With the emergence of cloud computing, many applications are migrated onto clouds. Video-on-demand (VoD) can be implemented on the cloud platform with geo-distributed cloud servers to serve worldwide users. New videos are distributed to these geo-distributed cloud servers. This distribution should be properly scheduled based on the videos' sizes, videos' popularities and the available network bandwidth, so that the mean completion time is minimized. We formulate this problemas a preemptive scheduling problem, prove that it is NP-hard, and design a heuristic scheduling algorithm to solve it. This algorithm iteratively determines: 1) themost preferred file to be received by the most preferred destination server by pairwise analysis and PageRank, and 2) the most preferred source servers which can transmit this file to the most preferred destination server with appropriate data rates. The simulation results demonstrate that the proposed scheduling algorithm gives much smaller mean completion time than four scheduling algorithms.

This master thesis deals with tracking the moving object in image. The result of the thesis is designed algorithm which is implemented in the programming language C#. This algorithm improves the functionallity of an existing tracking algorithm.

This master thesis deals with tracking the moving object in image. The result of the thesis is designed algorithm which is implemented in the programming language C#. This algorithm improves the functionallity of an existing tracking algorithm.

Goal of this thesis is design and implementation of application for editing multimedia content used for entertaining fans during sport events on stadiums, which will provide easy to use and intuitive graphical user interface. The theoretical part contains description of multimedia data from the perspective of this thesis, namely statical images and video. It provides the overview of multimedia applications, ranging from low end video editors to hi end media control centers. At last the closer look into sport stadiums environment is given in perspective of used digital display devices and multimedia content.

Digital video games are an immensely popular form of entertainment. The meaningful positive experiences that games facilitate are fundamental to the activity; players are known to invest a lot of time playing games in search of those experiences. Digital games research is polarized. Some studies find games to be a healthy hobby with positive effects; games promote well-being through regular experience of positive psychological experiences such as flow and positive emotions. Others have identified rare problematic use in those players who devote excessive amounts of time to gaming, associating them with social dysfunction, addiction, and maladaptive aggression. While it remains unclear if games cause these effects, or merely coincide with play, the negative effects historically receive more attention in both popular media and academia. Some authorities attempt to reduce the harms associated with games to such an extent that their methods have become national policy affecting all players including those who exhibit no negative outcomes. In South Korea and Taiwan, policing authorities employ a behaviour policy that sets strict daily limits on session length, thereby controlling the amount of time people spend playing games each day. In China, the General Administration of Press and Publication employ a design policy requiring that games service-providers fatigue their games’ mechanics after a period to coax them to take a break sooner than they ordinarily would. Both policy types alter player interaction with games in any given session and it is unclear how these policies affect players in general. This research aims to compare sessions affected by the behaviour policy, design policy, and policy-free sessions in terms of session length, measurable subjective user-experience, the player's intention to return to the game, and their reasons for choosing to stop playing in a particular session. For use in a repeated-measures experiment, we modified the action RPG Torchlight II to simulate both policies. Participants had one session at the same time each week for three consecutive weeks. In varied sequences, participants played a control session unaffected by policy, a onehour shutdown session representing behaviour policy, and a fatigue session representing design policy. After each session, we recorded their session's length, their user-experience in terms of flow and affect, their intention to return to the game, and their reason for ending the current session. We found that our shutdown condition successfully decreases session length, when compared to the other conditions. The condition facilitates strong flow, moderate positive-affect, and weak negative-affect. The shutdown event does not appear to degrade positive experiences and makes participants slightly more upset (statistically significant) than they would be after choosing to stop playing. This is because players do not get to make that decision, and because players are unable to complete the goals they have set for themselves. Most players intended to play the game again immediately or sometime later in that same day, much sooner (statistically significant) iii Word Template by Friedman & Morgan 2014 than they would after choosing to stop. This also may be due to satisfaction associated with choosing to stop, or being unable to complete their self-set goals. We found that our fatigue condition increases session length when compared to the other conditions. This result contradicts the intentions associated with design policies: shorter sessions. The fatigue mechanics make the game more difficult, which increases the time required for players to complete the goals they have set for themselves, whether it is to complete a level, quest, or narrative sequence. The condition facilitates high levels of flow, moderate positive-affect and low negativeaffect; the condition does not appear to degrade these positive experiences, nor increase negative experience. Most players intended to take the longest breaks between sessions of at least one day, and although we observed that these were longer than the control condition, the differences is not statistically significant. We found that most participants chose to stop playing when the game stopped providing them with positive experiences, or begins to generate discomfort. A large group of participants chose to stop because another activity took priority. Few participants chose to stop because they were satisfied with their session. Less than one third of players explicitly referenced the fatigue mechanics in their decision to stop. Neither policy is holistically better than the other. Both provide strong positive experiences, and have different effects on session length. Whereas it appears that the fatigue condition fails to reduce session length, it also appears that players intend taking longer breaks between sessions, which may reduce total play-time across all sessions. Similarly, the shutdown condition may increase total play time, or at least bring it closer to normal amounts of play-time while also making players more upset. Our operational definition of user-experience is bi-dimensional, and does not include many experiential constructs commonly associated with digital games. During this research, several reliable and valid, and more representative experience measures became available. Any future work on this topic should make use of one of these. Our experiment tested the effects of player experience associated with a single game, genre, and context. Future research should reduce the variation of player factors by focusing on single personalities, typologies, or risk-factors rather than generalizing to all players. We tested out participants only as they played in the early stages of Torchlight II. It is possible that the game's narrative elements, rather than the gameplay mechanics fatigued by the design policy, motivated continued play. We suggest a longitudinal study of the individual policies to explore their effects over many sessions.

