Eyewear Computing \u2013 Augmenting the Human with Head-Mounted Wearable Assistants

The seminar was composed of workshops and tutorials on head-mounted eye tracking, egocentric vision, optics, and head-mounted displays. The seminar welcomed 30 academic and industry researchers from Europe, the US, and Asia with a diverse background, including wearable and ubiquitous computing, computer vision, developmental psychology, optics, and human-computer interaction. In contrast to several previous Dagstuhl seminars, we used an ignite talk format to reduce the time of talks to one half-day and to leave the rest of the week for hands-on sessions, group work, general discussions, and socialising. The key results of this seminar are 1) the identification of key research challenges and summaries of breakout groups on multimodal eyewear computing, egocentric vision, security and privacy issues, skill augmentation and task guidance, eyewear computing for gaming, as well as prototyping of VR applications, 2) a list of datasets and research tools for eyewear computing, 3) three small-scale datasets recorded during the seminar, 4) an article in ACM Interactions entitled \u201cEyewear Computers for Human-Computer Interaction\u201d, as well as 5) two follow-up workshops on \u201cEgocentric Perception, Interaction, and Computing\u201d at the European Conference on Computer Vision (ECCV) as well as \u201cEyewear Computing\u201d at the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp)

Can Large Language Models Be Good Companions? An LLM-Based Eyewear System with Conversational Common Ground

Developing chatbots as personal companions has long been a goal of artificial intelligence researchers. Recent advances in Large Language Models (LLMs) have delivered a practical solution for endowing chatbots with anthropomorphic language capabilities. However, it takes more than LLMs to enable chatbots that can act as companions. Humans use their understanding of individual personalities to drive conversations. Chatbots also require this capability to enable human-like companionship. They should act based on personalized, real-time, and time-evolving knowledge of their owner. We define such essential knowledge as the \textit{common ground} between chatbots and their owners, and we propose to build a common-ground-aware dialogue system from an LLM-based module, named \textit{OS-1}, to enable chatbot companionship. Hosted by eyewear, OS-1 can sense the visual and audio signals the user receives and extract real-time contextual semantics. Those semantics are categorized and recorded to formulate historical contexts from which the user's profile is distilled and evolves over time, i.e., OS-1 gradually learns about its user. OS-1 combines knowledge from real-time semantics, historical contexts, and user-specific profiles to produce a common-ground-aware prompt input into the LLM module. The LLM's output is converted to audio, spoken to the wearer when appropriate.We conduct laboratory and in-field studies to assess OS-1's ability to build common ground between the chatbot and its user. The technical feasibility and capabilities of the system are also evaluated. OS-1, with its common-ground awareness, can significantly improve user satisfaction and potentially lead to downstream tasks such as personal emotional support and assistance.Comment: 36 pages, 25 figures, Under review at ACM IMWU

Enhancing the online decision-making process by using augmented reality: a two country comparison of youth markets

Although online stores extend the traditional offer of the brick and mortar ones, the limited possibilities to virtually try the product before the effective buying makes the online purchase decision a complex process for consumers. Therefore, online retailers face new challenges for supporting consumers consisting of the introduction of advanced technologies such as augmented reality systems. The present study investigates the effect of augmented reality technologies on consumer behaviour within the online retail environments, by comparing two different cultural settings. Drawing upon the technology acceptance model (TAM), new constructs related to the technology characteristics (e.g. quality of information, aesthetic quality, interactivity, and response time) developed a new conceptual model. This model has been tested for a new technology for virtual try-on (a smart mirror for virtual glasses). Focusing on young consumers, data collected in Italy and Germany yielding a total of 318 participants was used. Findings across these two markets reflect cross-market similarities, but also dissimilarities, related to consumers’ motivation to employ augmented reality systems for supporting their online purchase decision. These insights should prove helpful to retailers in better manage the online channels, that could be easily extended to the mobile one

Strategic coupling and institutional innovation in times of upheavals: the industrial chain chief model in Zhejiang, China

For regions that are deeply integrated into the global economy, the question of how to remain competitive and resilient in times of uncertainty is a key concern. While strategic coupling is a useful concept for understanding local-global economic dynamics, the idea that a region can simultaneously couple into multiple production networks organised at different spatial scales and that regional actors can increase their autonomy by creatively combining different coupling scenarios has been little explored. This paper explores how regional institutional innovations can facilitate such multiple couplings. We focus on the industrial chain chief model in China’s Zhejiang province, which emerged against the backdrop of the U.S.-China trade war and the COVID-19 pandemic. We argue that this institutional innovation offers a different way of thinking for regions that have long been exposed to the influence of globalisation, and that it increases the agency of local actors in global production networks

