastic tissue sections using machine learning classifiers including support vector machine and random forest with 86.6% and 83.3% accuracies, respectively. These proof-of-concept results demonstrate that this technique might be eventually used in the clinics to assist pathologists once validated with a larger and more diverse glioblastoma cohort and improved detection accuracies.Publication Metadata only Multimodal speaker identification with audio-video processing(Ieee, 2003) Department of Computer Engineering; N/A; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Yemez, Yücel; Kanak, Alper; Erzin, Engin; Tekalp, Ahmet Murat; Faculty Member; Master Student; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; 107907; N/A; 34503; 26207In this paper we present a multimodal audio-visual speaker identification system. The objective is to improve the recognition performance over conventional unimodal schemes. The proposed system decomposes the information existing in a video stream into three components: speech, face texture and lip motion. Lip motion between successive frames is first computed in terms of optical row vectors and then encoded as a feature vector in a magnitude-direction histogram domain. The feature vectors obtained along the whole stream are then interpolated to match the rate of the speech signal and fused with mel frequency cepstral coeffcients (MFCC) of the corresponding speech signal. The resulting joint feature vectors are used to train and test a Hidden Markov Model (HMM) based identification system. Face texture images are treated separately in eigenface domain and integrated to the system through decision-fusion. Experimental results are also included for demonstration of the system performance.Publication Metadata only Quality assessment of asymmetric stereo video coding(IEEE, 2010) N/A; N/A; Department of Electrical and Electronics Engineering; Saygılı, Görkem; Gürler, Cihat Göktuğ; Tekalp, Ahmet Murat; Master Student; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 26207It is well known that the human visual system can perceive high frequencies in 3D, even if that information is present in only one of the views. therefore, the best 3D stereo quality may be achieved by asymmetric coding where the reference (right) and auxiliary (left) views are coded at unequal PSNR. However, the questions of what should be the level of this asymmetry and whether asymmetry should be achieved by spatial resolution reduction or SNR (quality) reduction are open issues. Extensive subjective tests indicate that when the reference view is encoded at sufficiently high quality, the auxiliary view can be encoded above a low-quality threshold without a noticeable degradation on the perceived stereo video quality. This low-quality threshold may depend on the 3D display; e.g., it is about 31 dB for a parallax barrier display and 33 dB for a polarized projection display. Subjective tests show that, Above this PSNR threshold value, users prefer SNR reduction over spatial resolution reduction on both parallax barrier and polarized projection displays. It is also observed that, if the auxiliary view is encoded below this threshold value, symmetric coding starts to perform better than asymmetric coding in terms of perceived 3D video quality.Publication Metadata only Scanning led array based volumetric display(IEEE, 2007) N/A; Department of Electrical and Electronics Engineering; Sayınta, Murat; Ürey, Hakan; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 8579This paper reports a novel volumetric display system using 1D LED arrays mounted on rotating platforms to create a quasi-holographic display. the system employs a 2D array of such modules and a special diffuser screen in front of them. a virtual 3D image pixel (voxel) appears behind the screen at the intersection of 2 rays emitted from 2 LEDs at different rotation angles. the basic concept is reported for the first time here. a subsystem demonstrator is developed using a single LED mounted on a polymer scanner platform rotating at 60Hz, which corresponds to the refresh rate of the display system. Large rotation angle and high modulation speeds are achievable with LEDs mounted on polymer scanners. an array of LEDs can be driven by a LED Driving IC, integrated with the polymer scanner.Publication Metadata only Scanning led array based volumetric display(IEEE, 2008) N/A; N/A; Department of Electrical and Electronics Engineering; Sayınta, Murat; Işıkman, Serhan Ömer; Ürey, Hakan; PhD Student; Master Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 8579A novel quasi-holographic display concept is developed using Light Emitting Diode (LED) arrays on scanning platform. The display system is capable of providing smooth motion parallax and solving the accommodation -vergence rivalry. Each scanner module contains I D LED array mounted on a polymer scanner with a lens for imaging the LEDs onto a special diffuser screen. The scanning modules are actuated electromagnetically and the LEDs are driven with an external LED driving Field Programmable Gate Array (FPGA) circuitry designed for the purpose. The scanners have a natural frequency of 12.7 Hz, scan line of 21.5 degrees Total Optical Scan Angle (TOSA) and a quality factor of 20. The three dimensional (3D) display concept is proved with two of these modules by displaying two points sequentially at two different depths.Publication Metadata only Speech driven 3D head gesture synthesis(IEEE, 2006) Erdem, A. Tanju; N/A; Department of Computer Engineering; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Sargın, Mehmet Emre; Erzin, Engin; Yemez, Yücel; Tekalp, Ahmet Murat; Master Student; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; College of Engineering; N/A; 34503; 107907; 26207In this paper, we present a speech driven natural head gesture analysis and synthesis system. The proposed system assumes that sharp head movements are correlated with prominence in speech. For analysis, a binocular camera system is employed to capture the head motion of a talking person. The motion parameters associated with the 3D head motion are then used for extraction of the repetitive head gestures. In parallel, prosodic events are detected using an HMM structure with pitch and formant frequencies and speech intensity as audio features. For synthesis, the head motion parameters are estimated from the prosodic events based on a gesture-speech correlation model and then the associated Euler angles are used for speech driven animation of a 3D personalized talking head model. Results on head motion feature extraction, prosodic event detection and correlation modelling are provided..