851 resultados para Streaming video--Taxation


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In this paper, the problem of moving object detection in aerial video is addressed. While motion cues have been extensively exploited in the literature, how to use spatial information is still an open problem. To deal with this issue, we propose a novel hierarchical moving target detection method based on spatiotemporal saliency. Temporal saliency is used to get a coarse segmentation, and spatial saliency is extracted to obtain the object’s appearance details in candidate motion regions. Finally, by combining temporal and spatial saliency information, we can get refined detection results. Additionally, in order to give a full description of the object distribution, spatial saliency is detected in both pixel and region levels based on local contrast. Experiments conducted on the VIVID dataset show that the proposed method is efficient and accurate.

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This paper discusses the idea and demonstrates an early prototype of a novel method of interacting with security surveillance footage using natural user interfaces in place of traditional mouse and keyboard interaction. Current surveillance monitoring stations and systems provide the user with a vast array of video feeds from multiple locations on a video wall, relying on the user’s ability to distinguish locations of the live feeds from experience or list based key-value pair of location and camera IDs. During an incident, this current method of interaction may cause the user to spend increased amounts time obtaining situational and location awareness, which is counter-productive. The system proposed in this paper demonstrates how a multi-touch screen and natural interaction can enable the surveillance monitoring station users to quickly identify the location of a security camera and efficiently respond to an incident.

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Streaming services like Spotify and Pandora pay many millions of dollars each year for the rights to the music they play. But how much of this ends up back with artists and songwriters? The answer: not an awful lot.

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Importance Active video games may offer an effective strategy to increase physical activity in overweight and obese children. However, the specific effects of active gaming when delivered within the context of a pediatric weight management program are unknown. Objective To evaluate the effects of active video gaming on physical activity and weight loss in children participating in an evidence-based weight management program delivered in the community. Design, Setting, and Participants Group-randomized clinical trial conducted during a 16-week period in YMCAs and schools located in Massachusetts, Rhode Island, and Texas. Seventy-five overweight or obese children (41 girls [55%], 34 whites [45%], 20 Hispanics [27%], and 17 blacks [23%]) enrolled in a community-based pediatric weight management program. Mean (SD) age of the participants was 10.0 (1.7) years; body mass index (BMI) z score, 2.15 (0.40); and percentage overweight from the median BMI for age and sex, 64.3% (19.9%). Interventions All participants received a comprehensive family-based pediatric weight management program (JOIN for ME). Participants in the program and active gaming group received hardware consisting of a game console and motion capture device and 1 active game at their second treatment session and a second game in week 9 of the program. Participants in the program-only group were given the hardware and 2 games at the completion of the 16-week program. Main Outcomes and Measures Objectively measured daily moderate-to-vigorous and vigorous physical activity, percentage overweight, and BMI z score. Results Participants in the program and active gaming group exhibited significant increases in moderate-to-vigorous (mean [SD], 7.4 [2.7] min/d) and vigorous (2.8 [0.9] min/d) physical activity at week 16 (P < .05). In the program-only group, a decline or no change was observed in the moderate-to-vigorous (mean [SD] net difference, 8.0 [3.8] min/d; P = .04) and vigorous (3.1 [1.3] min/d; P = .02) physical activity. Participants in both groups exhibited significant reductions in percentage overweight and BMI z scores at week 16. However, the program and active gaming group exhibited significantly greater reductions in percentage overweight (mean [SD], −10.9% [1.6%] vs −5.5% [1.5%]; P = .02) and BMI z score (−0.25 [0.03] vs −0.11 [0.03]; P < .001). Conclusions and Relevance Incorporating active video gaming into an evidence-based pediatric weight management program has positive effects on physical activity and relative weight.

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The Australian Taxation Office (AT)) attempted to challenge both the private equity fund reliance on double tax agreements and the assertion that profits were capital in nature in its dispute with private equity group TPG. Failure to resolve the dispute resulted in the ATO issuing two taxation determinations: TD 2010/20 which states that the general anti-avoidance provisions can apply to arrangements designed to alter the intended effect of Australia's international tax agreements net; and TD 2010/21 which states that the profits on the sale of shares in a company group acquired in a leveraged buyout is assessable income. The purpose of this article is to determine the effectiveness of the administrative rulings regime as a regulatory strategy. This article, by using the TPG-Myer scenario and subsequent tax determinations as a case study, collects qualitative data which is then analysed (and triangulated) using tonal and thematic analysis. Contemporaneous commentary of private equity stakeholders, tax professionals, and media observations are analysed and evaluated within a framework of responsive regulation and utilising the current ATO compliance model. Contrary to the stated purpose of the ATO rulings regime to alleviate complexities in Australian taxation law and provide certainty to taxpayers, and despite the de facto law status afforded these rulings, this study found that the majority of private equity stakeholders and their advisors perceived that greater uncertainty was created by the two determinations. Thus, this study found that in the context of private equity fund investors, a responsive regulation measure in the form of taxation determinations was not effective.

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Multiplayer Dynamic Difficulty Adjustment (mDDA) is a method of reducing the difference in player performance and subsequent challenge in competitive multiplayer video games. As a balance of between player skill and challenge experienced is necessary for optimal player experience, this experimental study investigates the effects of mDDA and awareness of its presence on player performance and experience using subjective and biometric measures. Early analysis indicates that mDDA normalizes performance and challenge as expected, but awareness of its presence can reduce its effectiveness.

