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Publication Metadata only 3D articulated shape segmentation using motion information(Institute of Electrical and Electronics Engineers (IEEE), 2010) Department of Computer Engineering; N/A; Yemez, Yücel; Kalafatlar, Emre; Faculty Member; Master Student; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; 107907; N/AWe present a method for segmentation of articulated 3D shapes by incorporating the motion information obtained from time-varying models. We assume that the articulated shape is given in the form of a mesh sequence with fixed connectivity so that the inter-frame vertex correspondences, hence the vertex movements, are known a priori. We use different postures of an articulated shape in multiple frames to constitute an affinity matrix which encodes both temporal and spatial similarities between surface points. The shape is then decomposed into segments in spectral domain based on the affinity matrix using a standard K-means clustering algorithm. The performance of the proposed segmentation method is demonstrated on the mesh sequence of a human actor.Publication Metadata only 3D shape recovery and tracking from multi-camera video sequences via surface deformation(Institute of Electrical and Electronics Engineers (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. / Bu makale, çok kameralı video kullanarak zamanla değişen gerçek nesnelerin 3B yeniden yapılandırılmasını ve modellenmesini ele almaktadır. Çalışma iki aşamadan oluşmaktadır. İlk aşamada, nesnenin ilk şekli, bir yüzey deformasyon modeli kullanılarak silüetlerinden kurtarılır. Aynı deformasyon modeli, ikinci aşamada, yüzey evrimi yoluyla zamanla değişen siluet bilgisi yoluyla geri kazanılan ilk şekli izlemek için de kullanılır. Yüzey deformasyonu/evrimi modeli, sabit bağlantıya sahip uzamsal ve zamansal olarak pürüzsüz bir yüzey ağ temsili oluşturmamıza izin verir. Bu, sonunda, altta yatan hareketin anlamını koruyan ve işlemesi, görselleştirmesi, depolaması ve iletmesi çok daha verimli olan genel bir uzay-zaman temsiline yol açar.Publication Metadata only A distributed approach for computing sum aggregation in P2P networks(IEEE, 2011) N/A; Department of Computer Engineering; N/A; Özkasap, Öznur; Çem, Emrah; Faculty Member; PhD Student; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; 113507; N/ASince hand vein patterns are assumed not to change over time except in size and they are unique to each individual, researchers aim to construct a biometric control system based on hand vein patterns. Each hand vein pattern defines a graph structure. According to this, we converted each hand vein pattern to a graph and to match these graphs, we developed an algorithm based on (Graph Edit Distance) GED. GED is defined as the least cost graph edit operation sequence which is used to transform one graph to another. Our initial results confirm the utility of GED-based hand vein verification.Publication Metadata only Adaptive streaming of multiview video over P2P networks(Wiley, 2013) N/A; Department of Electrical and Electronics Engineering; Gürler, Cihat Göktuğ; Tekalp, Ahmet Murat; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 26207Three-dimensional (3D) video is the next natural step in the evolution of digital media technologies. Recent 3D auto-stereoscopic displays can display multiview video with up to 200 views. While it is possible to broadcast 3D stereo video (two views) over digital TV platforms today, streaming over IP provides a more flexible approach for distribution of stereo and free-view 3D media to home and mobile with different connection bandwidth and different 3D displays. Here, flexible transport refers to quality-scalable and view-scalable transport over the Internet. These scalability options are the key to deal with the biggest challenge, which is the scarcity of bandwidth in IP networks, in the delivery of multiview video. However, even with the scalability options at hand, it is very possible that the bandwidth requirement of the sender side can reach to critical levels and render such a service infeasible. Peer-to-peer (P2P) video streaming is a promising approach and has received significant attention recently and can be used to alleviate the problem of bandwidth scarcity in server-client-based applications. Unfortunately, P2P also introduces new challenges, such as handling unstable peer connections and peers' limited upload capacity. In this chapter, we provide an adaptive P2P video streaming solution that addresses these challenges for streaming multiview video over P2P overlays. We start with reviewing fundamental video transmission concepts and the state-of-the-art P2P video streaming solutions. We then take a look at beyond the state of the art and introduce the methods for enabling adaptive video streaming for P2P network to distribute legacy monoscopic video. Finally, we move to modifications that are needed to deliver multiview