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- All Subjects: Computer Science
- All Subjects: Music
- Genre: Doctoral Dissertation
- Genre: Art music
- Creators: Li, Baoxin
- Creators: Hill, Gary
Description
Reliable extraction of human pose features that are invariant to view angle and body shape changes is critical for advancing human movement analysis. In this dissertation, the multifactor analysis techniques, including the multilinear analysis and the multifactor Gaussian process methods, have been exploited to extract such invariant pose features from video data by decomposing various key contributing factors, such as pose, view angle, and body shape, in the generation of the image observations. Experimental results have shown that the resulting pose features extracted using the proposed methods exhibit excellent invariance properties to changes in view angles and body shapes. Furthermore, using the proposed invariant multifactor pose features, a suite of simple while effective algorithms have been developed to solve the movement recognition and pose estimation problems. Using these proposed algorithms, excellent human movement analysis results have been obtained, and most of them are superior to those obtained from state-of-the-art algorithms on the same testing datasets. Moreover, a number of key movement analysis challenges, including robust online gesture spotting and multi-camera gesture recognition, have also been addressed in this research. To this end, an online gesture spotting framework has been developed to automatically detect and learn non-gesture movement patterns to improve gesture localization and recognition from continuous data streams using a hidden Markov network. In addition, the optimal data fusion scheme has been investigated for multicamera gesture recognition, and the decision-level camera fusion scheme using the product rule has been found to be optimal for gesture recognition using multiple uncalibrated cameras. Furthermore, the challenge of optimal camera selection in multi-camera gesture recognition has also been tackled. A measure to quantify the complementary strength across cameras has been proposed. Experimental results obtained from a real-life gesture recognition dataset have shown that the optimal camera combinations identified according to the proposed complementary measure always lead to the best gesture recognition results.
ContributorsPeng, Bo (Author) / Qian, Gang (Thesis advisor) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2011
Description
The purpose of this project was to commission, perform, and discuss a new work for an instrument pairing not often utilized, oboe and percussion. The composer, Alyssa Morris, was selected in June 2009. Her work, titled Forecast, was completed in October of 2009 and premiered in February of 2010, as part of a program showcasing music for oboe and percussion. Included in this document is a detailed biography of the composer, a description of the four movements of Forecast, performance notes for each movement, a diagram for stage set-up, the full score, the program from the premiere performance with biographies of all the performers involved, and both a live recording and MIDI sound file. The performance notes discuss issues that arose during preparation for the premiere and should help avoid potential pitfalls. TrevCo Music, publisher of the work, graciously allowed inclusion of the full score. This score is solely for use in this document; please visit the publisher's website for purchasing information. The commission and documentation of this composition are intended to add to the repertoire for oboe in an unusual instrument pairing and to encourage further exploration of such combinations.
ContributorsCreamer, Caryn (Author) / Schuring, Martin (Thesis advisor) / Hill, Gary (Committee member) / Holbrook, Amy (Committee member) / Micklich, Albie (Committee member) / Spring, Robert (Committee member) / Arizona State University (Publisher)
Created2011
Description
During the twentieth-century, the dual influence of nationalism and modernism in the eclectic music from Latin America promoted an idiosyncratic style which naturally combined traditional themes, popular genres and secular music. The saxophone, commonly used as a popular instrument, started to develop a prominent role in Latin American classical music beginning in 1970. The lack of exposure and distribution of the Latin American repertoire has created a general perception that composers are not interested in the instrument, and that Latin American repertoire for classical saxophone is minimal. However, there are more than 1100 works originally written for saxophone in the region, and the amount continues to grow. This Modern Latin American Repertoire for Classical Saxophone: Recording Project and Performance Guide document establishes and exhibits seven works by seven representative Latin American composers.The recording includes works by Carlos Gonzalo Guzman (Colombia), Ricardo Tacuchian (Brazil), Roque Cordero (Panama), Luis Naón (Argentina), Andrés Alén-Rodriguez (Cuba), Alejandro César Morales (Mexico) and Jose-Luis Maúrtua (Peru), featuring a range of works for solo alto saxophone to alto saxophone with piano, alto saxophone with vibraphone, and tenor saxophone with electronic tape; thus forming an important selection of Latin American repertoire. Complete recorded performances of all seven pieces are supplemented by biographical, historical, and performance practice suggestions. The result is a written and audio guide to some of the most important pieces composed for classical saxophone in Latin America, with an emphasis on fostering interest in, and research into, composers who have contributed in the development and creation of the instrument in Latin America.
