Entertainment Computing最新文献_第9页

Impact of social media on the psychological well-being of rural Youth- A systematic literature review and bibliometric analysis 社交媒体对农村青年心理健康的影响——系统文献综述与文献计量分析

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2025-08-19 DOI: 10.1016/j.entcom.2025.101012

M. Anshida , P.P. Murugan , M. Senthilkumar , M. Chandrakumar , G. Vanitha

The rise of social media has profoundly influenced the mental health of young people, including rural youth who face unique socio-economic challenges. This systematic literature review and bibliometric analysis investigates the impact of social media on the psychological well-being of rural youth, examining both positive and negative aspects. Social media fosters social connectivity and educational access but also contributes to anxiety, depression and low self-esteem through social comparison and cyberbullying. A systematic search of peer-reviewed articles from 2019 to May 2024 was conducted using the Scopus database. Inclusion criteria focused on studies addressing the psychological effects of social media on rural youth. Data were analyzed using Bibliometrics, an R package for bibliometric analysis, to identify trends, collaborations and key themes. The findings highlight the dual nature of social media’s impact. While it provides opportunities for interaction and access to resources, excessive or maladaptive use, particularly exposure to idealized content and cyberbullying, poses significant mental health risks. Rural youth are especially vulnerable due to isolation and limited access to mental health support. Understanding this nuanced role is vital for designing interventions that maximize social media’s benefits while mitigating risks, promoting the psychological well-being of rural youth in the digital age.

社交媒体的兴起深刻影响了年轻人的心理健康，包括面临独特社会经济挑战的农村青年。本系统的文献综述和文献计量分析调查了社交媒体对农村青年心理健康的影响，检查了积极和消极的方面。社交媒体促进了社会联系和教育机会，但也通过社会比较和网络欺凌导致焦虑、抑郁和自卑。使用Scopus数据库对2019年至2024年5月的同行评议文章进行了系统搜索。纳入标准侧重于解决社交媒体对农村青年心理影响的研究。数据分析使用文献计量学（一个用于文献计量学分析的R软件包），以确定趋势、合作和关键主题。这些发现凸显了社交媒体影响的双重性质。虽然它提供了互动和获取资源的机会，但过度或不适应地使用，特别是接触理想化的内容和网络欺凌，会造成重大的心理健康风险。农村青年由于孤立和获得精神健康支助的机会有限，尤其容易受到伤害。了解这种微妙的作用对于设计干预措施至关重要，这些干预措施可以最大限度地发挥社交媒体的好处，同时降低风险，促进数字时代农村青年的心理健康。

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引用次数: 0

Integrating artificial intelligence and gamification in rehabilitation: A scoping review 整合人工智能和游戏化在康复：范围审查

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2025-08-13 DOI: 10.1016/j.entcom.2025.101011

Minkai Wang , Jingdong Zhu , Wei Qian , Hanjie Gu

The integration of artificial intelligence (AI) and gamification represents a promising direction in rehabilitation, enabling personalized training, real-time feedback, and enhanced patient engagement. However, research in this area remains fragmented, necessitating a structured synthesis. This scoping review analyzed 20 studies published over the past two decades and indexed in PubMed, Cochrane Library, Web of Science, and IEEE Xplore. Stroke rehabilitation was the most frequently addressed condition (9 studies), followed by motor dysfunction (2), rheumatoid arthritis (2), cognitive impairment (3), phantom limb pain (2), ADHD (1), and multiple sclerosis (1). AI techniques included machine learning (10 studies), deep learning (4), and unspecified methods (6), while game-based interventions were categorized as gamification (4), serious games (8), and digital games (8). Reported outcomes indicated improvements in motivation, therapy adherence, and various metrics of rehabilitation performance. Nonetheless, key challenges persist, including small sample sizes, methodological heterogeneity, data privacy concerns, and the lack of large-scale clinical trials. Barriers related to cost, accessibility, and ethics also hinder broader implementation. Future research should prioritize multimodal data integration, AI-driven remote rehabilitation platforms, and wearable technologies to enhance scalability and clinical impact.

