Stars in their eyes: What eye-tracking reveal about multimedia perceptual quality

Perceptual multimedia quality is of paramount importance to the continued take-up and proliferation of multimedia applications: users will not use and pay for applications if they are perceived to be of low quality. Whilst traditionally distributed multimedia quality has been characterised by Quality of Service (QoS) parameters, these neglect the user perspective of the issue of quality. In order to redress this shortcoming, we characterise the user multimedia perspective using the Quality of Perception (QoP) metric, which encompasses not only a user’s satisfaction with the quality of a multimedia presentation, but also his/her ability to analyse, synthesise and assimilate informational content of multimedia. In recognition of the fact that monitoring eye movements offers insights into visual perception, as well as the associated attention mechanisms and cognitive processes, this paper reports on the results of a study investigating the impact of differing multimedia presentation frame rates on user QoP and eye path data. Our results show that provision of higher frame rates, usually assumed to provide better multimedia presentation quality, do not significantly impact upon the median coordinate value of eye path data. Moreover, higher frame rates do not significantly increase level of participant information assimilation, although they do significantly improve overall user enjoyment and quality perception of the multimedia content being shown

Applying psychological science to the CCTV review process: a review of cognitive and ergonomic literature

As CCTV cameras are used more and more often to increase security in communities, police are spending a larger proportion of their resources, including time, in processing CCTV images when investigating crimes that have occurred (Levesley & Martin, 2005; Nichols, 2001). As with all tasks, there are ways to approach this task that will facilitate performance and other approaches that will degrade performance, either by increasing errors or by unnecessarily prolonging the process. A clearer understanding of psychological factors influencing the effectiveness of footage review will facilitate future training in best practice with respect to the review of CCTV footage. The goal of this report is to provide such understanding by reviewing research on footage review, research on related tasks that require similar skills, and experimental laboratory research about the cognitive skills underpinning the task. The report is organised to address five challenges to effectiveness of CCTV review: the effects of the degraded nature of CCTV footage, distractions and interrupts, the length of the task, inappropriate mindset, and variability in people’s abilities and experience. Recommendations for optimising CCTV footage review include (1) doing a cognitive task analysis to increase understanding of the ways in which performance might be limited, (2) exploiting technology advances to maximise the perceptual quality of the footage (3) training people to improve the flexibility of their mindset as they perceive and interpret the images seen, (4) monitoring performance either on an ongoing basis, by using psychophysiological measures of alertness, or periodically, by testing screeners’ ability to find evidence in footage developed for such testing, and (5) evaluating the relevance of possible selection tests to screen effective from ineffective screener

Distributed multimedia quality: The user perspective

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Distributed multimedia supports a symbiotic infotainment duality, i.e. the ability to transfer information to the user, yet also provide the user with a level of satisfaction. As multimedia is ultimately produced for the education and / or enjoyment of viewers, the user’s-perspective concerning the presentation quality is surely of equal importance as objective Quality of Service (QoS) technical parameters, to defining distributed multimedia quality. In order to extensively measure the user-perspective of multimedia video quality, we introduce an extended model of distributed multimedia quality that segregates quality into three discrete levels: the network-level, the media-level and content-level, using two distinct quality perspectives: the user-perspective and the technical-perspective. Since experimental questionnaires do not provide continuous monitoring of user attention, eye tracking was used in our study in order to provide a better understanding of the role that the human element plays in the reception, analysis and synthesis of multimedia data. Results showed that video content adaptation, results in disparity in user video eye-paths when: i) no single / obvious point of focus exists; or ii) when the point of attention changes dramatically. Accordingly, appropriate technical- and user-perspective parameter adaptation is implemented, for all quality abstractions of our model, i.e. network-level (via simulated delay and jitter), media-level (via a technical- and user-perspective manipulated region-of-interest attentive display) and content-level (via display-type and video clip-type). Our work has shown that user perception of distributed multimedia quality cannot be achieved by means of purely technical-perspective QoS parameter adaptation

A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community

In recent years, deep learning (DL), a re-branding of neural networks (NNs), has risen to the top in numerous areas, namely computer vision (CV), speech recognition, natural language processing, etc. Whereas remote sensing (RS) possesses a number of unique challenges, primarily related to sensors and applications, inevitably RS draws from many of the same theories as CV; e.g., statistics, fusion, and machine learning, to name a few. This means that the RS community should be aware of, if not at the leading edge of, of advancements like DL. Herein, we provide the most comprehensive survey of state-of-the-art RS DL research. We also review recent new developments in the DL field that can be used in DL for RS. Namely, we focus on theories, tools and challenges for the RS community. Specifically, we focus on unsolved challenges and opportunities as it relates to (i) inadequate data sets, (ii) human-understandable solutions for modelling physical phenomena, (iii) Big Data, (iv) non-traditional heterogeneous data sources, (v) DL architectures and learning algorithms for spectral, spatial and temporal data, (vi) transfer learning, (vii) an improved theoretical understanding of DL systems, (viii) high barriers to entry, and (ix) training and optimizing the DL.Comment: 64 pages, 411 references. To appear in Journal of Applied Remote Sensin

