Investigating Context Awareness of Affective Computing Systems: A Critical Approach

AbstractIntelligent Human Computer Interaction systems should be affective aware and Affective Computing systems should be context aware. Positioned in the cross-section of the research areas of Interaction Context and Affective Computing current paper investigates if and how context is incorporated in automatic analysis of human affective behavior. Several related aspects are discussed ranging from modeling, acquiring and annotating issues in affectively enhanced corpora to issues related to incorporating context information in a multimodal fusion framework of affective analysis. These aspects are critically discussed in terms of the challenges they comprise while, in a wider framework, future directions of this recently active, yet mainly unexplored, research area are identified. Overall, the paper aims to both document the present status as well as comment on the evolution of the upcoming topic of Context in Affective Computing

A Survey on Computational and Emergent Digital Storytelling

The research field of digital storytelling is cross-disciplinary and extremely wide. In this paper, methods, frameworks, and tools that have been created for authoring and presenting digital narratives, are selected and examined among hundreds of works. The basic criterion for selecting these works has been their ability to create content by computational, emergent methods. By delving into the work of many researchers, the objective is to study current trends in this research field and discuss possible future directions. Most of the relevant tools and methods have been designed with a specific purpose in mind, but their use could be expanded to other areas of interest or could at least be the steppingstone for other ideas. Therefore, the following works show elements of computational and emergent narrative creation and a classification is proposed according to their purpose of existence. Finally, new potential research directions in the field are identified and possible future research steps are discussed

Smart Glasses for Cultural Heritage: A Survey

This paper presents a comprehensive survey on the utilization of smart glasses in the context of cultural heritage. It offers a systematic exploration of prevailing trends, the latest state-of-the-art technologies, and notable projects within this emerging field. Through a meticulous examination of diverse works, this study endeavors to categorize and establish a taxonomy, thereby facilitating a structured analysis of the current landscape. By distilling key insights from this categorization, the paper aims to draw meaningful conclusions and provide valuable insights into the potential future trajectory of SGs technology in the realm of CH preservation and appreciation

A Personalized Heritage-Oriented Recommender System Based on Extended Cultural Tourist Typologies

Recent developments in digital technologies regarding the cultural heritage domain have driven technological trends in comfortable and convenient traveling, by offering interactive and personalized user experiences. The emergence of big data analytics, recommendation systems and personalization techniques have created a smart research field, augmenting cultural heritage visitor’s experience. In this work, a novel, hybrid recommender system for cultural places is proposed, that combines user preference with cultural tourist typologies. Starting with the McKercher typology as a user classification research base, which extracts five categories of heritage tourists out of two variables (cultural centrality and depth of user experience) and using a questionnaire, an enriched cultural tourist typology is developed, where three additional variables governing cultural visitor types are also proposed (frequency of visits, visiting knowledge and duration of the visit). The extracted categories per user are fused in a robust collaborative filtering, matrix factorization-based recommendation algorithm as extra user features. The obtained results on reference data collected from eight cities exhibit an improvement in system performance, thereby indicating the robustness of the presented approach

Non-manual cues in automatic sign language recognition

Present work deals with the incorporation of non-manual cues in automatic sign language recognition. More specifically, eye gaze, head pose, and facial expressions are discussed in relation to their grammatical and syntactic function and means of including them in the recognition phase are investigated. Computer vision issues related to extracting facial features, eye gaze, and head pose cues are presented and classification approaches for incorporating these non-manual cues into the overall Sign Language recognition architecture are introduced