Thesis (Ph. D.), Oregon Graduate Institute of Science & Technology, 1996.

Thesis (Ph. D.)-- University of Washington, 2005. / Vita. Includes bibliographical references (p. 115-118).

Thesis (M.S.)--University of Missouri-Columbia, 2004. / Typescript. Includes bibliographical references (leaves 59-61). Also available on the Internet.

Thesis (M.S.)--Tennessee Technological University, 2009. / Title from title page screen (viewed on June 29, 2010). Bibliography: leaves 68-70.

No description available.

Orientador: Yuzo Iano / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-26T03:55:11Z (GMT). No. of bitstreams: 1 Tanji_Mauricio_M.pdf: 2807982 bytes, checksum: 41aeece240ea9b64df695dd36d87c2ea (MD5) Previous issue date: 2014 / Resumo: Este trabalho propõe um método de avaliação objetiva de qualidade de vídeo digital no padrão H.264. Especificamente, o método combina algumas das técnicas clássicas de avaliação de qualidade de vídeo a partir de uma rede de treinamento neural. São apresentados métodos que podem ser aplicados em sistemas de avaliação Full-Reference e Reduced-Reference. Os algoritmos propostos são aplicados a um conjunto de cenas de vídeo H.264 e cada parâmetro de qualidade é calculado. A estimativa da qualidade é realizada a partir de uma função interpoladora utilizando redes neurais, treinadas com uma base de dados subjetiva das sequências trabalhadas. Além disso, é proposto um sistema de avaliação que permite a avaliação de codificadores de vídeo em campo, a partir de um set-top box. Os resultados alcançados mostram valores elevados de correlação, os quais não poderiam ser obtidos pelos métodos trabalhando de forma isolada / Abstract: This dissertation proposes an objective method of digital video quality assessment in H.264 standard. Specifically, the method combines some of the classical techniques of evaluation of video quality with a neural network training. Methods that can be applied in evaluation systems with "Full-Reference" and "Reduced-Reference" are listed. The algorithms are applied to a collection of scenes and each H.264 video quality parameter is calculated. The estimation of quality is processed from an interpolating function using neural networks trained with a data base of respective subjective sequences. Furthermore, we propose an evaluation system which enables evaluation of video encoders in the field, from a set-top box. The results show high correlation values, which could not be obtained by the methods working in isolation / Mestrado / Telecomunicações e Telemática / Mestre em Engenharia Elétrica

The purpose of this project was the specification, design and implementation of a prototype 2-D MPEG-4 authoring tool. A literature study was conducted of the MPEG-4 standard and multimedia authoring tools to determine the specification and design of a prototype 2- D MPEG-4 authoring tool. The specification and design was used as a basis for the implementation of a prototype 2-D MPEG-4 authoring tool that complies with the Complete 2-D Scene Graph Profile. The need for research into MPEG-4 authoring tools arose from the reported lack of knowledge of the MPEG-4 standard and the limited implementations of MPEG-4 authoring tools available to content authors. In order for MPEG-4 to reach its full potential, it will require authoring tools and content players that satisfy the needs of its users. The theoretical component of this dissertation included a literature study of the MPEG-4 standard and an investigation of relevant multimedia authoring systems. MPEG-4 was introduced as a standard that allows for the creation and streaming of interactive multimedia content at variable bit rates over high and low bandwidth connections. The requirements for the prototype 2-D MPEG-4 authoring system were documented and a prototype system satisfying the requirements was designed, implemented and evaluated. The evaluation of the prototype system showed that the system successfully satisfied all its requirements and that it provides the user with an easy to use and intuitive authoring tool. MPEG-4 has the potential to satisfy the increasing demand for innovative multimedia content on low bandwidth networks, including the Internet and mobile networks, as well as the need expressed by users to interact with multimedia content. This dissertation makes an important contribution to the understanding of the MPEG-4 standard, its functionality and the design of a 2-D MPEG-4 Authoring tool. Keywords: MPEG-4; MPEG-4 authoring; Binary Format for Scenes.

