Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
4,270
result(s) for
"Interactive art."
Sort by:
DeepFusionNet for realtime classification in iotbased crossmedia art and design using multimodal deep learning
The integration of Internet of Things (IoT) technologies with deep learning has introduced powerful opportunities for advancing cross-media art and design. This paper proposed DeepFusionNet, an IoT-driven multimodal classification framework developed to process real-time visual, auditory, and motion data acquired from distributed sensor networks. Rather than generating new content, the system classifies contextual input states to activate predefined artistic modules within interactive multimedia environments. The architecture of DeepFusionNet integrates Convolutional Neural Networks (CNNs) for spatial feature extraction, as well as Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) layers for modeling temporal dependencies in auditory and motion data. Additionally, it features fully connected layers for multimodal feature fusion and final classification. Input data undergoes comprehensive preprocessing, including normalization, imputation, noise filtering, and augmentation, to ensure consistent and high-quality multimodal representations. Extracted features from each modality are fused within the network to identify user interaction contexts that guide adaptive system responses. Unlike existing multimodal transformer-based frameworks, DeepFusionNet prioritizes low-latency and synchronized IoT processing, offering a Lightweight yet robust alternative for real-time interaction. Employing deep multimodal fusion rather than simple rule-based triggers ensures contextual awareness, scalability, and resilience in interactive art installations. Experimental evaluations demonstrate that DeepFusionNet achieves high performance, with 94.2% accuracy, 92.5% sensitivity, 96.1% specificity, 93.8% F1-score, 95.0% precision, MCC of 0.846, and an AUC of 0.96. Furthermore, the model achieves a 15% reduction in latency compared to baseline frameworks. The DeepFusionNet offers a scalable and real-time infrastructure for user-aware, IoT-enhanced cross-media art applications.
Journal Article
Emergence in interactive art
This text is concerned with emergence, interaction, art and computing. It introduces a new focus for emergence in interactive art: the emergent experience. Emergence literature is discussed and an organising framework, the Taxonomy of Emergence in Interactive Art (TEIA) is provided together with case studies of digital, interactive art systems that facilitate emergence. Evidence from evaluations of people interacting with the works is analysed using the TEIA. Artworks from across the world are also reviewed to further illustrate the potential for emergence. Interactive art is, itself, still a young domain where audience influence, or interaction with the work is a defining aspect. 'Emergence in Interactive Art' explores the rich opportunities for interactive experiences of digital art systems that are provided by looking through a 'lens' of emergence.
Book
A smart community interactive art therapy platform based on multimodal computer graphics and resilient artificial intelligence for home-based elderly care
This research presents an innovative smart community interactive art therapy platform that integrates multimodal computer graphics with resilient artificial intelligence adaptation mechanisms to address the growing challenges of home-based elderly care. The platform employs a four-layered hierarchical architecture encompassing perception, network, platform, and application layers to deliver personalized therapeutic interventions. The system utilizes multimodal data fusion algorithms to process visual, auditory, and haptic inputs while implementing adaptive learning mechanisms that continuously optimize user experiences based on individual preferences and capabilities. Experimental validation demonstrates superior performance with response times averaging 387 ms under 100 concurrent users, therapeutic recommendation accuracy of 87.3%, and user satisfaction scores of 4.2/5.0 across multiple evaluation dimensions. The resilient adaptation mechanisms achieved 99.7% service availability and 34% improvement in CPU utilization compared to conventional systems. Long-term usage tracking revealed sustained engagement patterns with minimal dropout rates over 6-month evaluation periods. The platform successfully addresses key limitations of traditional elderly care models by providing comprehensive support that encompasses cognitive stimulation, emotional well-being, and social connection while maintaining cost-effectiveness and scalability for large-scale deployment in smart community environments.
Journal Article
A Comprehensive Study of Emotional Responses in AI-Enhanced Interactive Installation Art
This study presents a comprehensive literature review on the convergence of affective computing, interactive installation art, multi-dimensional sensory stimulation, and artificial intelligence (AI) in measuring emotional responses, demonstrating the potential of artificial intelligence in emotion recognition as a tool for sustainable development. It addresses the problem of understanding emotional response and measurement in the context of interactive installation art under artificial intelligence (AI), emphasizing sustainability as a key factor. The study aims to fill the existing research gaps by examining three key aspects: sensory stimulation, multi-dimensional interactions, and engagement, which have been identified as significant contributors to profound emotional responses in interactive installation art. The proposed approach involves conducting a process analysis of emotional responses to interactive installation art, aiming to develop a conceptual framework that explores the variables influencing emotional responses. This study formulates hypotheses that make specific predictions about the relationships between sensory stimulation, multi-dimensional interactions, engagement, and emotional responses. By employing the ASSURE model combined with experimental design, the research methodology ensures a systematic and comprehensive study implementation. The implications of this project lie in advancing the understanding of emotional experiences in interactive installation art under AI, providing insights into the underlying mechanisms that drive these experiences, and their influence on individual well-being from a sustainable perspective. The contributions of this research include bridging the identified research gaps, refining theoretical frameworks, and guiding the design of more impactful and emotionally resonant interactive artworks with sustainability in mind. This research seeks not only to fill the existing gaps in understanding emotional experiences in interactive installation art, but also to guide the development of immersive and emotionally engaging installations, ultimately advancing the broader field of human–computer interaction, promoting individual well-being, and contribute to sustainable development.
