International Journal of Arts and Technology (21 papers in press)

Regular Issues

• Audiences' Acceptance towards Technological Integration: a Case Study using PCA and HCA Method to Analyse Experience on Augmented Reality Public Sculpture Exhibited at Kota Samarahan, Sarawak  
  by Valerie Michael, Muhammad Fauzan Abu Bakar 
  Abstract: The study aims to explore and reveal the possible potential of augmented reality in redefining audience interaction and artistic communication, specifically concerning the incorporation of Augmented Reality into the development of public sculpture. This research utilises quantitative approaches, specifically Principal Component Analysis (PCA), p-values, confidence intervals and Hierarchical Cluster Analysis (HCA), to identify the primary component influencing audience experiences. A total of 38 participants are eligible to participate in the study and the results indicated that augmented reality may improve interactive encounters, emotional engagement, and consequently, a deeper comprehension of the artist's representations. The article explain how augmented reality can connect traditional and digital art, foster inclusivity, and promote critical thinking among its audience. This placing of the findings within the art context highlights some cultural and pedagogical implications of AR technology in the emerging paradigmatic application of participatory art activities.
  Keywords: Augmented Reality; Audience Engagement; Innovative Arts; Participatory Arts; Artistic Community.
  DOI: 10.1504/IJART.2026.10074055
   
  
• Application of Digital Image Media Technology in Film Animation  
  by Yan Liu, Feng Tang 
  Abstract: The development of media technology in the digital age has enabled many traditional artists to achieve new developments in their creations. The emergence of this expression method has greatly enriched the forms of artistic expression. This paper studies the application of digital image media technology in film and television animation. In the experimental part, it is applied to teaching, and experiments are conducted on several processes of animation production. The experimental results show that its application effect in the post-production link is most obvious. The scores of the experimental class are mainly concentrated in the 80100 points stage. There are 20 students in Class A who have reached 90100 points, 18 students in Class B who have reached 90100 points, and only five students in Class C who have reached 90100 points, and only six students in Class D who have reached 90100 points. It can be seen that the application of digital image media technology has effectively improved the production effect of animation. At the end of the paper, a brief summary of specific technologies and applications is given.
  Keywords: Film and Television Animation; Digital Image Technology; Post Production; Image Fusion Algorithm.
  DOI: 10.1504/IJART.2026.10074102
   
  
• Construction of a 3D Art Visualization Platform Based on Digital Engineering and VR Technology  
  by Danyang Li, Zixin Wang 
  Abstract: To address issues such as irregular 3D sculpting modelling, distortion in rendering of ink paintings and oil paintings, and low efficiency in collaborative workflows for multi-source art assets, this paper utilises an enhanced NVIDIA Omniverse architecture to optimise data processing efficiency and VR device compatibility in 3D art visualisation. First, this paper implements point cloud data compression and mesh simplification using an improved KD-tree algorithm; secondly, it develops a PBR material converter to automatically map traditional materials to physically-based rendering materials. Furthermore, the system implements a USDZ scene description file generation process, supporting real-time asset updates, BIM-compatible path tracing rendering, and distributed ray tracing with OptiX acceleration. Finally, this paper validates the performance of the platform through experiments. The experimental results show that the improved platform reduces GPU memory usage by 35%, reduces rendering latency by 56%, and achieves a VR device compatibility rate of 98.6%.
  Keywords: Digital Engineering; Virtual Reality Technology; 3D Visualization; Data Processing; Cross-platform Adaptation.
  DOI: 10.1504/IJART.2026.10074163
   
  
• Multimedia Art Data Optimisation by Integrating UO-CRUSH and Q-learning Algorithm VR Technology  
  by Hongying Song, Xiaohong Wang 
  Abstract: A resource management framework based on virtual reality (VR) technology is proposed to address the limitations and poor presentation effects of traditional multimedia art data flat creation. It integrates the UO-CRUSH algorithm driven by resource interest and the Q-learning algorithm driven by user interest to optimise the storage and scheduling of multimedia art data. The experimental results show that the proposed model has an average computation time of 426 seconds, completes an average of 752 tasks in the maximum cycle, and has a uniform distribution of resource placement groups (137153). In the instance verification, the classification accuracy is not less than 90%, the interactive response speed is 172 ms, and the frame rate of the picture reaches 78fps, which combines good immersion and economy. This model effectively improves the optimisation effect of multimedia art data.
  Keywords: Multimedia art data; Virtual reality; Scalable replica hashing algorithm; Reinforcement learning algorithm; Resource management.
  DOI: 10.1504/IJART.2026.10074165
   