Bakgrund: Användningen av digitala videobesök har ökat inom fysioterapin under de senaste åren, särskilt i samband med covid-pandemin. Den nuvarande kunskapen om fysioterapeuters upplevelser och erfarenheter av användandet av digitala videobesök är begränsad.  Syfte: Att undersöka fysioterapeuters upplevelser och erfarenheter av att möta patienter via digitala videobesök. Metod: Studien har en kvalitativ design. Data insamlades genom semistrukturerade intervjuer med fem fysioterapeuter inom primärvården. Datan bearbetades genom kvalitativ innehållsanalys.  Resultat: Insamlad data resulterade i följande huvudkategorier: Begränsningar för användandet av digitala videobesök, fördelar med digitala videobesök samt utveckling av digitala videobesök. Konklusion: Sammanfattningsvis ansåg fysioterapeuterna generellt att digitala videobesök är ett bra verktyg att tillgå. Framförallt genom att det ökar tillgängligheten till fysioterapeuten och att det möjliggör ett mer flexibelt arbete. De beskrev även begränsningar i arbetet med videobesök. Bland annat organisatoriska hinder och frånvaron av fysisk kontakt med patienten. Dessutom framfördes olika tankar om utveckling av videobesök. Exempelvis tekniska förbättringsmöjligheter och möjlighet till mer utbildning på området. / Background: The use of digital video meetings in physiotherapy has increased in recent years, particularly  in conjunction with the covid-pandemic. The current evidence for physiotherapists' experiences and perceptions of using digital video meetings is limited.  Purpose: To investigate physiotherapists experiences and perceptions of meeting patients through digital video meetings.  Method: The study has a qualitative design. Data were collected through semi structured interviews of five physiotherapists in primary care. The data was processed using qualitative content analysis.  Results: Collected data resulted in the following main categories: restrictions in the use of digital video meetings, benefits of digital video meetings and development of digital video meetings.  Conclusion: In summary, physiotherapists generally considered digital video meetings to be a good tool available. Mainly by increasing the accessibility to the physiotherapist and by contributing to  a more flexible job. They also described limitations in their work with video meetings. For instance, organizational obstacles and the absence of physical contact with the patient. Furthermore, different ways of developing the video meetings were presented. For example, technical opportunities for improvement and opportunities for more education in the field.

No / This work presents a novel broadband monopole antenna for digital video broadcastingterrestrial (DVB-T) application. The proposed antenna consists of a grating patch and a concave rectangular ground plane with defected ground plane, and the Multiple Split-Ring Resonator (MSRR). The added part in the ground plane and the meta-material are used to enable the antenna height reduction for fixed ranges of operating frequency. The antenna can operate from 468 MHz to 894 MHz frequency range corresponding to 62.5% of impedance bandwidth for |S11|<-7.5 dB. Details of the proposed antenna designs and experimental results of the constructed prototypes are presented and discussed.