video in an adaptive manner over the Internet. We provide benchmark test results against the state of the P2P video streaming solutions to prove the superiority of the proposed approach in adaptive video transmission.Publication Metadata only Affect burst detection using multi-modal cues(IEEE, 2015) Department of Computer Engineering; Department of Computer Engineering; N/A; Department of Computer Engineering; N/A; Sezgin, Tevfik Metin; Yemez, Yücel; Türker, Bekir Berker; Erzin, Engin; Marzban, Shabbir; Faculty Member; Faculty Member; PhD Student; Faculty Member; Master Student; Department of Computer Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; Graduate School of Sciences and Engineering; 18632; 107907; N/A; 34503; N/ARecently, affect bursts have gained significant importance in the field of emotion recognition since they can serve as prior in recognising underlying affect bursts. In this paper we propose a data driven approach for detecting affect bursts using multimodal streams of input such as audio and facial landmark points. The proposed Gaussian Mixture Model based method learns each modality independently followed by combining the probabilistic outputs to form a decision. This gives us an edge over feature fusion based methods as it allows us to handle events when one of the modalities is too noisy or not available. We demonstrate robustness of the proposed approach on 'Interactive emotional dyadic motion capture database' (IEMOCAP) which contains realistic and natural dyadic conversations. This database is annotated by three annotators to segment and label affect bursts to be used for training and testing purposes. We also present performance comparison between SVM based methods and GMM based methods for the same configuration of experiments.Publication Metadata only Affect-expressive hand gestures synthesis and animation(IEEE, 2015) Department of Computer Engineering; N/A; Department of Computer Engineering; Erzin, Engin; Bozkurt, Elif; Yemez, Yücel; Faculty Member; PhD Student; Faculty Member; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; 34503; N/A; 107907Speech and hand gestures form a composite communicative signal that boosts the naturalness and affectiveness of the communication. We present a multimodal framework for joint analysis of continuous affect, speech prosody and hand gestures towards automatic synthesis of realistic hand gestures from spontaneous speech using the hidden semi-Markov models (HSMMs). To the best of our knowledge, this is the first attempt for synthesizing hand gestures using continuous dimensional affect space, i.e., activation, valence, and dominance. We model relationships between acoustic features describing speech prosody and hand gestures with and without using the continuous affect information in speaker independent configurations and evaluate the multimodal analysis framework by generating hand gesture animations, also via objective evaluations. Our experimental studies are promising, conveying the role of affect for modeling the dynamics of speech-gesture relationship. © 2015 IEEE.Publication Metadata only An annotation assistant for interactive debugging of programs with common synchronization idioms(2009) Qadeer, Shaz; N/A; Department of Computer Engineering; Department of Computer Engineering; Sezgin, Ali; Taşıran, Serdar; Elmas, Tayfun; Researcher; Faculty Member; PhD Student; Department of Computer Engineering; N/A; College of Engineering; Graduate School of Sciences and Engineering; N/A; N/A; N/AThis paper explores an approach to improving the practical usability of static verification tools for debugging synchronization idioms. Synchronization idioms such as mutual exclusion and readers/writer locks are widely-used to ensure atomicity of critical regions. We present an annotation assistant that automatically generates program annotations. These annotations express noninterference between program statements, ensured by the synchronization idioms, and are used to identify atomic code regions. This allows the programmer to debug the use of the idioms in the program. We start by formalizing several well-known idioms by providing an abstract semantics for each idiom. For programs that use these idioms, we require the programmer to provide a few predicates linking the idiom with its realization in terms of program variables. From these, we automatically generate a proof script that is mechanically checked. These scripts include steps such as automatically generating assertions and annotating program actions with them, introducing auxiliary variables and invariants. We have successfully shown the applicability of this approach to several concurrent programs from the literature.Publication Metadata only Analysis and synthesis of multiview audio-visual dance figures(IEEE, 2008) Canton-Ferrer C.; Tilmanne J.; Balcı K.; Bozkurt E.; Kızoǧlu I.Akarun L.; Erdem A.T.; Department of Electrical and Electronics Engineering; Department