  
• Developing a Community Participation Strategy for the Preservation of Historic Buildings in Shanghai  
  by Lu Chen 
  Abstract: This study introduces a novel approach that is specifically designed to align with China's unique national circumstances, allowing for the active involvement of the community. We propose a "community participation framework" that incorporates distinctive local features, formulated through an extensive review and synthesis of both domestic and international literature, as well as drawing insights from effective community governance practices in China. The framework seeks to harmonise the interactions between community members, historic structures, and municipal authorities. Within this structure, these stakeholders can create a cohesive and self-sustaining system, mutually benefiting from the preservation efforts of historical architecture. To guarantee ongoing advancements in this initiative, oversight and management practices were implemented, utilising performance evaluation metrics to measure the protective measures' effectiveness. Our findings offer valuable insights for furthering the engagement of social forces in the conservation of historical buildings in China.
  Keywords: Community Engagement; Conservation of Historic Buildings; Layered Analysis; Framework Development.
  DOI: 10.1504/IJART.2026.10074166
   
  
• Quantitative Evaluation of the Effectiveness of Preservation of Modern Urban Residential Buildings in Shanghai (1910-1949)  
  by Lu Chen 
  Abstract: This study examines modern residential buildings in Shanghai 19101949), analysing the dynamic relationships among architecture, inhabitants, the environment, and society. Addressing the urgent need to conserve Shanghai historical structures, it establishes key evaluation metrics for preservation effectiveness. Employing a quantitative approach validated by a BP neural network model, the analysis demonstrates that current conservation strategies fail to fully harness their potential to drive economic growth, enhance resident quality of life, foster environmental sustainability, or enrich urban cultural heritage. Recognising the intrinsic link between historical preservation and collective well-being encompassing human, environmental, and societal dimensions the research develops optimisation strategies to maximise conservation outcomes. The goal is to significantly elevate the impact of preservation efforts on these buildings, establishing a benchmark for scholarly research, policy formulation, and heritage management in Shanghai and analogous contexts.
  Keywords: Quantitative Assessment of Conservation Effectiveness; AHP; FCE;BP.
  DOI: 10.1504/IJART.2026.10074167
   
  
• Building Immersive Virtual Reality Visualisation Display System based on Multi-Level Interaction for Metaverse  
  by Yong Zhang, Xiaocheng Zhou, Mengzi Zhang, Lei Ding, RongWang Yin 
  Abstract: Currently, art and design education primarily relies on two-dimensional image presentations, lacking support from immersive and interactive metaverse environments. This limits the ability to effectively demonstrate the dynamic aspects of the design process, thus hindering students in-depth understanding of the design process. This research uses the Unity engine as its platform, leveraging its material and lighting capabilities, to develop an immersive virtual reality (VR) visualisation system to enhance art and design teaching effectiveness. After testing, the results showed that the immersive VR visualisation system based on Unity engine technology achieved an average immersion score of 8.7, and the average task completion time was 2.76 seconds. Research shows that the system designed in this paper not only enhances the immersion and interactivity of teaching, enriches teaching content, and optimises the remote learning experience, but also provides strong support for innovation in educational technology.
  Keywords: Immersive Virtual Reality; Art Design; Visual Display System; Multi-level Interaction; Metaverse Background.
  DOI: 10.1504/IJART.2026.10074168
   
