Matching Items (233)
Filtering by
- Genre: Academic theses
- Creators: Li, Baoxin
- Creators: Norton, Kay
- Member of: Theses and Dissertations
Description
Currently Java is making its way into the embedded systems and mobile devices like androids. The programs written in Java are compiled into machine independent binary class byte codes. A Java Virtual Machine (JVM) executes these classes. The Java platform additionally specifies the Java Native Interface (JNI). JNI allows Java code that runs within a JVM to interoperate with applications or libraries that are written in other languages and compiled to the host CPU ISA. JNI plays an important role in embedded system as it provides a mechanism to interact with libraries specific to the platform. This thesis addresses the overhead incurred in the JNI due to reflection and serialization when objects are accessed on android based mobile devices. It provides techniques to reduce this overhead. It also provides an API to access objects through its reference through pinning its memory location. The Android emulator was used to evaluate the performance of these techniques and we observed that there was 5 - 10 % performance gain in the new Java Native Interface.
ContributorsChandrian, Preetham (Author) / Lee, Yann-Hang (Thesis advisor) / Davulcu, Hasan (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2011
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
With the introduction of compressed sensing and sparse representation,many image processing and computer vision problems have been looked at in a new way. Recent trends indicate that many challenging computer vision and image processing problems are being solved using compressive sensing and sparse representation algorithms. This thesis assays some applications of compressive sensing and sparse representation with regards to image enhancement, restoration and classication. The first application deals with image Super-Resolution through compressive sensing based sparse representation. A novel framework is developed for understanding and analyzing some of the implications of compressive sensing in reconstruction and recovery of an image through raw-sampled and trained dictionaries. Properties of the projection operator and the dictionary are examined and the corresponding results presented. In the second application a novel technique for representing image classes uniquely in a high-dimensional space for image classification is presented. In this method, design and implementation strategy of the image classification system through unique affine sparse codes is presented, which leads to state of the art results. This further leads to analysis of some of the properties attributed to these unique sparse codes. In addition to obtaining these codes, a strong classier is designed and implemented to boost the results obtained. Evaluation with publicly available datasets shows that the proposed method outperforms other state of the art results in image classication. The final part of the thesis deals with image denoising with a novel approach towards obtaining high quality denoised image patches using only a single image. A new technique is proposed to obtain highly correlated image patches through sparse representation, which are then subjected to matrix completion to obtain high quality image patches. Experiments suggest that there may exist a structure within a noisy image which can be exploited for denoising through a low-rank constraint.
ContributorsKulkarni, Naveen (Author) / Li, Baoxin (Thesis advisor) / Ye, Jieping (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
Description
There are many wireless communication and networking applications that require high transmission rates and reliability with only limited resources in terms of bandwidth, power, hardware complexity etc.. Real-time video streaming, gaming and social networking are a few such examples. Over the years many problems have been addressed towards the goal of enabling such applications; however, significant challenges still remain, particularly, in the context of multi-user communications. With the motivation of addressing some of these challenges, the main focus of this dissertation is the design and analysis of capacity approaching coding schemes for several (wireless) multi-user communication scenarios. Specifically, three main themes are studied: superposition coding over broadcast channels, practical coding for binary-input binary-output broadcast channels, and signalling schemes for two-way relay channels. As the first contribution, we propose an analytical tool that allows for reliable comparison of different practical codes and decoding strategies over degraded broadcast channels, even for very low error rates for which simulations are impractical. The second contribution deals with binary-input binary-output degraded broadcast channels, for which an optimal encoding scheme that achieves the capacity boundary is found, and a practical coding scheme is given by concatenation of an outer low density parity check code and an inner (non-linear) mapper that induces desired distribution of "one" in a codeword. The third contribution considers two-way relay channels where the information exchange between two nodes takes place in two transmission phases using a coding scheme called physical-layer network coding. At the relay, a near optimal decoding strategy is derived using a list decoding algorithm, and an approximation is obtained by a joint decoding approach. For the latter scheme, an analytical approximation of the word error rate based on a union bounding technique is computed under the assumption that linear codes are employed at the two nodes exchanging data. Further, when the wireless channel is frequency selective, two decoding strategies at the relay are developed, namely, a near optimal decoding scheme implemented using list decoding, and a reduced complexity detection/decoding scheme utilizing a linear minimum mean squared error based detector followed by a network coded sequence decoder.