Establishing National Ocean Service Priorities for Estuarine, Coastal, and Ocean Modeling: Capabilities, Gaps, and Preliminary Prioritization Factors

This report was developed to help establish National Ocean Service priorities and chart new directions for research and development of models for estuarine, coastal and ocean ecosystems based on user-driven requirements and supportive of sound coastal management, stewardship, and an ecosystem approach to management. (PDF contains 63 pages

Toward A Theory of Media Reconciliation: An Exploratory Study of Closed Captioning

This project is an interdisciplinary empirical study that explores the emotional experiences resulting from the use of the assistive technology closed captioning. More specifically, this study focuses on documenting the user experiences of both the D/deaf and Hearing multimedia user in an effort to better identify and understand those variables and processes that are involved with facilitating and supporting connotative and emotional meaning making. There is an ever present gap that defines closed captioning studies thus far, and this gap is defined by the emphasis on understanding and measuring denotative meaning making behavior while largely ignoring connotative meaning making behavior that is necessarily an equal participant in a user\u27s viewing experience. This study explores connotative and emotional meaning making behaviors so as to better understand the behavior exhibited by users engaged with captioned multimedia. To that end, a mixed methods design was developed that utilizes qualitative methods from the field of User Experience (UX) to explore connotative equivalence between D/deaf and Hearing users and an augmented version of S. R. Gulliver and G. Ghinea\u27s (2003) quantitative measure Information Assimilation (IA) from the field of Human Computer Interaction (HCI) to measure the denotative equivalence between the two user types. To measure denotative equivalence a quiz containing open-ended questions to measure IA was used. To measure connotative equivalence the following measures were used: 1) Likert scales to measure users\u27 confidence in answers to open-ended questions. 2) Likert scale to measure a users\u27 interest in the stimulus. 3) Open - ended questions to identify scenes that elicited the strongest emotional responses from users. 4) Four- level response questions with accompanying Likert scales to determine strength of emotional reaction to three select excerpts from the stimulus. 5) An interview consisting of three open- ended questions and one fixed - choice question. This study found that there were no major differences in the denotative equivalence between the D/deaf and Hearing groups; however, there were important differences in the emotional reactions to the stimulus that indicate there was not connotative equivalence between the groups in response to the emotional content. More importantly, this study found that the strategies used to understand the information users were presented with in order to create both denotative and connotative meaning differed between groups and individuals within groups. To explain such behaviors observed, this work offers a theory of Media Reconciliation based on Wolfgang Iser\u27s (1980) phenomenological theory about the \u27virtual text\u27

Analysis of Gravity Recovery and Climate Experiment (GRACE) Satellite-Derived Data as a Groundwater and Drought Monitoring Tool

This research compares Gravity Recovery and Climate Experiment (GRACE) groundwater storage (GWS) and root zone soil moisture (RZSM) percentiles to measured data, other drought indicators (DIs) and indices, and stakeholder observations for the purpose of assessing the feasibility and usefulness of these products to detect drought conditions. GRACE percentiles were directly compared to historic groundwater percentiles at 89 Nebraska well locations. Spatial time-series correlations over CONUS were performed between GRACE GWS and RZSM and the U.S. Drought Monitor (USDM), Standardized Precipitation Index (SPI), and soil moisture parameters from several North American Land Data Assimilation System (NLDAS) models. A survey of stakeholder observations during a 2016 flash drought event centered on Montana, Wyoming, South Dakota, and Nebraska was also compared to GRACE percentile data to analyze drought onset timing, geographic coverage, and severity. Overall the results show GRACE GWS has similar spatial and temporal agreement over the well period of record, and generally has the expected negative correlation relationship with observed groundwater, but it does not accurately reflect historic percentiles in Nebraska. GRACE GWS and RZSM have moderate correlation with USDM, and high correlation with SPI, and NLDAS models over the entire U.S. with notable regional and seasonal patterns. SPI accumulation period also plays an important role in correlation strength for both RZSM and GWS with the best agreement seen at 3-month and 12-month accumulation periods, respectively. GRACE RZSM time-series data closely matches stakeholder observations of decreasing soil moisture availability, while observations of decreasing water levels were not as closely matched by GWS. When analyzed as an average over all responding zip codes, RZSM showed an early warning trend up to six weeks prior to observed reports. These results indicate GRACE percentiles are promising drought indicators that can be used as a monitoring and early warning system by decision makers. Advisor: Tsegaye Tadess