Ubiquitous Emotion Analytics and How We Feel Today

Emotions are complicated. Humans feel deeply, and it can be hard to bring clarity to those depths, to communicate about feelings, or to understand others’ emotional states. Indeed, this emotional confusion is one of the biggest challenges of deciphering our humanity. However, a kind of hope might be on the horizon, in the form of emotion analytics: computerized tools for recognizing and responding to emotion. This analysis explores how emotion analytics may reflect the current status of humans’ regard for emotion. Emotion need no longer be a human sense of vague, indefinable feelings; instead, emotion is in the process of becoming a legible, standardized commodity that can be sold, managed, and altered to suit the needs of those in power. Emotional autonomy and authority can be surrendered to those technologies in exchange for perceived self-determination. Emotion analytics promises a new orderliness to the messiness of human emotions, suggesting that our current state of emotional uncertainty is inadequate and intolerable

Mapping the unseen: making sense of the subjective image.

It used to be thought that photography, as a kind of automatic mapping, could provide an objective view of the world. Now we are aware of the power of framing and other interventions between what is 'out there' and what is captured in depiction. Perhaps even perception, let alone depiction, shares this subjectivity? The Sapir-Whorf hypothesis holds that different cultures actually see the world in different ways, as evidenced and influenced by concepts in their languages – though this idea has been derided, for example by Pinker. A key difficulty is that the word subjectivity is bandied about without care for its different meanings and without distinguishing the many forms it takes in the graphic image. If into this muddle we introduce the idea of interactivity, still greater confusion easily follows. The chapter brings some order to different kinds and levels of subjectivity by documenting how they are reflected in forms of graphical mapping. In the process, it becomes clear how significant is the change in media technologies from those bound by the conventional rectangles of the page and screen to media which are interactive, pervasive, multimodal, physical and social

Eavesdropping Whilst You're Shopping: Balancing Personalisation and Privacy in Connected Retail Spaces

Physical retailers, who once led the way in tracking with loyalty cards and `reverse appends', now lag behind online competitors. Yet we might be seeing these tables turn, as many increasingly deploy technologies ranging from simple sensors to advanced emotion detection systems, even enabling them to tailor prices and shopping experiences on a per-customer basis. Here, we examine these in-store tracking technologies in the retail context, and evaluate them from both technical and regulatory standpoints. We first introduce the relevant technologies in context, before considering privacy impacts, the current remedies individuals might seek through technology and the law, and those remedies' limitations. To illustrate challenging tensions in this space we consider the feasibility of technical and legal approaches to both a) the recent `Go' store concept from Amazon which requires fine-grained, multi-modal tracking to function as a shop, and b) current challenges in opting in or out of increasingly pervasive passive Wi-Fi tracking. The `Go' store presents significant challenges with its legality in Europe significantly unclear and unilateral, technical measures to avoid biometric tracking likely ineffective. In the case of MAC addresses, we see a difficult-to-reconcile clash between privacy-as-confidentiality and privacy-as-control, and suggest a technical framework which might help balance the two. Significant challenges exist when seeking to balance personalisation with privacy, and researchers must work together, including across the boundaries of preferred privacy definitions, to come up with solutions that draw on both technology and the legal frameworks to provide effective and proportionate protection. Retailers, simultaneously, must ensure that their tracking is not just legal, but worthy of the trust of concerned data subjects.Comment: 10 pages, 1 figure, Proceedings of the PETRAS/IoTUK/IET Living in the Internet of Things Conference, London, United Kingdom, 28-29 March 201

Brain Computer Interfaces and Emotional Involvement: Theory, Research, and Applications

This reprint is dedicated to the study of brain activity related to emotional and attentional involvement as measured by Brain–computer interface (BCI) systems designed for different purposes. A BCI system can translate brain signals (e.g., electric or hemodynamic brain activity indicators) into a command to execute an action in the BCI application (e.g., a wheelchair, the cursor on the screen, a spelling device or a game). These tools have the advantage of having real-time access to the ongoing brain activity of the individual, which can provide insight into the user’s emotional and attentional states by training a classification algorithm to recognize mental states. The success of BCI systems in contemporary neuroscientific research relies on the fact that they allow one to “think outside the lab”. The integration of technological solutions, artificial intelligence and cognitive science allowed and will allow researchers to envision more and more applications for the future. The clinical and everyday uses are described with the aim to invite readers to open their minds to imagine potential further developments

Towards agent-based crowd simulation in airports using games technology

We adapt popular video games technology for an agent-based crowd simulation in an airport terminal. To achieve this, we investigate the unique traits of airports and implement a virtual crowd by exploiting a scalable layered intelligence technique in combination with physics middleware and a socialforces approach. Our experiments show that the framework runs at interactive frame-rate and evaluate the scalability with increasing number of agents demonstrating navigation behaviour

Practical Considerations for Face Recognition System Implementation: Retail Business Use Case

COVID-19 pandemic has proven experts’ prediction which stated that traditional retail might not survive in the coming age. During the pandemic, many longstanding retail brands barely survived, and some of them even went out of business. To survive and thrive, implementation of digital technologies to drive a more convenient shopping experience and enhance customer experience has proven to be crucial in gaining customer loyalty. One of the use cases that is gaining popularity nowadays is the implementation of Face Recognition system. The purpose of this study is to propose the practical solutions to three underlying issues of Face Recognition implementation: the simple but effective choice of framework, the discreet but effective way to arrange camera locations, and the light but robust choice of algorithm that could deliver good accuracy with minimum resources. This study used explorative descriptive method, combining authors’ direct experience with literature study. The result of this study is: proposed implementation framework, proposed camera arrangement, and proposed use of Neural Network algorithm with image augmentation. This study hopefully could give context to academics and fellow practitioners of the steps needed to implement Face Recognition to solve real world issues