Matching Items (627)
Filtering by

Clear all filters

149977-Thumbnail Image.png
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

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
149991-Thumbnail Image.png
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

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
149794-Thumbnail Image.png
Description
Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them

Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. Genes have widely different pertinences to the etiology and pathology of diseases. Thus, they can be ranked according to their disease-significance on a genomic scale, which is the subject of gene prioritization. Given a set of genes known to be related to a disease, it is reasonable to use them as a basis to determine the significance of other candidate genes, which will then be ranked based on the association they exhibit with respect to the given set of known genes. Experimental and computational data of various kinds have different reliability and relevance to a disease under study. This work presents a gene prioritization method based on integrated biological networks that incorporates and models the various levels of relevance and reliability of diverse sources. The method is shown to achieve significantly higher performance as compared to two well-known gene prioritization algorithms. Essentially, no bias in the performance was seen as it was applied to diseases of diverse ethnology, e.g., monogenic, polygenic and cancer. The method was highly stable and robust against significant levels of noise in the data. Biological networks are often sparse, which can impede the operation of associationbased gene prioritization algorithms such as the one presented here from a computational perspective. As a potential approach to overcome this limitation, we explore the value that transcription factor binding sites can have in elucidating suitable targets. Transcription factors are needed for the expression of most genes, especially in higher organisms and hence genes can be associated via their genetic regulatory properties. While each transcription factor recognizes specific DNA sequence patterns, such patterns are mostly unknown for many transcription factors. Even those that are known are inconsistently reported in the literature, implying a potentially high level of inaccuracy. We developed computational methods for prediction and improvement of transcription factor binding patterns. Tests performed on the improvement method by employing synthetic patterns under various conditions showed that the method is very robust and the patterns produced invariably converge to nearly identical series of patterns. Preliminary tests were conducted to incorporate knowledge from transcription factor binding sites into our networkbased model for prioritization, with encouraging results. To validate these approaches in a disease-specific context, we built a schizophreniaspecific network based on the inferred associations and performed a comprehensive prioritization of human genes with respect to the disease. These results are expected to be validated empirically, but computational validation using known targets are very positive.
ContributorsLee, Jang (Author) / Gonzalez, Graciela (Thesis advisor) / Ye, Jieping (Committee member) / Davulcu, Hasan (Committee member) / Gallitano-Mendel, Amelia (Committee member) / Arizona State University (Publisher)
Created2011
Description

Soiled: An Environmental Podcast is a six episode series that addresses common environmental topics and debunks myths that surround those topics.

ContributorsTurner, Natalie Ann (Co-author) / Kuta, Tiffany (Co-author) / Jones, Cassity (Co-author) / Boyer, Mackenzie (Thesis director) / Ward, Kristen (Committee member) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
147998-Thumbnail Image.png
Description

For this Creative Project, I decided to explore the elements that set novellas apart from other genres and then experiment writing in the form. In doing so, I took into account three main categories: Plot Structure, Character Development, Style/Format, and then used my findings to write 45 pages of a

For this Creative Project, I decided to explore the elements that set novellas apart from other genres and then experiment writing in the form. In doing so, I took into account three main categories: Plot Structure, Character Development, Style/Format, and then used my findings to write 45 pages of a novella titled Emmy and Me.

ContributorsBingham, Roxanne Marie (Author) / Irish, Jennifer (Thesis director) / Danielson, Jonathan (Committee member) / Department of English (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

Filmmakers seek to create story pieces that are visually beautiful and engage the full attention of their audience. They typically abide by a 3-step process moving through pre-production, production, and post-production. Within each step, there are a series of tasks that need to be accomplished in order to reach the

