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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only An audio-driven dancing avatar(Springer, 2008) Balci, Koray; Kizoglu, Idil; Akarun, Lale; Canton-Ferrer, Cristian; Tilmanne, Joelle; Bozkurt, Elif; Erdem, A. Tanju; Department of Computer Engineering; N/A; N/A; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Yemez, Yücel; Ofli, Ferda; Demir, Yasemin; Erzin, Engin; Tekalp, Ahmet Murat; Faculty Member; PhD Student; Master Student; Faculty Member; Faculty Member; College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; 107907; N/A; N/A; 34503; 26207We present a framework for training and synthesis of an audio-driven dancing avatar. The avatar is trained for a given musical genre using the multicamera video recordings of a dance performance. 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. We consider two different marker-based schemes for the motion capture problem. The first scheme uses 3D joint positions to represent the body motion whereas the second uses joint angles. 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 the synthesis phase, an audio signal of unknown musical type is first classified, within a time interval, into one of the genres that have been learnt in the analysis phase, based on mel frequency cepstral coefficients (MFCC). The motion parameters of the corresponding dance figures are then synthesized via the trained HMM structures in synchrony with the audio signal based on the estimated tempo information. Finally, the generated motion parameters, either the joint angles or the 3D joint positions of the body, are animated along with the musical audio using two different animation tools that we have developed. Experimental results demonstrate the effectiveness of the proposed framework.Publication Metadata only On the convergence of ICA algorithms with symmetric orthogonalization(IEEE, 2008) Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Erdoğan, Alper Tunga; Faculty Member; College of Engineering; 41624We study the convergence behavior of Independent Component Analysis (ICA) algorithms that are based on the contrast function maximization and that employ symmetric orthogonalization method to guarantee the orthogonality property of the search matrix. In particular, the characterization of the critical points of the corresponding optimization problem and the stationary points of the conventional gradient ascent and fixed point algorithms are obtained. As an interesting and a useful feature of the symmetrical orthogonalization method, we show that the use of symmetric orthogonalization enables the monotonic convergence for the fixed point ICA algorithms that are based on the convex contrast functions.Publication Metadata only Universal switching portfolios under transaction costs(Ieee, 2008) Singer, Andrew C.; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Kozat, Süleyman Serdar; Faculty Member; College of Engineering; 177972In this paper, we consider online (sequential) portfolio selection in a competitive algorithm framework under transaction costs. We construct a sequential algorithm for portfolio selection that asymptotically achieves the wealth of the best piecewise constant rebalanced portfolio tuned to the underlying individual sequence of price relative vectors where we pay a fixed percent commission for each transaction. Without knowledge of the investment duration, the algorithm can perform as well as the best investment algorithm that can choose both the partitioning of the sequence of the price relative vectors as well as the best constant rebalanced portfolio within each segment based on knowledge of the sequence of price relative vectors in advance. We use a transition diagram similar to that in [1] to compete with an exponential number of switching investment strategies, using only linear complexity in the data length for combination.Publication Metadata only Universal portfolios via context trees(IEEE, 2008) Singer, Andrew C.; Bean, Andrew J.; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Kozat, Süleyman Serdar; Faculty Member; College of Engineering; 177972In this paper, we consider the sequential portfolio investment problem considered by Cover [3] and extend the results of [3] to the class of piecewise constant rebalanced portfolios that are tuned to the underlying sequence of price relatives. Here, the piecewise constant models are used to partition the space of past price relative vectors where we assign a different constant rebalanced portfolio to each region independently. We then extend these results where we compete against a doubly exponential number of piecewise constant portfolios that are represented by a context tree. We use the context tree to achieve the wealth of a portfolio selection algorithm that can choose both its partitioning of the space of the past price relatives and its constant rebalanced portfolio within each region of the partition, based on observing the entire sequence of price relatives in advance, uniformly, for every bounded deterministic sequence of price relative vectors. This performance is achieved with a portfolio algorithm whose complexity is only linear in the depth of the context tree per investment period. We demonstrate that the resulting portfolio algorithm achieves significant gains on historical stock pairs over the algorithm of [3] and the best constant rebalanced portfolio.Publication Metadata only Audio-driven human body motion analysis and synthesis(IEEE, 2008) Canton-Ferrer, C.; Tilmanne, J.; Bozkurt, E.; N/A; N/A; Department of Computer Engineering; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Ofli, Ferda; Demir, Yasemin; Yemez, Yücel; Erzin, Engin; Tekalp, Ahmet Murat; PhD Student; Master Student; Faculty Member; Faculty Member; Faculty Member; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; College of Engineering; N/A; N/A; 107907; 34503; 26207This paper presents a framework for audio-driven human body motion analysis and synthesis. We address the problem in the context of a dance performance, where gestures and movements of the dancer are mainly driven by a musical piece and characterized by the repetition of a set of dance figures. The system is trained in a supervised manner using the multiview video recordings of the dancer. 