人工智能（AI）和游戏化的整合代表了康复领域的一个有前途的方向，可以实现个性化训练、实时反馈和增强患者参与。然而，这一领域的研究仍然是碎片化的，需要一个结构化的综合。这篇综述分析了过去二十年来发表的20篇研究，这些研究被PubMed、Cochrane图书馆、Web of Science和IEEE explore收录。中风康复是最常见的疾病（9项研究），其次是运动功能障碍（2项）、类风湿性关节炎（2项）、认知障碍（3项）、幻肢痛（2项）、多动症（1项）和多发性硬化症（1项）。人工智能技术包括机器学习（10项研究）、深度学习（4项）和未指明的方法（6项），而基于游戏的干预被归类为游戏化（4项）、严肃游戏（8项）和数字游戏（8项）。报道的结果表明，动机、治疗依从性和各种康复表现指标有所改善。尽管如此，关键的挑战仍然存在，包括样本量小、方法异质性、数据隐私问题以及缺乏大规模临床试验。成本、可及性和道德方面的障碍也阻碍了更广泛的实施。未来的研究应优先考虑多模式数据集成、人工智能驱动的远程康复平台和可穿戴技术，以增强可扩展性和临床影响。

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引用次数: 0

Reflection Stamps: A simple and positive method to support self-evaluation in illustration drawing 反射邮票：一种简单而积极的方法来支持插图绘画的自我评价

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2025-08-07 DOI: 10.1016/j.entcom.2025.100998

Seina Tajika, Hiroki Watanabe, Yoshinari Takegawa, Keiji Hirata

In this research, which targets illustration drawing, we designed, implemented and evaluated a system, called ‘Reflection Stamps’, to reduce the effort and mental burden of the act of reflecting on one’s work and encourage positive reflection. When drawing an illustration, it is important for the learner to reflect positively on their own work to aid the development of their technique. However, the majority of existing reflection methods require a great deal of effort, or else involve a negative approach of indicating points for improvement, which results in the problem that the act of reflection imposes a mental burden. The proposed ‘Reflection Stamps’ system is equipped with a word stamp function that makes it easy to record evaluation and feedback on each part of an illustration. The system is furnished with a large number of stamps with positive content to encourage the learner’s sense of self-affirmation. The results of the evaluation experiment showed that the proposed system reduced the time required for reflection by 60% in comparison to the comparative method, which was a conventional method. In addition, there was a 133% increase in positive reflections when compared to the comparative method, demonstrating that the proposed system facilitated many more positive reflections. Furthermore, the system received a rating of 79 points on the System Usability Scale, confirming that it has good usability. However, it also became clear that to increase operability it is necessary to improve the placement of the stamps, and the enlarge/reduce function. In future we aim to construct a system to better support skill improvement in illustration, by increasing the variety and range of expression of the stamps to enable effective and accurate reflection.

在这项以插画为目标的研究中，我们设计、实施并评估了一个名为“反思印记”的系统，以减少反思工作的工作量和精神负担，并鼓励积极的反思。在绘制插图时，对学习者来说，积极地反思自己的工作有助于他们技术的发展是很重要的。然而，现有的大多数反思方法都需要付出很大的努力，或者是一种消极的方法，即指出需要改进的地方，这就造成了反思行为给精神带来负担的问题。“反射图章”系统配备了一个单词图章功能，可以很容易地记录对插图每个部分的评价和反馈。系统设置了大量内容积极的图章，鼓励学习者的自我肯定意识。评价实验结果表明，与传统的比较法相比，该系统的反射时间缩短了60%。此外，与比较方法相比，积极反思增加了133%，这表明提议的系统促进了更多的积极反思。此外，该系统在系统可用性量表上获得了79分的评级，证实它具有良好的可用性。然而，很明显，为了提高可操作性，有必要改进邮票的放置和放大/缩小功能。在未来，我们的目标是构建一个系统，以更好地支持技能的提高，通过增加邮票的表达种类和范围，使有效和准确的反映。

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引用次数: 0

Personalizing empathy training with immersive virtual reality games: Development and user experience study 沉浸式虚拟现实游戏的个性化移情训练：开发和用户体验研究

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2025-07-31 DOI: 10.1016/j.entcom.2025.101004