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The location of previously unseen and unregistered individuals in complex camera networks from semantic descriptions is a time consuming and often inaccurate process carried out by human operators, or security staff on the ground. To promote the development and evaluation of automated semantic description based localisation systems, we present a new, publicly available, unconstrained 110 sequence database, collected from 6 stationary cameras. Each sequence contains detailed semantic information for a single search subject who appears in the clip (gender, age, height, build, hair and skin colour, clothing type, texture and colour), and between 21 and 290 frames for each clip are annotated with the target subject location (over 11,000 frames are annotated in total). A novel approach for localising a person given a semantic query is also proposed and demonstrated on this database. The proposed approach incorporates clothing colour and type (for clothing worn below the waist), as well as height and build to detect people. A method to assess the quality of candidate regions, as well as a symmetry driven approach to aid in modelling clothing on the lower half of the body, is proposed within this approach. An evaluation on the proposed dataset shows that a relative improvement in localisation accuracy of up to 21 is achieved over the baseline technique.

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Due to extension of using CCTVs and the other video security systems in all areas, these sorts of devices have been introduced as the most important digital evidences to search and seizure crimes. Video forensics tools are developed as a part of digital forensics tools to analyze digital evidences and clear vague points of them for presenting in the courts Existing video forensics tools have been facilitated the investigation process by providing different features based on various video editing techniques. In this paper, some of the most popular video forensics tools are discussed and the strengths and shortages of them are compared and consequently, an alternative framework which includes the strengths of existing popular tools is introduced.

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We propose a method of representing audience behavior through facial and body motions from a single video stream, and use these features to predict the rating for feature-length movies. This is a very challenging problem as: i) the movie viewing environment is dark and contains views of people at different scales and viewpoints; ii) the duration of feature-length movies is long (80-120 mins) so tracking people uninterrupted for this length of time is still an unsolved problem, and; iii) expressions and motions of audience members are subtle, short and sparse making labeling of activities unreliable. To circumvent these issues, we use an infrared illuminated test-bed to obtain a visually uniform input. We then utilize motion-history features which capture the subtle movements of a person within a pre-defined volume, and then form a group representation of the audience by a histogram of pair-wise correlations over a small-window of time. Using this group representation, we learn our movie rating classifier from crowd-sourced ratings collected by rottentomatoes.com and show our prediction capability on audiences from 30 movies across 250 subjects (> 50 hrs).

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This study explores the idea of video games where the players are not just allowed to express themselves creatively, but are challenged to do so and are judged based on the quality of their creative expression. The outcome of the research is a series of six games which comment on this idea. The study also raises further questions regarding how current video games are constructed and designed in comparison with non-computer games, and invites a further evolution of the craft of video game design in a direction that focuses more on interpreting and reacting to what the player is doing.

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A single channel video projection with image, text and sound components. It was projected so as entirely fill a 3 x 3.5 wall in a 6 x 3.5 metre gallery space. The work deals with the role of humour and the fictocritical in exploring the relationship between politics and art.

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Effective Quality of Experience (QoE) management for mobile video delivery – to optimize overall user experience while adapting to heterogeneous use contexts – is still a big challenge to date. This paper proposes a mobile video delivery system to emphasize the use of acceptability as the main indicator of QoE to manage the end-to-end factors in delivering mobile video services. The first contribution is a novel framework for user-centric mobile video system that is based on acceptability-based QoE (A-QoE) prediction models, which were derived from comprehensive subjective studies. The second contribution is results from a field study that evaluates the user experience of the proposed system during realistic usage circumstances, addressing the impacts of perceived video quality, loading speed, interest in content, viewing locations, network bandwidth, display devices, and different video coding approaches, including region-of-interest (ROI) enhancement and center zooming

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The solutions proposed in this thesis contribute to improve gait recognition performance in practical scenarios that further enable the adoption of gait recognition into real world security and forensic applications that require identifying humans at a distance. Pioneering work has been conducted on frontal gait recognition using depth images to allow gait to be integrated with biometric walkthrough portals. The effects of gait challenging conditions including clothing, carrying goods, and viewpoint have been explored. Enhanced approaches are proposed on segmentation, feature extraction, feature optimisation and classification elements, and state-of-the-art recognition performance has been achieved. A frontal depth gait database has been developed and made available to the research community for further investigation. Solutions are explored in 2D and 3D domains using multiple images sources, and both domain-specific and independent modality gait features are proposed.

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This thesis investigates face recognition in video under the presence of large pose variations. It proposes a solution that performs simultaneous detection of facial landmarks and head poses across large pose variations, employs discriminative modelling of feature distributions of faces with varying poses, and applies fusion of multiple classifiers to pose-mismatch recognition. Experiments on several benchmark datasets have demonstrated that improved performance is achieved using the proposed solution.

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This volume examines how disruptive innovations are reshaping industry boundaries and challenging conventional business models and practices in the industries for film, video and photography. The thirteen chapters provide a rich and diverse account of these processes from a wide range of country contexts. The book fills the gap between the study of disruption by innovation scholars in business schools and the recognition of disruption by academics and practitioners from non-business school disciplines and contexts, including the broader social sciences.