ContributorsOcampo Cardona, Javier Andrés (Author) / McAllister, Timothy (Thesis advisor) / Spring, Robert (Committee member) / Hill, Gary (Committee member) / Pilafian, Sam (Committee member) / Rogers, Rodney (Committee member) / Gardner, Joshua (Committee member) / Arizona State University (Publisher)
Created2011
Description
Bridging semantic gap is one of the fundamental problems in multimedia computing and pattern recognition. The challenge of associating low-level signal with their high-level semantic interpretation is mainly due to the fact that semantics are often conveyed implicitly in a context, relying on interactions among multiple levels of concepts or low-level data entities. Also, additional domain knowledge may often be indispensable for uncovering the underlying semantics, but in most cases such domain knowledge is not readily available from the acquired media streams. Thus, making use of various types of contextual information and leveraging corresponding domain knowledge are vital for effectively associating high-level semantics with low-level signals with higher accuracies in multimedia computing problems. In this work, novel computational methods are explored and developed for incorporating contextual information/domain knowledge in different forms for multimedia computing and pattern recognition problems. Specifically, a novel Bayesian approach with statistical-sampling-based inference is proposed for incorporating a special type of domain knowledge, spatial prior for the underlying shapes; cross-modality correlations via Kernel Canonical Correlation Analysis is explored and the learnt space is then used for associating multimedia contents in different forms; model contextual information as a graph is leveraged for regulating interactions among high-level semantic concepts (e.g., category labels), low-level input signal (e.g., spatial/temporal structure). Four real-world applications, including visual-to-tactile face conversion, photo tag recommendation, wild web video classification and unconstrained consumer video summarization, are selected to demonstrate the effectiveness of the approaches. These applications range from classic research challenges to emerging tasks in multimedia computing. Results from experiments on large-scale real-world data with comparisons to other state-of-the-art methods and subjective evaluations with end users confirmed that the developed approaches exhibit salient advantages, suggesting that they are promising for leveraging contextual information/domain knowledge for a wide range of multimedia computing and pattern recognition problems.
ContributorsWang, Zhesheng (Author) / Li, Baoxin (Thesis advisor) / Sundaram, Hari (Committee member) / Qian, Gang (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2011
Description
Finger motion and hand posture of six professional clarinetists (defined by entrance into or completion of a doctorate of musical arts degree in clarinet performance) were recorded using a pair of CyberGloves® in Arizona State University's Center for Cognitive Ubiquitous Computing Laboratory. Performance tasks included performing a slurred three-octave chromatic scale in sixteenth notes, at sixty quarter-note beats per minute, three times, with a metronome and a short pause between repetitions, and forming three pedagogical hand postures. Following the CyberGloves® tasks, each subject completed a questionnaire about equipment, playing history, practice routines, health practices, and hand usage during computer and sports activities. CyberGlove® data were analyzed to find average hand/finger postures and differences for each pitch across subjects, subject variance in the performance task and differences in ascending and descending postures of the chromatic scale. The data were also analyzed to describe generalized finger posture characteristics based on hand size, whether right hand thumb position affects finger flexion, and whether professional clarinetists use similar finger/hand postures when performing on clarinet, holding a tennis ball, allowing hands to hang freely by the sides, or form a "C" shape. The findings of this study suggest an individual approach based on hand size is necessary for teaching clarinet hand posture.
ContributorsHarger, Stefanie (Author) / Spring, Robert (Thesis advisor) / Hill, Gary (Committee member) / Koonce, Frank (Committee member) / Norton, Kay (Committee member) / Stauffer, Sandy (Committee member) / Arizona State University (Publisher)
Created2011
Description
A statement appearing in social media provides a very significant challenge for determining the provenance of the statement. Provenance describes the origin, custody, and ownership of something. Most statements appearing in social media are not published with corresponding provenance data. However, the same characteristics that make the social media environment challenging, including the massive amounts of data available, large numbers of users, and a highly dynamic environment, provide unique and untapped opportunities for solving the provenance problem for social media. Current approaches for tracking provenance data do not scale for online social media and consequently there is a gap in provenance methodologies and technologies providing exciting research opportunities. The guiding vision is the use of social media information itself to realize a useful amount of provenance data for information in social media. This departs from traditional approaches for data provenance which rely on a central store of provenance information. The contemporary online social media environment is an enormous and constantly updated "central store" that can be mined for provenance information that is not readily made available to the average social media user. This research introduces an approach and builds a foundation aimed at realizing a provenance data capability for social media users that is not accessible today.