  
• Digital Preservation of Art and Architectural Motifs: a Technology-Integrated Design Framework for the Dimasa Heritage Monuments  
  by Swarnadeep Nath, Sourish Sarkar, Bhaskar Saha 
  Abstract: Cultural heritage, rooted in historical, cultural, and religious traditions, is essential to regional identity and national legacy. In Assam, Northeast India, diverse indigenous communities have shaped a rich architectural tradition. However, limited written records obscure much of this history, making material culture monuments, archaeological sites, and architectural remains a crucial source for reconstructing the regions understudied past. Among these contributions, the Dimasa emerged as prominent rulers who significantly shaped the architectural heritage of the region. Over time, though, the remnants from the kingdom have faced significant erosion due to various organic and environmental factors, risking the loss of invaluable relics without precise preservation and restoration. This study aims to digitally restore the structural integrity and design aesthetics of the Dimasa Kingdoms heritage monuments at Khaspur. Integrating 2D and 3D framework with terrestrial and aerial photogrammetry ensures accurate structural documentation, while close-range photography captures intricate design motifs. The combined datasets support a comprehensive design process aligned with the studys objectives. This imperative study holds the potential to ensure the digital preservation of the regions heritage monuments. Moreover, this effort may recreate novel opportunities as a resource for researchers and archaeologists, especially within the context of upcoming restoration and conservation efforts.
  Keywords: Dimasa kingdom; Architectural motifs; Art and technology; Digital restoration; Cultural heritage.
  DOI: 10.1504/IJART.2026.10074182
   
  
• Image based Digital Processing Technology and System for Music Signals  
  by Huan Li 
  Abstract: Traditional music signal digital processing only focuses on the time-frequency characteristics of audio signals, ignoring the image features related to music signals, which leads to limitations in the overall understanding and representation of music signals. By comprehensively utilizing the characteristics of audio and image signals, a more comprehensive and accurate music signal processing method was proposed to comprehensively and accurately understand music emotions. The music emotion data from MediaEval Emotion in Music, MagnaTagATune Dataset, EmoReact Dataset, and DEAM Dataset were selected, preprocessed, and mapped to represent music emotions using Valence and Arousal. The Long Short-Term Memory (LSTM) - Residual Network (ResNet) model was constructed, with the LSTM module used to extract audio features and the ResNet module used to extract image features. In the fusion layer, the features extracted by the LSTM module and ResNet module were fused 1:1. A music recommendation system was constructed based on user historical preferences and recognition results of music emotions. The experimental results showed that the average accuracy of LSTM-ResNet model in music emotion classification on DEAM Dataset was as high as 98.5%. The combination of LSTM and ResNet can enhance the performance of music emotion classification and provide new methods for music recommendation tasks.
  Keywords: Music Signals; Emotional Classification; Music Recommendations; Music Images; Long Short-Term Memory; Residual Network.
  DOI: 10.1504/IJART.2026.10074476
   
  
• Classification and Recognition of Visual Communication Elements using Multimodal Fusion Affective Computing  
  by Yihan Yang, Xuehang Wu 
  Abstract: This paper aims to study a method for classifying and recognising visual communication elements based on multimodal fusion affective computing technology, in order to improve the accuracy of information transmission and the ability to express emotions. First, this paper utilises Pythons Scrapy library to automatically collect, filter, and preprocess image and text data using open-source computer vision libraries and regular expressions. Then, this paper uses the ResNet model to extract image features and the Transformer-based bidirectional encoder representation (BERT) model to extract text features, and fuses them through an attention mechanism. Finally, this paper uses the support vector machine (SVM) algorithm to classify the features, thus completing the classification and recognition of visual communication elements. Experimental results show that the proposed model performs well in emotion classification and recognition tasks, with high accuracy and stability.
  Keywords: Multimodal Fusion Affective Computing; Visual Communication Element; Residual Network; Bidirectional Encoder Representations from Transformers; Attention Mechanism.
  DOI: 10.1504/IJART.2026.10075026
   
  
• Combination of Visual Art Perspective Painting Style and Modern Interior Public Cultural Space Design  
  by Weiwei Zhang, Kaiyan Wong, Xiaojuan Liu 
  Abstract: This study addresses the prevalent lack of artistic expression in public cultural spaces, which often results in visually monotonous environments with diminished cultural atmosphere and emotional engagement. To achieve a balance between functionality and aesthetics, we propose an integrative design framework that incorporates four distinct painting styles-abstractionism, impressionism, cubism, and realism into spatial design. While the museum serves as the primary case for in-depth intervention and analysis, the frameworks applicability is systematically extended to other public cultural spaces, including city libraries, community cultural centres, science and technology exhibition halls, and historical memorial halls. The design integration encompasses multiple architectural elements such as walls, ceilings, floors, exhibition stands, entrances, and exhibit backgrounds, each informed by specific stylistic principles. Results demonstrate that the fusion of painting styles significantly enhances spatial appeal and audience engagement. For instance, in the museum, the abstract style design increased average visitor stay time from 1.2 hours to 2.4 hours and interaction frequency from three to eight times. Cross-case analysis confirms the frameworks broad effectiveness, with consistent improvements in dwell time and interactivity across all space types. This research establishes a replicable, interdisciplinary model for enriching diverse public cultural environments through art-informed spatial design
  Keywords: Painting Style; Modern Interior; Public Culture; Space Design; Visual Art Perspective.
  DOI: 10.1504/IJART.2026.10075152
   