The Extended Mind and Network-Enabled Cognition

In thinking about the transformative potential of network technologies with respect to human cognition, it is common to see network resources as playing a largely assistive or augmentative role. In this paper we propose a somewhat more radical vision. We suggest that the informational and technological elements of a network system can, at times, constitute part of the material supervenience base for a human agent’s mental states and processes. This thesis (called the thesis of network-enabled cognition) draws its inspiration from the notion of the extended mind that has been propounded in the philosophical and cognitive science literature. Our basic claim is that network systems can do more than just augment cognition; they can also constitute part of the physical machinery that makes mind and cognition mechanistically possible. In evaluating this hypothesis, we identify a number of issues that seem to undermine the extent to which contemporary network systems, most notably the World Wide Web, can legitimately feature as part of an environmentally-extended cognitive system. Specific problems include the reliability and resilience of network-enabled devices, the accessibility of online information content, and the extent to which network-derived information is treated in the same way as information retrieved from biological memory. We argue that these apparent shortfalls do not necessarily merit the wholesale rejection of the network-enabled cognition thesis; rather, they point to the limits of the current state-of-the-art and identify the targets of many ongoing research initiatives in the network and information sciences. In addition to highlighting the importance of current research and technology development efforts, the thesis of network-enabled cognition also suggests a number of areas for future research. These include the formation and maintenance of online trust relationships, the subjective assessment of information credibility and the long-term impact of network access on human psychological and cognitive functioning. The nascent discipline of web science is, we suggest, suitably placed to begin an exploration of these issues

Unveiling causal attention in dogs' eyes with smart eyewear

Our goals are to better understand dog cognition, and to support others who share this interest. Existing investigation methods predominantly rely on human-manipulated experiments to examine dogs’ behavioral responses to visual stimuli such as human gestures. As a result, existing experimental paradigms are usually constrained to in-lab environments and may not reveal the dog’s responses to real-world visual scenes. Moreover, visual signals pertaining to dog behavioral responses are empirically derived from observational evidence, which can be prone to subjective bias and may lead to controversies. We aim to overcome or reduce the existing limitations of dog cognition studies by investigating a challenging issue: identifying the visual signal(s) from dog eye motion that can be utilized to infer causal explanations of its behaviors, namely estimating causal attention. To this end, we design a deep learning framework named Causal AtteNtIon NEtwork (CANINE) to unveil the dogs’ causal attention mechanism, inspired by the recent advance in causality analysis with deep learning. Equipped with CANINE, we developed the first eyewear device to enable inference on the vision-related behavioral causality of canine wearers. We demonstrate the technical feasibility of the proposed CANINE glasses through their application in multiple representative experimental scenarios of dog cognitive study. Various in-field trials are also performed to demonstrate the generality of the CANINE eyewear in real-world scenarios. With the proposed CANINE glasses, we collect the first large-scale dataset, named DogsView, which consists of automatically generated annotations on the canine wearer’s causal attention across a wide range of representative scenarios. The DogsView dataset is available online to facilitate research

Industrial districts and the fourth industrial revolution

Purpose: This paper aims to explore if firms located in industrial districts (IDs) have different adoption paths concerning Industry 4.0 technologies and get different results with respect to other similar firms located outside IDs. Design/methodology/approach: The study is based on a quantitative analysis related to an original data set of 206 Italian manufacturing firms specializing in made in Italy industries and adopting Industry 4.0 technologies. A case study of a district firm is also presented to explain the rationale of investment strategies and results obtained. Findings: The analysis shows that there are differences between district and non-district firms when Industry 4.0 technology investments are concerned (higher investment rate in big data/cloud and augmented reality for district firms than non-district ones). In contrast to a breakthrough view of the fourth industrial revolution, the study suggests that 4.0 technologies emphasize the peculiarities and competitiveness factors typical of the district model in terms of customization and flexibility. There are differences in the motivations of adoption (product diversification for district firms vs productivity enhancement for non-district firms) and in the results achieved. Originality/value: The paper is one of the first attempts to empirically explore the technological innovation paths related to Industry 4.0 within IDs, therefore, contributing to the debate on the possible evolution of the district mode