Jiyoung Moon , Teemu H. Laine , Sunny Thapa Magar , Hae Jung Suk

Immersive virtual reality (IVR) has been successfully applied in various areas of psychology and learning. IVR has also been adapted for empathy training, but previous studies failed to consider various empathy types. We aimed to provide learners with personalized recommendations of empathy training content for different empathy types. Consequently, we presented Robot’s Dream, an IVR game suite providing personalized content based on the learner’s empathy type. We then conducted a mixed-method evaluation with 35 fifth and sixth-grade students who played Robot’s Dream and answered a post-test questionnaire on usability, user experience, and impact. The user study results demonstrated adequate usability and user experience with emotional engagement of the participants. However, the participants gave mixed reactions to realism and discomfort with the IVR hardware. The results also showed high perceived potential for empathy training and raising awareness of empathy. By retrospectively analyzing the development process and the user study results, we presented learned lessons and identified aspects in Robot’s Dream for future improvement. The presented development account of Robot’s Dream and the user study results can be helpful for educators, researchers, and developers interested in personalizing empathy training and other psychological training with IVR games.

沉浸式虚拟现实（IVR）已经成功地应用于心理学和学习的各个领域。IVR也被用于同理心训练，但之前的研究没有考虑到各种同理心类型。本研究旨在针对不同的共情类型，为学习者提供个性化的共情训练内容推荐。因此，我们提出了机器人的梦想，一个IVR游戏套件，根据学习者的移情类型提供个性化的内容。然后，我们对35名玩《机器人之梦》的五年级和六年级学生进行了混合方法评估，并回答了测试后关于可用性、用户体验和影响的问卷。用户研究结果表明，充分的可用性和用户体验与情感参与的参与者。然而，参与者对IVR硬件的现实和不舒服反应不一。结果还显示了移情训练和提高移情意识的高感知潜力。通过回顾性分析开发过程和用户研究结果，我们提出了机器人之梦的经验教训，并确定了未来改进的方面。机器人之梦的发展描述和用户研究结果可以帮助教育工作者、研究人员和开发人员对个性化移情训练和其他心理训练感兴趣的IVR游戏。

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引用次数: 0

Chasing the Rush: How horror games trigger adrenaline and fuel Fear-Inducing elements 追逐热潮：恐怖游戏如何激发肾上腺素并激发恐惧诱导元素

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2025-07-26 DOI: 10.1016/j.entcom.2025.101001

Klarisse Nicole N. Savino , Ronila Angela B. Mateo , Ardvin Kester S. Ong

Fear has been capitalized through horror video games, driving players to develop a craving for adrenaline-fueled fear, fostering fear-inducing elements, and leading to unhealthy behavioral patterns. This study examined how fear and adrenaline are triggered in horror video games, influencing play intention and actual gameplay, and how these experiences contribute to fear-inducing elements analyzed based on their stimulus-organism-response (S-O-R) aspects. The objective was to determine significant predictors of actual gaming of horror video games by analyzing data from 1,015 valid players using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach with SOR-based analysis. Findings revealed that fear-inducing elements strongly influenced psychological response and emotional value. In contrast, game design elements primarily impacted perceived control and play intention. It was revealed that both psychological and physiological responses contribute to emotional value, while cognitive processing played a more dominant role than physiological arousal in shaping emotional impact. In accordance, play intention strongly predicts actual gameplay, but excessive fear-inducing elements can reduce actual gameplay. These results highlight the need for game designers and developers to balance fear elements with adaptive difficulty, strategic pacing, and perceived control to enhance immersion while being physiologically, and psychologically safe. Horror game players can use these insights to manage their expectations and experiences effectively. For gaming industry marketers and publishers, responsible promotion of horror games should emphasize thrilling engagement and psychological safety, ensuring sustainable and innovative gaming practices.