Deep learning, usually built upon artificial neural networks, was proposed in 1943, but poor computational capability restricted its development at that time. With the advancement of computer architecture and chip design, deep learning gains sufficient computational power and has revolutionized many areas in computer vision. As a fundamental research area of computer vision, video enhancement often serves as the first step of many modern vision systems and facilitates numerous downstream vision tasks. This thesis provides a comprehensive study of video enhancement, especially in the sense of video frame interpolation and space-time video super-resolution. For video frame interpolation, two novel methods, named GDConvNet and VFIT, are proposed. In GDConvNet, a novel mechanism named generalized deformable convolution is introduced in order to overcome the inaccuracy flow estimation issue in the flow-based methods and the rigidity issue of kernel shape in the kernel-based methods. This mechanism can effectively learn motion information in a data-driven manner and freely select sampling points in space-time. Our GDConvNet, built upon this mechanism, is shown to achieve state-of-the-art performance. As for VFIT, the concept of local attention is firstly introduced to video interpolation, and a novel space-time separation window-based self-attention scheme is further devised, which not only saves costs but acts as a regularization term to improve the performance. Based on the new scheme, VFIT is presented as the first Transformer-based video frame interpolation framework. In addition, a multi-scale frame synthesis scheme is developed to fully realize the potential of Transformers. Extensive experiments on a variety of benchmark datasets demonstrate the superiority and liability of VFIT. For space-time video super-resolution, a novel unconstrained space-time video super-resolution network is proposed to solve the common issues of the existing methods that either fail to explore the intrinsic relationship between temporal and spatial information or lack flexibility in the choice of final temporal/spatial resolution. To this end, several new ideas are introduced, such as integration of multi-level representations and generalized pixshuffle. Various experiments validate the proposed method in terms of its complete freedom in choosing output resolution, as well as superior performance over the state-of-the-art methods. / Thesis / Doctor of Philosophy (PhD)

