Socialising around media. Improving the second screen experience through semantic analysis, context awareness and dynamic communities

SAM is a social media platform that enhances the experience of watching video content in a conventional living room setting, with a service that lets the viewer use a second screen (such as a smart phone) to interact with content, context and communities related to the main video content. This article describes three key functionalities used in the SAM platform in order to create an advanced interactive and social second screen experience for users: semantic analysis, context awareness and dynamic communities. Both dataset-based and end user evaluations of system functionalities are reported in order to determine the effectiveness and efficiency of the components directly involved and the platform as a whole

2022 Undergraduate Research Symposium: Full Program

Full program with schedule and abstracts for the 2020 Undergraduate Research Symposium

A COMPUTATION METHOD/FRAMEWORK FOR HIGH LEVEL VIDEO CONTENT ANALYSIS AND SEGMENTATION USING AFFECTIVE LEVEL INFORMATION

VIDEO segmentation facilitates e±cient video indexing and navigation in large digital video archives. It is an important process in a content-based video indexing and retrieval (CBVIR) system. Many automated solutions performed seg- mentation by utilizing information about the \facts" of the video. These \facts" come in the form of labels that describe the objects which are captured by the cam- era. This type of solutions was able to achieve good and consistent results for some video genres such as news programs and informational presentations. The content format of this type of videos is generally quite standard, and automated solutions were designed to follow these format rules. For example in [1], the presence of news anchor persons was used as a cue to determine the start and end of a meaningful news segment. The same cannot be said for video genres such as movies and feature films. This is because makers of this type of videos utilized different filming techniques to design their videos in order to elicit certain affective response from their targeted audience. Humans usually perform manual video segmentation by trying to relate changes in time and locale to discontinuities in meaning [2]. As a result, viewers usually have doubts about the boundary locations of a meaningful video segment due to their different affective responses. This thesis presents an entirely new view to the problem of high level video segmentation. We developed a novel probabilistic method for affective level video content analysis and segmentation. Our method had two stages. In the first stage, a®ective content labels were assigned to video shots by means of a dynamic bayesian 0. Abstract 3 network (DBN). A novel hierarchical-coupled dynamic bayesian network (HCDBN) topology was proposed for this stage. The topology was based on the pleasure- arousal-dominance (P-A-D) model of a®ect representation [3]. In principle, this model can represent a large number of emotions. In the second stage, the visual, audio and a®ective information of the video was used to compute a statistical feature vector to represent the content of each shot. Affective level video segmentation was achieved by applying spectral clustering to the feature vectors. We evaluated the first stage of our proposal by comparing its emotion detec- tion ability with all the existing works which are related to the field of a®ective video content analysis. To evaluate the second stage, we used the time adaptive clustering (TAC) algorithm as our performance benchmark. The TAC algorithm was the best high level video segmentation method [2]. However, it is a very computationally intensive algorithm. To accelerate its computation speed, we developed a modified TAC (modTAC) algorithm which was designed to be mapped easily onto a field programmable gate array (FPGA) device. Both the TAC and modTAC algorithms were used as performance benchmarks for our proposed method. Since affective video content is a perceptual concept, the segmentation per- formance and human agreement rates were used as our evaluation criteria. To obtain our ground truth data and viewer agreement rates, a pilot panel study which was based on the work of Gross et al. [4] was conducted. Experiment results will show the feasibility of our proposed method. For the first stage of our proposal, our experiment results will show that an average improvement of as high as 38% was achieved over previous works. As for the second stage, an improvement of as high as 37% was achieved over the TAC algorithm

Watching men: masculinity and surveillance in the American serial killer film 1978-2008

This thesis explores the depiction of masculinity in the American serial killer film with a particular focus on the articulation of surveillance. I trace shifts and trends in films made between 1978 and 2008. Drawing on existing analyses of the serial killer panic, I argue that cinema swiftly assimilated FBI rhetoric which influenced the development of the serial killer as a cultural figure. In particular, I highlight the profiler as a crucial element of serial killer discourse. This thesis tracks the development of this figure within American cinema, investigates the influence of this character on portrayals of the serial killer, and argues that the killer and profiler are constructed as opposing agents of surveillance. Using a chronological approach, I investigate the films shaped by this historical moment, splitting them into time-specific cycles in order to understand the cultural shifts affecting their development. I argue that a fascination with surveillance is a factor in the continuing power of the serial killer, exploring the different ways in which surveillance is thematised in the films. Highlighting the gendered nature of surveillance, I contend that the films support gender norms, with the killer often functioning as a violent example of the suppression of non-normative expressions of gendered identity. Including discussions of both mainstream and niche films, I show that the serial killer is distanced from normative masculinity in ways which allude to the Gothic and to gender, class and race prejudice, constructing the status of the serial killer as a special, inscrutable individual removed from power structures. The thesis argues that cinematic representations have embraced certain elements of FBI rhetoric, emphasising the exceptional surveillance skills of the profiler. As a result, the serial killer is frequently depicted as an extraordinary figure requiring elite expertise. I consider the ramifications of these portrayals and discuss the moments at which patriarchal power structures underlying this form of violence are both concealed and exposed

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

Ambient Images

The digitization of the image has intensified the transformation of the relationship between humans and images. The proliferation of tools for the production of images and acceleration in their distribution has meant that a blasé attitude toward visual saturation, already prominent in the 20th century, has become more widespread. Writing in 1927, Siegfried Kracauer presciently spoke of a “blizzard of photographs.” In the first decades of the 21st century this grew into an environmental flood and the multiple streams along which people circulated images, challenged many of the traditional assumptions about the status and function of the image. Then came the pandemic. Suddenly, the relationship between the personal image and the public image was reconfigured. People hung out on platforms such as Instagram and Tik Tok with increased intensity and hunger. The platforms for virtual communication absorbed and at times aimed to compensate for the loss of events, meetings, face-to-face encounters and relationships. Confinement to the domestic sphere produced ever more mundane practices of co-present intimacy across platforms. For instance, while cross-generational practices of food photo sharing have long been a significant genre, photographs of home baking became an Instagram cliché, with “sourdough” becoming Google’s top food-related search phrase in 2020. The zoom boom soon became a new malaise—zoom fatigue. This adoption of virtual platforms was a profound incursion. It altered our sense of time and space as sense-making and social performance were increasingly aimed at and organised via camera and screen. Linear biographical narratives were cross-cut and spliced in novel ways. The image was less and less a document of an external reality, but more and more part of the new forms of mediated sociality. The diminution of physical engagements had an impact on how impressions were formed, what constituted the sensory triggers for memory, as well as shifting the markers for processes of understanding and decision-making. In this environment, images do not just multiply. Their increasing number also accentuates how they are stitched together to form new atmospheres, assemblages, iterations—or what we call the production of ambient images