ContributorsBhat, Uttam (Author) / Duman, Tolga M. (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Li, Baoxin (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2011
Description
In many classication problems data samples cannot be collected easily, example in drug trials, biological experiments and study on cancer patients. In many situations the data set size is small and there are many outliers. When classifying such data, example cancer vs normal patients the consequences of mis-classication are probably more important than any other data type, because the data point could be a cancer patient or the classication decision could help determine what gene might be over expressed and perhaps a cause of cancer. These mis-classications are typically higher in the presence of outlier data points. The aim of this thesis is to develop a maximum margin classier that is suited to address the lack of robustness of discriminant based classiers (like the Support Vector Machine (SVM)) to noise and outliers. The underlying notion is to adopt and develop a natural loss function that is more robust to outliers and more representative of the true loss function of the data. It is demonstrated experimentally that SVM's are indeed susceptible to outliers and that the new classier developed, here coined as Robust-SVM (RSVM), is superior to all studied classier on the synthetic datasets. It is superior to the SVM in both the synthetic and experimental data from biomedical studies and is competent to a classier derived on similar lines when real life data examples are considered.
ContributorsGupta, Sidharth (Author) / Kim, Seungchan (Thesis advisor) / Welfert, Bruno (Committee member) / Li, Baoxin (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
ABSTRACT études; written for violin ensemble, which include violin duets, trios, and quartets, are less numerous than solo études.; These works rarely go by the title "étude;," and have not been the focus of much scholarly research. Ensemble études; have much to offer students, teachers and composers, however, because they add an extra dimension to the learning, teaching, and composing processes. This document establishes the value of ensemble études; in pedagogy and explores applications of the repertoire currently available. Rather than focus on violin duets, the most common form of ensemble étude;, it mainly considers works for three and four violins without accompaniment. Concentrating on the pedagogical possibilities of studying études; in a group, this document introduces creative ways that works for violin ensemble can be used as both études; and performance pieces. The first two chapters explore the history and philosophy of the violin étude; and multiple-violin works, the practice of arranging of solo études; for multiple instruments, and the benefits of group learning and cooperative learning that distinguish ensemble étude; study from solo étude; study. The third chapter is an annotated survey of works for three and four violins without accompaniment, and serves as a pedagogical guide to some of the available repertoire. Representing a wide variety of styles, techniques and levels, it illuminates an historical association between violin ensemble works and pedagogy. The fourth chapter presents an original composition by the author, titled Variations on a Scottish Folk Song: étude; for Four Violins, with an explanation of the process and techniques used to create this ensemble étude.; This work is an example of the musical and technical integration essential to étude; study, and demonstrates various compositional traits that promote cooperative learning. Ensemble études; are valuable pedagogical tools that deserve wider exposure. It is my hope that the information and ideas about ensemble études; in this paper and the individual descriptions of the works presented will increase interest in and application of violin trios and quartets at the university level.
ContributorsLundell, Eva Rachel (Contributor) / Swartz, Jonathan (Thesis advisor) / Rockmaker, Jody (Committee member) / Buck, Nancy (Committee member) / Koonce, Frank (Committee member) / Norton, Kay (Committee member) / Arizona State University (Publisher)
Created2011
Description
The name of Geechie Wiley has surfaced only rarely since 1931, when she recorded her second session with the Paramount Company in Grafton, WI. A few scholars including Paul Oliver and Greil Marcus unearthed and promoted her music and called for further research on this enigmatic figure. In other publications, Wiley is frequently given only passing mention in long lists of talented female blues singer-guitarists, or briefly discussed in descriptions of songsters. Her music is lauded in the liner notes of the myriad compilation albums that have re-released her recordings. However, prior to this study, Marcus's three-page profile is the longest work written about Wiley; other contributions range between one sentence and two paragraphs in length. None really answers the question: who was Geechie Wiley? This thesis begins by documenting my attempt to piece together all information presently available on Geechie Wiley. A biographical chapter, supplemented with a discussion of the blues songster, follows. I then discuss my methodology and philosophy for transcription. This is followed by a critical and comparative analysis of the recordings, using the transcriptions as supplements. Finally, my fifth chapter presents conclusions about Wiley's life, career, and disappearance. My transcriptions of Wiley's six songs are found in the first appendix. Reproductions of Paramount Records advertisements are located in the final appendix. In these ways, this thesis argues that Wiley's work traces the transformation of African-American music from the general secular music of the songsters to the iconic blues genre.
ContributorsCordeiro, AnneMarie Youell (Author) / Norton, Kay (Thesis advisor) / Mook, Richard (Committee member) / Sunkett, Mark (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