Filmmakers seek to create story pieces that are visually beautiful and engage the full attention of their audience. They typically abide by a 3-step process moving through pre-production, production, and post-production. Within each step, there are a series of tasks that need to be accomplished in order to reach the completed film. A successful film requires careful planning and strategy in pre-production, timely and decisive execution in production, and minimal unforeseen retouching in post-production.<br/><br/>Even though filmmakers have continued to follow the same formula throughout the decades, the filmmaking process has remained largely inefficient. It is extremely common for pre-production planning to be undercut, for production filming to run far too long, and for post-production VFX and editing to send the project over budget. These instances can cause major issues as the project is being finalized. In many scenarios portions of the project need to be reshot, the box office revenue isn’t enough to make up for extensive VFX retouching, or the project may never even come to fruition. <br/><br/>The reason for this recurring theme of films being over budget and out of time is quite simply that technology has made filmmakers lazy. “Fix it in post” is a disgustingly common phrase used in the film industry. It describes the utter abuse of computer retouching in the post-production phase of filmmaking. Despite working in an industry that seeks to entertain the human eye, filmmakers have become blind to all of the small mistakes that could cost them hundreds of hours and millions of dollars in the long run.

ContributorsKlewicki, Tallee Jo (Author) / Shin, Dosun (Thesis director) / Eliciana, Nascimento (Committee member) / The Design School (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
147924-Thumbnail Image.png
Description

My project is designed to provide art education to incarcerated youth in Arizona. This project will address two current issues in Arizona; the underfunding of art programs and high rates of incarceration. As of 2021, there are no state-funded art programs in Arizona. Arizona is tied with Texas for the

My project is designed to provide art education to incarcerated youth in Arizona. This project will address two current issues in Arizona; the underfunding of art programs and high rates of incarceration. As of 2021, there are no state-funded art programs in Arizona. Arizona is tied with Texas for the eighth highest rate of incarceration in the country. In Arizona, 750 out of every 100,000 people are incarcerated. This project is an art course for incarcerated youth. The project includes a packet detailing the course content and assignment details, a class syllabus, a course flyer, and a certificate of completion. The course is intended to be taught at the Adobe Mountain School facility. The course is designed so that it can be implemented in other facilities in the future. The class will be taught by volunteers with a background in studio art, design, or art education. Each student will receive a course packet that they can use to keep track of information and assignments. Instructors will use the course packet to teach the class. The course focuses on drawing with charcoal and oil pastel, which will build a foundation in drawing skills. The course covers a twelve-week semester. The course content packet includes a week-by-week breakdown of the teaching material and project descriptions. The course consists of two main projects and preparatory work. The preparatory work includes vocabulary terms, art concepts, drawing guides, brainstorming activities, and drawing activities. The two main prompts are designed for students to explore the materials and to encourage self-reflection. The class is curated so that students can create art in a low-risk, non-judgemental environment. The course will also focus on establishing problem-solving and critical thinking skills through engaging activities.

ContributorsSheppard, Eve (Author) / Cornelia, Wells (Thesis director) / Jennifer, Nelson (Committee member) / School of Art (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

Soiled: An Environmental Podcast is a six episode series where common environmental topics are discussed and misconceptions surrounding these topics are debunked.

ContributorsKuta, Tiffany T (Co-author) / Jones, Cassity (Co-author) / Turner, Natalie (Co-author) / Boyer, Mackenzie (Thesis director) / Ward, Kristen (Committee member) / Civil, Environmental and Sustainable Eng Program (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

Soiled: An Environmental Podcast is a six episode series where common environmental topics are discussed and misconceptions surrounding these topics are debunked.

ContributorsJones, Cassity Rachelle (Co-author) / Kuta, Tiffany (Co-author) / Turner, Natalie (Co-author) / Boyer, Mackenzie (Thesis director) / Ward, Kristen (Committee member) / School of Life Sciences (Contributor) / School of Human Evolution & Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
148212-Thumbnail Image.png
Description

Developed a business product with a team of CS students.

ContributorsPerri, Cole Thomas (Co-author) / Hernandez, Maximilliano (Co-author) / Schneider, Kaitlin (Co-author) / Call, Andy (Thesis director) / Hunt, Neil (Committee member) / School of Accountancy (Contributor) / Watts College of Public Service & Community Solut (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05