  
• Exploration on High Dynamic Dance Video Keyframe Extraction Based on Clustering Algorithm  
  by Zhuoying Qi 
  Abstract: The amount of dance videos is also increasing, and how to watch dance videos rapidly and efficiently is already an issue that needs to be solved nowadays The research on an efficient way to watch the key information of dance video is of great help to dance learning and dance posture analysis Based on this, this paper studied the keyframe extraction of high dynamic dance video, and proposed a keyframe extraction method based on K-means clustering algorithm (KMA) Firstly, this paper proposed a method of shot segmentation by using histogram features for edge extraction, and then compared the similarity between video frames Finally, the KMA was used to match the video frames with the nearest cluster, and the dance video keyframes were determined by evaluating the sum of the similarity between the cluster centre and all sample frames of the cluster After putting forward the keyframe extraction method, this paper analysed its extraction effect, and drew the following conclusions through experimental research: compared with the extraction results of the traditional keyframe extraction method, the precision of the extraction results of the improved KMA was 6.5% higher, and the recall rate was 8.8% higher. The keyframe extraction method based on the improved KMA has good results.
  Keywords: Keyframe Extraction; High Dynamic Dance Video; Clustering Algorithm; K-means Clustering Algorithm.
  DOI: 10.1504/IJART.2026.10075220
   
  
• Aesthetic Relevance of Generative Artificial Intelligence  
  by Umberto Roncoroni 
  Abstract: This article examines the impact of generative artificial intelligence (GAI) on contemporary art, creative practice, and education. Evaluating the benefits and drawbacks of GAI is difficult due to the accelerated development of technology and weak academic relationships among aesthetics and computer science. To elucidate GAI, we propose setting aside metaphysical dilemmas and concentrating on the aesthetic problems of AI such as romantic influences, technocentric approaches to creativity, black boxes, and misunderstanding about the properties of digital media. Through an approach that combines philosophical analysis, computer science, and art-based research, we compare the Dadaist Poem by Tzara with GAI to verify its coherence with contemporary art development. We found that GAI contradicts contemporary art innovations and the aesthetic potential of digital media. The results demonstrate why GAI will jeopardize the development of creative and significant art and proffer a review of theories, methods, and interdisciplinary references.
  Keywords: Aesthetics; Avant-gardes; Computational Creativity; Contemporary Art; Dadaism; Digital Media; Generative Artificial Intelligence; Interactivity; Postmodernism; Public Art.
  DOI: 10.1504/IJART.2026.10075314
   
  
• Design of Three-Dimensional System of Computer Aided Dance Teaching Technology Management  
  by Hongmei Li 
  Abstract: Traditional dance teaching has problems such as single means, low efficiency, and difficulty in intelligent scheduling of teaching content. To this end, this paper designs a computer-aided three-dimensional dance teaching technology management system, constructs a three-layer system architecture with logic representation layer, business logic layer and database as the core, and integrates embedded communication protocols to achieve stable transmission and response of teaching data between multiple modules; in terms of action recognition algorithm, the system extracts multi-resolution features based on high-resolution network (HRNet), and performs convolution, interpolation and cascade operations between different resolutions through the sequence multi-scale feature fusion model to obtain highly semantic and accurately positioned joint point heat maps, and then constructs a geometric relationship estimation network with a three-layer structure, predicts the position relationship according to the trunk and limb joints, and matches the connection, completing the accurate modelling of dance movements. Experimental results show that the system has the highest accuracy of 95.3% in dance movement recognition tasks and 85.3% in posture estimation. This paper verifies the effectiveness and practical value of the technology management system that combines multi-module system design with multi-scale sequence fusion algorithm in dance teaching.
  Keywords: Dance Teaching; Technology Management; Embedded System; Feature Fusion Algorithm; Pose Estimation.
  DOI: 10.1504/IJART.2026.10075649
   