There is a great need to automatically segment, categorize, and annotate video data, and to develop efficient tools for browsing and searching. We believe that the categorization of videos can be achieved by exploring the concepts and meanings of the videos. This task requires bridging the gap between low-level content and high-level concepts (or semantics). Once a relationship is established between the low-level computable features of the video and its semantics, the user would be able to navigate through videos through the use of concepts and ideas (for example, a user could extract only those scenes in an action film that actually contain fights) rat her than sequentially browsing the whole video. However, this relationship must follow the norms of human perception and abide by the rules that are most often followed by the creators (directors) of these videos. These rules are called film grammar in video production literature. Like any natural language, this grammar has several dialects, but it has been acknowledged to be universal. Therefore, the knowledge of film grammar can be exploited effectively for the understanding of films. To interpret an idea using the grammar, we need to first understand the symbols, as in natural languages, and second, understand the rules of combination of these symbols to represent concepts. In order to develop algorithms that exploit this film grammar, it is necessary to relate the symbols of the grammar to computable video features. In this dissertation, we have identified a set of computable features of videos and have developed methods to estimate them. A computable feature of audio-visual data is defined as any statistic of available data that can be automatically extracted using image/signal processing and computer vision techniques. These features are global in nature and are extracted using whole images, therefore, they do not require any object detection, tracking and classification. These features include video shots, shot length, shot motion content, color distribution, key-lighting, and audio energy. We use these features and exploit the knowledge of ubiquitous film grammar to solve three related problems: segmentation and categorization of talk and game shows; classification of movie genres based on the previews; and segmentation and representation of full-length Hollywood movies and sitcoms. We have developed a method for organizing videos of talk and game shows by automatically separating the program segments from the commercials and then classifying each shot as the host's or guest's shot. In our approach, we rely primarily on information contained in shot transitions and utilize the inherent difference in the scene structure (grammar) of commercials and talk shows. A data structure called a shot connectivity graph is constructed, which links shots over time using temporal proximity and color similarity constraints. Analysis of the shot connectivity graph helps us to separate commercials from program segments. This is done by first detecting stories, and then assigning a weight to each story based on its likelihood of being a commercial or a program segment. We further analyze stories to distinguish shots of the hosts from those of the guests. We have performed extensive experiments on eight full-length talk shows (e.g. Larry King Live, Meet the Press, News Night) and game shows (Who Wants To Be A Millionaire), and have obtained excellent classification with 96% recall and 99% precision. http://www.cs.ucf.edu/~vision/projects/LarryKing/LarryKing.html Secondly, we have developed a novel method for genre classification of films using film previews. In our approach, we classify previews into four broad categories: comedies, action, dramas or horror films. Computable video features are combined in a framework with cinematic principles to provide a mapping to these four high-level semantic classes. We have developed two methods for genre classification; (a) a hierarchical method and (b) an unsupervised classification met hod. In the hierarchical method, we first classify movies into action and non-action categories based on the average shot length and motion content in the previews. Next, non-action movies are sub-classified into comedy, horror or drama categories by examining their lighting key. Finally, action movies are ranked on the basis of number of explosions/gunfire events. In the unsupervised method for classifying movies, a mean shift classifier is used to discover the structure of the mapping between the computable features and each film genre. We have conducted extensive experiments on over a hundred film previews and demonstrated that low-level features can be efficiently utilized for movie classification. We achieved about 87% successful classification. http://www.cs.ucf.edu/-vision/projects/movieClassification/movieClmsification.html Finally, we have addressed the problem of detecting scene boundaries in full-length feature movies. We have developed two novel approaches to automatically find scenes in the videos. Our first approach is a two-pass algorithm. In the first pass, shots are clustered by computing backward shot coherence; a shot color similarity measure that detects potential scene boundaries (PSBs) in the videos. In the second pass we compute scene dynamics for each scene as a function of shot length and the motion content in the potential scenes. In this pass, a scene-merging criterion is used to remove weak PSBs in order to reduce over-segmentation. In our second approach, we cluster shots into scenes by transforming this task into a graph-partitioning problem. This is achieved by constructing a weighted undirected graph called a shot similarity graph (SSG), where each node represents a shot and the edges between the shots are weighted by their similarities (color and motion). The SSG is then split into sub-graphs by applying the normalized cut technique for graph partitioning. The partitions obtained represent individual scenes in the video. We further extend the framework to automatically detect the best representative key frames of identified scenes. With this approach, we are able to obtain a compact representation of huge videos in a small number of key frames. We have performed experiments on five Hollywood films (Terminator II, Top Gun, Gone In 60 Seconds, Golden Eye, and A Beautiful Mind) and one TV sitcom (Seinfeld) that demonstrate the effectiveness of our approach. We achieved about 80% recall and 63% precision in our experiments. http://www.cs.ucf.edu/~vision/projects/sceneSeg/sceneSeg.html