Journal Article
Toni Dove : embodied machines
This uniquely designed book presents the first survey of contemporary artist Toni Dove's pioneering work at the crossroads of performance, cinema, and virtual reality. Credited as one of the innovators of \"interactive cinema,\" since the early 1990s, Toni Dove has created an oeuvre of \"speculative technology\" blending computer driven interactivity, live-mix performance and installation in projects which examine histories of consumer culture through evolving technologies. Dove's collaborative practice brings together visual artists, filmmakers, fashion designers, robotics engineers, computer programmers, musicians, actors, and writers-each at the vanguard of his or her own metier. Accompanying a major exhibition, this distinctively designed volume presents four of Dove's most notable works, including the debut of her newest work The Dress That Eats Souls, which exists at the forefront of computer and robotic technology.
Book
Hidden markov modeling of emotional state transitions in interactive installation art
Interactive installation art provides a distinctive context for examining collective emotion, yet most prior studies have relied on laboratory or longitudinal data that are impractical in public cultural settings. This study applied Hidden Markov Models (HMMs) to self-reported well-being data from
HappyHere
, a participatory light installation at the National Galleries of Scotland. Despite the cross-sectional design, the HMM framework enabled inference of latent affective states and probabilistic differentiation patterns, stability, and convergence patterns. The results show four key findings. First, three qualitatively distinct latent states were identified: a low/negative cluster (M ≈ 1.5), a moderately positive cluster (M ≈ 3.5), and a ceiling-level, highly positive cluster (all M = 5.0), confirming clear differentiation (H1). Second, positive states proved the most stable, with the highest self-transition probability (0.875) and the longest dwell time (≈ 3.4 steps), supporting H2. Third, neutral states were comparatively unstable, showing the lowest self-transition probability (0.093) and a tendency to shift toward positivity, consistent with H3. Finally, the stationary distribution strongly favored positivity, with positive states Reaching 86.3%, neutral states 7.5%, and negative states 6.2%. Minor diurnal variation was observed, but effect sizes were negligible, confirming the enduring predominance of positivity (H4). The findings demonstrate that even cross-sectional cultural datasets can yield meaningful insights through probabilistic modelling. Positive affect emerged as the most stable and dominant attractor, underscoring the capacity of participatory art to regulate emotion and foster collective well-being.
Journal Article
Vision anew : the lens and screen arts
\"The ubiquity of digital images has profoundly changed the responsibilities and capabilities of anyone and everyone who uses them. Thanks to a range of innovations, from the convergence of moving and still image in the latest DSLR cameras to the growing potential of interactive and online photographic work, the lens and screen have emerged as central tools for many artists. Vision Anew brings together a diverse selection of texts by practitioners, critics, and scholars to explore the evolving nature of the lens-based arts. Presenting essays on photography and the moving image alongside engaging interviews with artists and filmmakers, Vision Anew offers an inspired assessment of the medium's ongoing importance in the digital era. Contributors include Ai Weiwei, Gerry Badger, David Campany, Lev Manovich, Christian Marclay, Lâaszlâo Moholy-Nagy, Walter Murch, Trevor Paglen, Pipilotti Rist, Shelly Silver, Rebecca Solnit, and Alec Soth, among others. This vital collection is essential reading for artists, educators, scholars, critics and curators, and anyone who is passionate about the lens-based arts\"--Provided by publisher.
Book
Survey of real-time brainmedia in artistic exploration
This survey examines the evolution and impact of real-time brainmedia on artistic exploration, contextualizing developments within a historical framework. To enhance knowledge on the entanglement between the brain, mind, and body in an increasingly mediated world, this work defines a clear scope at the intersection of bio art and interactive art, concentrating on real-time brainmedia artworks developed in the 21st century. It proposes a set of criteria and a taxonomy based on historical notions, interaction dynamics, and media art representations. The goal is to provide a comprehensive overview of real-time brainmedia, setting the stage for future explorations of new paradigms in communication between humans, machines, and the environment.
Journal Article