恐惧通过恐怖电子游戏被充分利用，驱使玩家产生对肾上腺素刺激的恐惧的渴望，培养恐惧诱导元素，并导致不健康的行为模式。该研究考察了恐怖电子游戏是如何触发恐惧和肾上腺素，影响游戏意图和实际玩法，以及这些体验是如何根据刺激-有机体-反应（S-O-R）方面分析导致恐惧的元素的。我们的目标是通过使用偏最小二乘结构方程模型（PLS-SEM）方法和基于sor的分析分析1015名有效玩家的数据，确定恐怖电子游戏实际游戏的重要预测因素。研究发现，恐惧诱发因素对心理反应和情感价值有强烈影响。相比之下，游戏设计元素主要影响感知控制和游戏意图。结果表明，心理和生理反应对情绪价值的形成都有贡献，但认知加工在形成情绪影响方面的作用大于生理唤醒。因此，游戏意图强烈地预示着实际的游戏玩法，但过度的恐惧诱导元素会减少实际的游戏玩法。这些结果强调了游戏设计师和开发者需要平衡恐惧元素与适应性难度、战略节奏和感知控制，以增强沉浸感，同时保持生理和心理安全。恐怖游戏玩家可以利用这些见解有效地管理自己的期望和体验。对于游戏行业的营销人员和发行商来说，负责任的恐怖游戏推广应该强调刺激的沉浸感和心理安全，确保可持续和创新的游戏实践。

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引用次数: 0

Dynamic difficulty adjustment using a large language model: A case study in magic: The Gathering 使用大型语言模型进行动态难度调整：以《万智牌》为例

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2025-07-25 DOI: 10.1016/j.entcom.2025.100997

Xiaoxu Li , Zifan Ye , Yi Xia , Ruck Thawonmas

This paper presents a framework called LLM-MTG-DDA, which uses a large language model (LLM) in the real-world card game Magic: The Gathering (MTG) to act as a player and implement a dynamic difficulty adjustment (DDA) mechanism. LLMs, as a highly useful technology, have been explored across various fields. However, research on using LLMs for DDA in games, particularly in complex turn-based games, is very limited. In this paper, GPT-4o acts as two players in a simplified version of MTG. One GPT-4o player plays as a regular player (LLM-Player), while the other GPT-4o player adjusts its strategy based on the current game state to balance the difficulty (LLM-DDA). Our LLM-MTG-DDA framework, with a suitable objectives for different players, demonstrates reasonable DDA, with the LLM-Player’s win rate and the win rate per round (excluding draws) both approaching 50%. This framework provides insights for applying LLMs as DDA mechanisms in other similar games.

本文提出了一个名为LLM-MTG-DDA的框架，该框架利用现实纸牌游戏《万智牌》（Magic: the Gathering， MTG）中的大型语言模型（LLM）作为玩家，实现动态难度调整（DDA）机制。法学硕士作为一项非常有用的技术，已经在各个领域进行了探索。然而，在游戏中使用llm进行DDA的研究，特别是在复杂的回合制游戏中，却非常有限。本文将gpt - 40作为简化版MTG中的两个玩家，其中一个gpt - 40玩家作为常规玩家（LLM-Player）进行游戏，另一个gpt - 40玩家根据当前游戏状态调整策略以平衡难度（LLM-DDA）。我们的LLM-MTG-DDA框架为不同的玩家提供了合适的目标，展示了合理的DDA， LLM-Player的胜率和每轮胜率（不包括平局）都接近50%。该框架为将llm作为DDA机制应用于其他类似游戏提供了洞见。

引用次数: 0

AI-powered virtual streamers and viewer behavior: An image-inspiration-behavior framework 人工智能驱动的虚拟流媒体和观众行为：一个图像-灵感-行为框架

IF 2.8 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2025-07-23 DOI: 10.1016/j.entcom.2025.101000

Ting (Tina) Li , Zhongyuan Zhou , Xianfeng Zhang , Yang Zhou , Si Wen

Today, a new form of live-streaming has emerged: virtual streamers powered by Artificial Intelligence technology, which autonomously perform live-streaming tasks as human streamers do. This form of live-streaming has quickly gained popularity. However, studies in this area are scarce. This study aims to fill this research gap by investigating how virtual AI streamers impact viewers by adopting the image-inspiration-behavior framework, in which the image of virtual AI streamers is described by warmth, competence, and coolness, and behavior is studied as interaction and purchase intentions. The data were collected from 559 participants via a scenario-based survey. The partial least squares – structural equation modeling and artificial neural network are used to analyze the data. It was found that the three image dimensions (warmth, competence, and coolness) influence consumer interaction and purchase intentions through the mediating effect of inspiration. The findings of this study advance previous studies mainly by investigating how virtual AI streamers impact viewer behaviors and offer insights to live-streaming companies in their adoption of virtual AI streamers.