ContributorsBarbier, Geoffrey P (Author) / Liu, Huan (Thesis advisor) / Bell, Herbert (Committee member) / Li, Baoxin (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
Description
Multi-label learning, which deals with data associated with multiple labels simultaneously, is ubiquitous in real-world applications. To overcome the curse of dimensionality in multi-label learning, in this thesis I study multi-label dimensionality reduction, which extracts a small number of features by removing the irrelevant, redundant, and noisy information while considering the correlation among different labels in multi-label learning. Specifically, I propose Hypergraph Spectral Learning (HSL) to perform dimensionality reduction for multi-label data by exploiting correlations among different labels using a hypergraph. The regularization effect on the classical dimensionality reduction algorithm known as Canonical Correlation Analysis (CCA) is elucidated in this thesis. The relationship between CCA and Orthonormalized Partial Least Squares (OPLS) is also investigated. To perform dimensionality reduction efficiently for large-scale problems, two efficient implementations are proposed for a class of dimensionality reduction algorithms, including canonical correlation analysis, orthonormalized partial least squares, linear discriminant analysis, and hypergraph spectral learning. The first approach is a direct least squares approach which allows the use of different regularization penalties, but is applicable under a certain assumption; the second one is a two-stage approach which can be applied in the regularization setting without any assumption. Furthermore, an online implementation for the same class of dimensionality reduction algorithms is proposed when the data comes sequentially. A Matlab toolbox for multi-label dimensionality reduction has been developed and released. The proposed algorithms have been applied successfully in the Drosophila gene expression pattern image annotation. The experimental results on some benchmark data sets in multi-label learning also demonstrate the effectiveness and efficiency of the proposed algorithms.
ContributorsSun, Liang (Author) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Liu, Huan (Committee member) / Mittelmann, Hans D. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Works for clarinet in the twentieth century exist in abundance; furthermore, the number of extant works from the Classical period is substantial. However, works for solo clarinet in the late-Romantic style are lacking; most of the significant literature for clarinet is contained in orchestral works. Therefore, the purpose of this project is to add to the solo clarinet repertoire of the late Romantic-style through the transcription of works written originally for viola. The four works transcribed for this project are by York Bowen. Bowen was a British composer and pianist who taught at the Royal Academy of Music in England. Although his career flourished in the twentieth century, his music reflects the music of the late-Romantic style. The project includes a transcription of Bowen's Sonata No. 1 in C minor, Op. 18 for viola and piano, Sonata No. 2 in F major, Op. 22 for viola and piano, Romance in D-flat for viola and piano, and Phantasy in F, Op. 54 for viola and piano. Additionally, a brief examination of Bowen's life, an overview of each piece, details regarding transcription parts, a list of changes made to the original part, and a recording of each transcription is included in the document.
ContributorsDeBoer, Andrew Caleb (Author) / Spring, Robert S (Thesis advisor) / Hill, Gary (Committee member) / Norton, Kay (Committee member) / McAllister, Timothy (Committee member) / Stauffer, Sandra (Committee member) / Arizona State University (Publisher)
Created2011
Description
The marimba has garnered increased attention in percussion performance over the past thirty years. Literature for beginners through professionals in a multitude of styles have been written. With the ever-growing number of marimbists since the 1980's there has been a high demand for new works. Numerous pieces were created through commissions: composers contracted to write music by individuals, institutions, and consortia. Three primary types of marimba solo music were written: unaccompanied solos, concerti, and marimba solos with electronic accompaniment. Since electronic music is relatively new in marimba performance, there is very little information published regarding this topic. Only a handful of well-known compositions in this genre have been widely performed, and a great number of existing works are unfamiliar to the percussion world. The goal of this study is to generate an overview of electronic music in marimba performance by compiling a chronological catalog of compositions written for solo marimba with electronics. In addition, this study wishes to promote this genre of solo marimba music through the commission, performance, examination, and recording of a new work for marimba and electronics. It is the author's wish to bring this topic to percussionists' attention, and to enrich the marimba solo literature by both exploring existing literature and encouraging the commissioning and performance of marimba music.
ContributorsChen, Yi-Chia (Author) / Smith, J.B. (Thesis advisor) / Bush, Jeffery (Committee member) / Hackbarth, Glenn (Committee member) / Hill, Gary (Committee member) / Sunkett, Mark (Committee member) / Arizona State University (Publisher)
Created2011
Description
The study of acoustic ecology is concerned with the manner in which life interacts with its environment as mediated through sound. As such, a central focus is that of the soundscape: the acoustic environment as perceived by a listener. This dissertation examines the application of several computational tools in the realms of digital signal processing, multimedia information retrieval, and computer music synthesis to the analysis of the soundscape. Namely, these tools include a) an open source software library, Sirens, which can be used for the segmentation of long environmental field recordings into individual sonic events and compare these events in terms of acoustic content, b) a graph-based retrieval system that can use these measures of acoustic similarity and measures of semantic similarity using the lexical database WordNet to perform both text-based retrieval and automatic annotation of environmental sounds, and c) new techniques for the dynamic, realtime parametric morphing of multiple field recordings, informed by the geographic paths along which they were recorded.
ContributorsMechtley, Brandon Michael (Author) / Spanias, Andreas S (Thesis advisor) / Sundaram, Hari (Thesis advisor) / Cook, Perry R. (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2013