http://dspace.cityu.edu.hk:80/handle/2031/3809 2013-04-30T06:48:14Z http://dspace.cityu.edu.hk:80/handle/2031/6655 Title: New strategies for designing live computer music Authors: Leung, Kei Cheuk Kechard ( 梁基爵) Abstract: This thesis explores the methodology for designing computer-based digital musical instruments (DMIs) to create a new direction for live computer music performance. Three forerunners of DMIs, Extended Tablet, Reactable and Silent Drum, are reviewed to give background information of DMIs, of which the individual components, performance contexts and artistic factors are investigated. The present study presents four case studies, each discussing a new DMI or installation, namely the Pod Drum, Control Table, 3D Fabric, and 'Transparent Caprice'. They were inspired by different motivations, artistic considerations, and technology involvement. Performances of original compositions for each of the creations are also presented. This thesis highlights three key implementations for the design of DMIs: (1) exploring gestural control in live computer music; (2) enhancing transparency of the control process and sound production of DMI designs; and (3) increasing the importance of repertoire and actual performances in the development of DMIs. Notes: CityU Call Number: ML1380 .L48 2011; 107 leaves : ill. (some col.) 30 cm.; Thesis (M.Phil.)--City University of Hong Kong, 2011.; Includes bibliographical references (leaves 105-107) 2011-01-01T00:00:00Z http://dspace.cityu.edu.hk:80/handle/2031/6283 Title: Digital puppertry : real-time performance in a mediatized age Authors: Wang, Zhe (王喆) Abstract: In this work, digital puppetry is discussed as a hybrid art form in which the performing objects are partially manipulated or wholly generated by algorithmic programs. The significant parameter here is the use of real-time technological interfaces, suggesting a synchronicity between the manipulator’s control and the performing object's resultant movement. While there is not a single ideal example of what digital puppetry, a wide range of digital forms or works (e.g., motion capture, machinima, Digital Marionette, The Sims, etc.) are analyzed in the context of improvisation and interaction through the employment of real-time technologies. In order to further examine the role it plays in this mediatized age, digital puppetry is proposed here both as a phenomenon that self-evidently is performance in the usual, aaesthetic sense of that term, and is also studied as performance in a broader sense suggested by the performance theory of Richard Schechner. Moreover, this study values Jean-François Lyotard’s performativity as a comparatively new theoretical framework in performance studies, useful to rethink the ongoing radical changes in the nature of performance in relation to technological developments. At this point, it is not my primary goal to develop a formal definition of digital puppetry, but to establish it as a significant contemporary phenomenon through a culturally and theoretically contextualized survey. Consequently, relevant cultural issues related to digital puppetry are addressed, such as play/perform, role/rule, agency/identity, and body/self complexes. By continuously expanding a database of human/computer interactive behavior, digital puppetry may create new forms of ritual for the global community. Keyword: digital puppetry, performance, real-time, body, agency Notes: CityU Call Number: PN1972 .W36 2010; 137 leaves 30 cm.; Thesis (M.Phil.)--City University of Hong Kong, 2010.; Includes bibliographical references (leaves 125-137) 2010-01-01T00:00:00Z http://dspace.cityu.edu.hk:80/handle/2031/6282 Title: Markov random field-based hierarchical handwritten Chinese character modeling Authors: Tian, Desai (田德赛) Abstract: This dissertation proposes a statistical-structural character modeling method based on the Markov Random Fields(MRFs) in the Handwritten Chinese Character Recognition(HCCR) problem. In the MRF framework, we view the character recognition as a labeling problem, as how well a given observation matches a character model. The MRF framework can represent both statistical and structural information of the Chinese character by the neighborhood systems and clique potentials. The neighborhood system denotes the most important stroke relationships. The clique potential is composed by prior clique potential based on our prior knowledge and likelihood clique potential represents both statistical and structural information, which is derived from Gaussian Mixture Models(GMMs). We add the radical information into our prior knowledge, thus form a hierarchical character structure in which radicals constitute characters, and strokes constitute radicals. With the help of radical structure, we can easily grasp the most important stroke relationships. We implemented a real-world application of character recognition. In the proposed HCCR system, we extract candidate strokes from character image by minimizing the single-site likelihood clique potentials, and find the best structural match between candidate strokes and stroke models by the relaxation labeling algorithm. The experiments done on the Korea Advanced Institute of Science and Technology (KAIST) character database demonstrate the practicability of proposed approaches. Notes: CityU Call Number: PL1074.5 .T53 2010; xi, 56 leaves : ill. 30 cm.; Thesis (M.Phil.)--City University of Hong Kong, 2010.; Includes bibliographical references (leaves 51-56) 2010-01-01T00:00:00Z http://dspace.cityu.edu.hk:80/handle/2031/6281 Title: Sequential Markov random fields for human body parts tracking Authors: Cao, Xiaoqin (曹小琴) Abstract: This thesis presents the sequential Markov random fields (SMRFs) for tracking human body parts in the monocular settings, which plays an important role in computer vision and pattern recognition with many potential applications in areas of entertainment, automatic surveillance, health care, virtual reality and human-computer interface. There has been increasing interests in developing an automatic system to detect, localize and track human body parts with flexibility and robustness. However, it is a challenging task to achieve high performance in terms of efficiency and accuracy because of the high degrees of freedom (DOF) of the articulated human body, background clutters, and missing body parts due to partial occlusions. We handle these problems by the hybrid strategy, where the temporal dependencies between two successive human poses are described by the sequential Monte Carlo (SMC) method, and the spatial relationships between body parts in a pose is described by the Markov random fields (MRFs). This hybrid SMRF is able to account for spatio-temporal dependencies in moving human parts, enhancing the overall tracking performance in partial occlusions and background clutters. Within the unified SMRF framework, we formulate the tracking task as a sequential labeling problem by minimizing the posterior energy function of both body parts’ temporal motion and their spatial structure. We also develop efficient inference and learning algorithms for the SMRF based on the relaxation labeling(RL). To reduce the search space, we use a labeling-by-synthesis manner to predict moving path based on MRF-based sequential importance sampling. The Experimental results from motion capture data and real walking video demonstrate that the SMRF can effectively and accurately detect and track human body parts. Notes: CityU Call Number: TA1634 .C36 2010; xiii, 73 leaves : ill. 30 cm.; Thesis (M.Phil.)--City University of Hong Kong, 2010.; Includes bibliographical references (leaves 68-73) 2010-01-01T00:00:00Z