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. Audio is analyzed to extract beat and tempo information. The joint analysis of audio and motion features provides a correlation model that is then used to animate a dancing avatar when driven with any musical piece of the same genre. Results are provided showing the effectiveness of the proposed algorithm.Publication Metadata only Snowflakes: a design speculation for a modular prototyping tool for rapidly designing smart wearables(Assoc Computing Machinery, 2018) Insel, Selin; N/A; Department of Electrical and Electronics Engineering; Department of Media and Visual Arts; Department of Electrical and Electronics Engineering; Department of Media and Visual Arts; Buruk, Oğuz Turan; Onbaşlı, Mehmet Cengiz; Özcan, Oğuzhan; PhD Student; Faculty Member; Faculty Member; KU Arçelik Research Center for Creative Industries (KUAR) / KU Arçelik Yaratıcı Endüstriler Uygulama ve Araştırma Merkezi (KUAR); Graduate School of Social Sciences and Humanities; College of Engineering; College of Social Sciences and Humanities; N/A; 258783; 12532Aesthetics qualities are critical aspects for smart jewelry as they are worn and considered as expressive artefacts. However, current tools for prototyping smart jewelry do not put aesthetic considerations as a primary concern. Therefore, we created Snowflakes, a design speculation for a modular, "snap-on-off", prototyping tool for designing smart jewelry. The design requirements of Snowflakes were determined after studying non-smart jewelry and extracting 7 parameters for them (limb, material, grip, fastener type, decoration, decoration placement and form). Drawing upon these parameters, Snowflakes were proposed as a tool that would allow prototyping smart jewelry by synthesizing conventional jewelry's form language with smart jewelry which is adorned with technology. This paper explores using this product as a design tool to experiment on designs blending aesthetics and function.Publication Metadata only 300 GHz broadband transceiver design for low-THz band wireless communications in indoor internet of things(Ieee, 2017) N/A; Department of Electrical and Electronics Engineering; N/A; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Khalid, Nabil; Abbasi, Naveed Ahmed; Akan, Özgür Barış; Researcher; PhD Student; Faculty Member; College of Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 6647This paper presents the architectural design of a 300 GHz transceiver system that can be used to explore the high speed communication opportunities offered by the Terahertz (THz) band for advanced applications of Internet-of-Things (IoT). We use low cost industry ready components to prepare a fully customizable THz band communication system that provides a bandwidth of 20 GHz that is easily extendable up to 40 GHz. Component parameters arc carefully observed and used in simulations to predict the system performance while the compatibility of different components is ensured to produce a reliable design. Our results show that the receiver provides a conversion gain of 51 dB with a noise figure (NE) of 9.56 dB to achieve a data rate of 90.31 Gbps at an operation range of 2 meters, which is suitable for high speed indoor IoT nodes. The flexible design of the transceiver provides groundwork for further research efforts in 5G IoT applications and pushing boundaries of throughputs to the order of terabits per second (Tbps).Publication Metadata only Delay optimization for switchless ARINC 664 mesh networks with cyclic dependencies(IEEE, 2021) Kaya, Sedat; Gul, Bekir; Demir, M. Selim; Hokelek, Ibrahim; Garip, Muhammet; Uvet, Huseyin; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Faculty Member; College of Engineering; 7211Switchless mesh topologies for modern avionics networks have been gaining popularity in recent years due to its inherent advantages in terms of the size, weight, and power (SWaP). However, it is a challenging task to calculate Network Calculus (NC) delay bounds for switchless mesh topologies due to the cyclic dependency problem, where the paths of interfering traffic flows form cycles. This paper, first, presents a method to automatically calculate the NC worst-case delay bounds for any switchless mesh topology with arbitrary traffic flows, where the cyclic dependency problem is solved using Time Stopping Method (TSM). Furthermore, we propose a Genetic Algorithm (GA) based delay optimization mechanism for switchless ARINC 664 mesh networks, where GA is used for exploring alternative paths to obtain tighter NC worst-case end-to-end delay bounds. The performance evaluation shows that the proposed GA based delay optimization provides consistently and significantly tighter delay bounds.