今天，一种新的直播形式出现了：由人工智能技术驱动的虚拟流媒体，它可以像人类流媒体一样自主执行直播任务。这种形式的直播迅速流行起来。然而，这方面的研究很少。本研究旨在填补这一研究空白，通过采用形象-启发-行为框架来研究虚拟AI主播如何影响观众，其中虚拟AI主播的形象被描述为温暖、能力和冷静，行为被研究为互动和购买意愿。数据是通过基于场景的调查从559名参与者中收集的。采用偏最小二乘-结构方程模型和人工神经网络对数据进行分析。研究发现，温暖、能力和冷静三个形象维度通过灵感的中介作用影响消费者互动和购买意愿。这项研究的结果主要通过调查虚拟人工智能流媒体如何影响观众的行为，并为直播公司采用虚拟人工智能流媒体提供见解，从而推进了之前的研究。

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引用次数: 0

Storytelling in mobile games: Cross-cultural analysis of narrative engagement, retention, and monetization 手机游戏中的故事叙述：叙述粘性、留存率和盈利的跨文化分析

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2025-07-23 DOI: 10.1016/j.entcom.2025.100994

JaeJun Lee, Joo-Eun Kang, Soyoun Eom

This study examines storytelling consumption patterns in The Walking Dead: Match3 Tales, a mobile game that integrates a well-known intellectual property into a ludic-focused gameplay experience. Through quantitative analysis of user behavior across 15 countries, we explore how different cultural regions engage with narrative elements in mobile games. The findings reveal that story consumption is highly fragmented, with players dedicating only a small fraction of their session time to storytelling. Regional differences emerge, with Western audiences generally spending more time with narrative content than East Asian players. However, more narrative content consumption does not correlate with higher retention or monetization. Instead, players who consume less story content exhibit higher retention rates and contribute more to in-game revenue. These findings indicate that simply integrating storytelling elements does not automatically lead to higher engagement or monetization, particularly when not supported by the game’s core mechanics and monetization framework. While certain cultural regions may indeed spend more time engaging with narrative features, the broader game structure must effectively integrate those elements to achieve meaningful player retention and revenue gains. Certain player segments in Western markets may allocate more time to story-driven features, yet simply adding narrative content does not ensure better retention or revenue. Instead, effective storytelling in mobile games must work in tandem with the underlying gameplay systems and monetization design.

本研究分析了《行尸走肉：三消故事》的故事叙述消费模式，这是一款将知名知识产权融入以搞笑为重点的游戏体验的手机游戏。通过对15个国家的用户行为进行定量分析，我们探讨了不同文化区域如何影响手机游戏中的叙事元素。调查结果显示，故事消费是高度分散的，玩家只花一小部分时间讲故事。地区差异开始显现，西方玩家通常比东亚玩家花更多时间在叙事内容上。然而，更多的叙事内容消费与更高的留存率或盈利并不相关。相反，较少消费故事内容的玩家呈现出更高的留存率，并为游戏收益做出更多贡献。这些发现表明，简单地整合故事元素并不会自动带来更高的粘性或盈利，尤其是在没有游戏核心机制和盈利框架支持的情况下。虽然某些文化区域确实会花更多时间在叙述功能上，但更广泛的游戏结构必须有效地整合这些元素，以获得有意义的玩家留存率和收益。西方市场的某些玩家群体可能会在故事驱动功能上投入更多时间，但仅仅添加叙事内容并不能确保更高的留存率或收益。相反地，手机游戏中有效的故事叙述必须与潜在的游戏玩法系统和盈利设计相结合。

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引用次数: 0

Leveraging deep reinforcement learning for dynamic NPC behavior and enhanced player experience in unity3d 在unity3d中利用深度强化学习动态NPC行为和增强玩家体验

IF 2.8 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2025-07-23 DOI: 10.1016/j.entcom.2025.101007