  
• Modelling of Outdoor Building Facade Automated Image Decoration Design System Based on Point Cloud Semantic Segmentation  
  by Jing Liu 
  Abstract: This paper aims to solve the problems of insufficient accuracy of point cloud semantic segmentation and poor system scalability in the automated decoration design of building facades, and constructs a three-module system including point cloud semantic segmentation, semantic-driven image decoration design, and result mapping. This paper addresses heterogeneous complex facade components and boundary fuzziness by optimising point cloud semantic segmentation with multi-scale feature fusion and boundary refinement achieving classification accuracy of 0.820.93 mIoU 0.87 and improved structural IoU 0.84 with 4.7-pixel keypoint error reduction. A semantic-constrained decoration module integrates style rules and geometric alignment yielding style matching 8.0 and structural alignment 8.46. The system automates 138 tasks hourly with 92.54% completion and 7.76% manual intervention demonstrating efficient structural-semantic-decoration integration.
  Keywords: Point Cloud Semantic Segmentation; Building Facade Modeling; Automated Image Decoration Design; Three-dimensional Structure Recognition; Multi-style Adaptability.
  DOI: 10.1504/IJART.2026.10075668
   
  
• Two Dimensional Digital Art Animation Synthesis System Based on BP Neural Network  
  by Zhouzhou Cheng, Xiao Xia 
  Abstract: At present, 2D animation still faces problems such as difficulty in getting rid of the production methods mainly based on manual creation and low creation efficiency. This paper aims to use BP neural network to construct and study a two-dimensional digital art animation synthesis system, in order to improve the production efficiency of two-dimensional animation. This paper first introduces the structure, advantages, and algorithm principles of BP neural network, and then explains the technology of two-dimensional digital art animation production. After constructing a two-dimensional digital art animation synthesis system model, this paper performs performance and image processing of the synthesis system, checks and confirms the advantages and disadvantages of the model, and then provides a rough overview of the artificial system. The results showed that the maximum error of the BP neural network in the experiment was less than 9%, and the average error was reduced to 5%.
  Keywords: 2D Digital Art Animation ; BP Neural Network ; Poisson Equation; Bezier Curve.
  DOI: 10.1504/IJART.2026.10075881
   
  
• Cross-Platform Music Recommendation Method and Innovation Path Based on the Internet of Things and Blockchain  
  by Jin Ma, Yi Li 
  Abstract: Traditional music recommendation systems have not yet implemented cross platform applications, and the improvement of recommendation effectiveness is limited by the limitations of the recommendation system itself. This paper aims to study how to analyse and investigate cross platform music recommendation methods based on IoT and blockchain technology. This paper tests four recommendation algorithm models for different recommendation list lengths. Experimental data shows that when the recommendation list length is 60, the accuracy, recall, and F1 score of the hybrid recommendation algorithm model are 62.14%, 50.64%, and 0.559, respectively, which are superior to the other three recommendation algorithms. In addition, when the number of users using the system is 60, the security of the system is 97.80%. A series of data proves that the cross platform music recommendation system based on the Internet of Things and blockchain designed in this paper is feasible and worthy of further promotion and application.
  Keywords: Music Recommendation Method; Internet of Things; Blockchain Technology; Music Platform.
  DOI: 10.1504/IJART.2027.10076014
   