of Computer Engineering; Department of Computer Engineering; N/A; N/A; Tekalp, Ahmet Murat; Erzin, Engin; Yemez, Yücel; Ofli, Ferda; Demir, Yasemin; Faculty Member; Faculty Member; Faculty Member; PhD Student; Master Student; Department of Electrical and Electronics Engineering; Department of Computer Engineering; College of Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; 26207; 34503; 107907; N/A; N/A; N/AThis paper presents a framework for audio-driven human body motion analysis and synthesis. The video is analyzed to capture the time-varying posture of the dancer's body whereas the musical audio signal is processed to extract the beat information. The human body posture is extracted from multiview video information without any human intervention using a novel marker-based algorithm based on annealing particle filtering. Body movements of the dancer are characterized by a set of recurring semantic motion patterns, i.e., dance figures. Each dance figure is modeled in a supervised manner with a set of HMM (Hidden Markov Model) structures and the associated beat frequency. In synthesis, given an audio signal of a learned musical type, the motion parameters of the corresponding dance figures are synthesized via the trained HMM structures in synchrony with the input audio signal based on the estimated tempo information. Finally, the generated motion parameters are animated along with the musical audio using a graphical animation tool. Experimental results demonstrate the effectiveness of the proposed framework.Publication Metadata only Analysis of distributed algorithms for density estimation in VANETs (poster)(IEEE-Inst Electrical Electronics Engineers Inc, 2012) N/A; Department of Computer Engineering; Department of Electrical and Electronics Engineering; N/A; Özkasap, Öznur; Ergen, Sinem Çöleri; Akhtar, Nabeel; Faculty Member; Faculty Member; Master Student; Department of Computer Engineering; Department of Electrical and Electronics Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; 113507; 7211; N/AVehicle density is an important system metric used in monitoring road traffic conditions. Most of the existing methods for vehicular density estimation require either building an infrastructure, such as pressure pads, inductive loop detector, roadside radar, cameras and wireless sensors, or using a centralized approach based on counting the number of vehicles in a particular geographical location via clustering or grouping mechanisms. These techniques however suffer from low reliability and limited coverage as well as high deployment and maintenance cost. In this paper, we propose fully distributed and infrastructure-free mechanisms for the density estimation in vehicular ad hoc networks. Unlike previous distributed approaches, that either rely on group formation, or on vehicle flow and speed information to calculate density, our study is inspired by the mechanisms proposed for system size estimation in peer-to-peer networks. We adapted and implemented three fully distributed algorithms, namely Sample & Collide, Hop Sampling and Gossip-based Aggregation. The extensive simulations of these algorithms at different vehicle traffic densities and area sizes for both highways and urban areas reveal that Hop Sampling provides the highest accuracy in least convergence time and introduces least overhead on the network, but at the cost of higher load on the initiator node.Publication Metadata only Applicability of eigenvector centrality principle to data replication in MANETs(IEEE, 2007) N/A; Department of Computer Engineering; N/A; Özkasap, Öznur; Atsan, Emre; Faculty Member; Master Student; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; 113507; N/AAn efficient data replication service is crucial for improving data accessability and resource utilization as well as providing consistency in mobile ad hoc systems. In this study, we investigate the applicability of eigenvector centrality (EVC) principle as an aid to determine replica nodes for data items in mobile ad hoc networks. There exist several studies for mathematical modeling of networks and defining roles to nodes based on EVC analysis in static networks. For MANETs, utilization of EVC to determine dissemination power of nodes has been also recently explored. In contrast to prior work, we focus on the question of whether EVC analysis can be helpful in locating nodes with replica roles. We present our approaches for connectivity matrix construction that is significant for precise EVC analysis. Comparative simulation results and analysis are described for both data replication and dissemination as a function of system scalability. Simulation results show that connectivity matrix construction techniques do not result in too much disparity for the performance of data replication and identifying one of the replicas to be the eigenvector central node does not lead to an improvement in data accessability for large networks.