The prevalence of regular video game use among populations of all ages, genders, geographic locations, and life experiences has grown exponentially in recent years (Entertainment Software Association, 2021). Gaming provides many players with an opportunity to engage in an immersive, engaging, and enjoyable activity that has the power to positively impact many facets of quality of life and well-being (Jones, 2021; Britnell & Goldberg, 2002). Despite monumental strides made in the gaming industry to ensure gaming controllers and software settings are accessible for players with disabilities, many players still face barriers to video game access following the onset of injury, illness, or an existing condition. The relationship between the occupational therapy profession and the prevalence of video game technologies is multifaceted. First, occupational therapists are tasked with adapting tasks or environments to facilitate access and independence in activities that a particular client finds meaningful. Additionally, occupational therapists ground the nature of their work in creating evaluation methods and intervention approaches that leverage a client’s established meaningful occupations in producing functional outcomes through therapeutic exercise and activity (AJOT, 2020). Given the large and growing population of clients who consider gaming a meaningful occupation, this project asserts that occupational therapists have the following responsibilities related to adequately serving the needs of their current and future clients: 1. Acquiring knowledge needed to successfully adapt gaming hardware and gameplay tasks through assistive technologies to facilitate access and independence in gameplay for leisure or social participation purposes 2. Acquiring knowledge needed to successfully embed game-based activities within occupational therapy interventions to ensure treatment sessions remain occupation based, meaningful, and engaging to applicable client populations. Despite these factors, gaming knowledge and adoption among occupational therapists remains relatively low due to a variety of factors discussed in further detail throughout this paper (Hills et al., 2016; Jones, 2021; Levac et al., 2017; Thomson et al., 2016). This project assessed the current body of evidence-based literature related to the therapeutic implications of gaming, the nature of current barriers contributing to low technology adoption rates, and established approaches deemed effective in mitigating these barriers in detail. This large body of data and evidence was used to create the Gaming and Occupational therapy Adoption Training Program (G.O.A.T.). This program leverages a multidimensional approach in providing a comprehensive intervention program for occupational therapists that ultimately seeks to increase the adoption of gaming technologies within the occupational therapy profession.

Yes / In this correspondence, we propose to add a lossless compression functionality into existing MPEGs by developing a new context tree to drive arithmetic coding for lossless video compression. In comparison with the existing work on context tree design, the proposed algorithm features in 1) prefix sequence matching to locate the statistics model at the internal node nearest to the stopping point, where successful match of context sequence is broken; 2) traversing the context tree along a fixed order of context structure with a maximum number of four motion compensated errors; and 3) context thresholding to quantize the higher end of error values into a single statistics cluster. As a result,the proposed algorithm is able to achieve competitive processing speed, low computational complexity and high compression performances, which bridges the gap between universal statistics modeling and practical compression techniques. Extensive experiments show that the proposed algorithm outperforms JPEG-LS by up to 24% and CALIC by up to 22%, yet the processing time ranges from less than 2 seconds per frame to 6 seconds per frame on a typical PC computing platform.

Analysis and extraction of features in video streaming refer to the process of identifying and extracting specific characteristics or patterns from a video stream that can be used for various purposes, such as object detection, recognition, and tracking, as well as video compression, indexing, and retrieval. The extracted features can be used for different purposes, depending on the specific needs and requirements of the application. End-to-end streaming latency refers to the delay between the time a video frame is captured and the time it is displayed on the user’s device. Analysis and extraction of features in video streaming can be used to measure end-to-end streaming latency by extracting specific characteristics or patterns from the video stream that indicate the start and end points of the video stream and the time stamps of each frame. In this work we propose a simple but effective way to measure the end-to-end streaming latency by using object detection and image-to-text conversion, both tasks based on the extraction of features of the underlying content. Shot boundary detection is the process of identifying the boundaries between shots in a video stream. Shot boundary detection is an important task in video processing, as it is used for various applications, such as video editing, indexing, retrieval, and summarization. Analysis and extraction of features in video streaming can be used for shot boundary detection by extracting specific characteristics or patterns from the video stream that indicate changes in the visual and audio content. Once these features are extracted, various techniques can be used to detect shot boundaries, such as thresholding, clustering, and machine learning algorithms. In this work, we analyze state-of-the-art deep learning algorithms for shot boundary detection tasks and datasets and propose several new models that improve the efficiency of the last state-of-the-art models meanwhile keeping or even improving the resulting metrics. Video temporal segmentation in scenes is the process of dividing a video stream into coherent temporal segments grouping all shots that are visually and semantically related to each other. In this work, we take advantage of the improvements done in the task of shot boundary detection to propose a foundational model in the task of segmenting the video into scenes, from a previous segmentation in shots. We propose a model based on visual similarity and we also contribute with a specific dataset for the task.

Royal Blood is a piece of software that confronts the author's childhood traumas and attempts to empower the audience through interactive emergent theater. On the surface Royal Blood is a multiplayer action video-game, however the roots of this game lay in the Psychomagic therapeutic practices that were first established by the cult film director Alejandro Jodorowsky.