  
• Integrating Actor-Network Theory and Speculative Design: Exploring Innovations in HCI Education from a More-than-Human Perspective  
  by Jiawei Li, Zhiyong Fu, Jiayue Wang, Lin Zhu, Jiaxuan Xu 
  Abstract: This study explores integrating Actor-Network Theory (ANT) and speculative design into Human-Computer Interaction (HCI) education to cultivate students' More-than-Human Design capabilities. Traditional human-centered approaches are insufficient for complex socio-technical challenges; students need new frameworks to understand human and non-human actor interactions. ANT analyzes HCI systems, emphasizing human-technology co-construction while recognizing human agency. Speculative design provides innovative methods for exploring HCI possibilities through provocative artifacts and narratives. A workshop guided students in applying ANT and speculative design to analyze More-than-Human systems, comparing human participation and AI-assisted generation results. This demonstrated AI's potential to enrich HCI education. The research offers a comprehensive framework combining theory and practice, fostering students' critical thinking and innovative awareness for envisioning future human-computer interaction designs.
  Keywords: Human-Computer Interaction education; More-than-Human Design; Actor-Network Theory; Speculative Design; Design pedagogy.
  DOI: 10.1504/IJART.2027.10076214
   
  
• Personalised News Recommendation System Based On Computer Artificial Intelligence Technology  
  by Qiang Wang 
  Abstract: In this paper, intelligent recommendation, an artificial intelligence algorithm, was incorporated into the design of digital media. Collaborative filtering algorithm was used to design a personalised news recommendation system. According to the current user's historical reading records, praise and sharing behaviour, collaborative filtering algorithm was used to recommend interesting news reports for users. Specific types of news were pushed to users based on algorithmic recommendations and were available to users through personalised news display pages. According to the validation of experimental data results, after algorithm processing, the existing calculated similarity was 0.85638. The top few target objects with the highest similarity were selected and pushed to users. Finally, data and opinions were collected through a survey questionnaire. The research results showed that integrating artificial intelligence technology into digital media can improve the design, innovation, and user experience of digital media, and provide users with more intelligent and personalised services.
  Keywords: Collaborative Filtering; Digital Media; Personalize News; Intellectualized System; Artificial Intelligence.
  DOI: 10.1504/IJART.2027.10076522
   
  
• Analysis of Brushstrokes during the Creation of a Painting of a Peach  
  by Otoniel Igno-Rosario, Claudia Hernández-Aguilar, Luis Manuel Hernández-Simón, Flavio Arturo Domínguez-Pacheco, Jose Alberto Medina-Pérez 
  Abstract: This study presents a systematic video-based analysis of brushstrokes during the creation of a peach painting. Using a dual-camera setup that simultaneously captured top and side views, we recorded 23 preliminary strokes and the complete sequence of 281 strokes that formed the final artwork. Each stroke was processed frame by frame to extract spatial-temporal features, including three-dimensional coordinates, orientation angles, and stroke velocity. Our research was motivated by the limited availability of annotated data on brushstrokes and the need for interpretability of human stroke dynamics. The study is presented as a preliminary case painting that generates evidence-based data to support further research in the field of computational art and robotic painting. Code is available at https://github.com/oton-lab/brushstrokes.
  Keywords: brushstroke analysis; video processing; artistic painting; computational creativity.
  DOI: 10.1504/IJART.2027.10076644
   
  
• Knowledge Mapping and Mechanistic Insights in Emotional Digital Design: An Empirical Study Combining Clustering and Thematic Analysis  
  by Lan Ma, Yiyuan Ding, Chenxi Dong, Tang Liu, Zhenyu Li, Wenlei Mao, Tianyi Liu, Fernando Jorge Matias Sanches Oliveir, Xue Zhu, Lianfa Xu, Guangyi Tang, Feng Sha 
  Abstract: This study maps the knowledge structure of emotional digital design using bibliometric co-word clustering and three-round thematic analysis of 3,817 Web of Science records. Six major research clusters were identified: design and technology, health and care, education and learning, mental health and emotion regulation, workplace studies, and conversational agents, revealing their evolution over time. Thematic analysis highlights research hotspots and cross-disciplinary trends that guide the fields development. By integrating quantitative mapping with qualitative interpretation, the study provides both a structural overview and detailed thematic insights. This dual-method approach enables researchers and practitioners to better understand the fields current state and future directions. It also addresses the limitations of traditional keyword co-occurrence analysis its lack of semantic depth and mechanistic insight by combining bibliometric clustering with multi-round thematic analysis, delivering a structural map and explanatory understanding of emotional digital design.
  Keywords: Emotional Digital Design; Affective Design Environments; Emotion-Centered Interaction; Experiential Design; User Engagement.
  DOI: 10.1504/IJART.2027.10076828