Ahmad Affandi Supli, Xu Siqi

With the innovation of information technology and the improvement of computer hardware and software, players’ needs gradually change from pursuing the ultimate visual and auditory feast to the inner performance, gameplay, interactive elements, etc. As an essential part of game content, game AI plays the role of communication and interaction with players. Since the emergence of game AI, it has been paid attention to by game developers. However, it is also a difficult job to make brilliant game AI. The common approaches to implementing game AI are finite state machines and behavior trees. Still, these two approaches require much work to implement flexible game AI and are difficult to maintain later. Therefore, this paper aims to investigate machine learning to train a compliant and flexible game AI. Specifically, this paper adopts a method to train game AI in Unity scenes using machine learning methods such as deep reinforcement learning with the help of the ML-Agents toolkit and Python programming interface. In order to better test the performance of the machine learning method, this study designs a game based on the Unity game engine, which includes a game AI implemented using behavior trees and machine learning. Through the production process and the final implementation results, this paper compares the differences in design ideas and implementation process between using behavior trees and using machine learning to implement game AI, as well as the advantages and disadvantages of each. The purpose of this study is to promote machine learning in the field of game research and achieve higher operational efficiency. Relevant existing principles and guidelines inform the game design process. In addition, the game proposed in this paper can be used as future research to promote machine learning in games to achieve a more efficient, more straightforward design and better player experience. After the game implementation, a quantitative research method is used to measure the players’ immersion in the game and the players’ satisfaction with the designed game AI. The evaluation results showed that most respondents believed that the proposed agents performed well against both human players and inbuilt game agents.

随着信息技术的创新和计算机软硬件的完善，玩家的需求逐渐从追求极致的视觉和听觉盛宴转变为内在的表演、玩法、互动元素等。游戏AI作为游戏内容的重要组成部分，起着与玩家沟通互动的作用。自游戏AI出现以来，一直受到游戏开发者的关注。然而，制作出色的游戏AI也是一项困难的工作。执行游戏AI的常见方法是有限状态机和行为树。尽管如此，这两种方法仍然需要大量工作去执行灵活的游戏AI，并且很难在之后进行维护。因此，本文旨在研究机器学习来训练一个兼容且灵活的游戏AI。具体来说，本文采用了一种在Unity场景中，借助ML-Agents工具包和Python编程接口，利用深度强化学习等机器学习方法来训练游戏AI的方法。为了更好地测试机器学习方法的性能，本研究设计了一个基于Unity游戏引擎的游戏，其中包括一个使用行为树和机器学习实现的游戏AI。本文通过制作过程和最终的实现结果，比较了使用行为树和使用机器学习实现游戏AI在设计思路和实现过程上的差异，以及各自的优缺点。本研究的目的是推动机器学习在游戏研究领域的发展，实现更高的操作效率。相关的现有原则和指导方针会影响游戏设计过程。此外，本文提出的游戏可以作为未来的研究，促进游戏中的机器学习，以实现更高效，更直接的设计和更好的玩家体验。在游戏实施后，采用定量研究的方法来衡量玩家对游戏的沉浸感和玩家对所设计的游戏AI的满意度。评估结果显示，大多数受访者认为所提出的代理在对抗人类玩家和内置游戏代理时都表现良好。

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引用次数: 0

Developing an advanced machine learning model for identifying virtual montages in digital media 开发先进的机器学习模型，用于识别数字媒体中的虚拟蒙太奇

IF 2.4 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS

Entertainment Computing

Pub Date : 2025-07-22 DOI: 10.1016/j.entcom.2025.101002

Yuxuan Liu

Virtual montages are compositions that blend several digital materials to produce a new, visually appealing narrative and are becoming increasingly popular, as a result of the quick development of digital media. Virtual montages have emerged as a potent technique for improving visual storytelling and content presentation across platforms in the digital age. However, the quick expansion of digital content has made advanced methods for effectively recognizing and classifying these montages necessary. This work suggests a novel method for virtual montage identification across a broad range of visual themes, content types, and media resolutions, and resolutions utilizing an Adaptive Flower Pollination Optimized Mutual Information with Naïve Bayes (AFPO-MI-NB) model. The research’s dataset comprises a variety of content from virtual montage detection dataset which enables the model to generalize effectively to data from the real world. To improve the model’s capacity to handle various image and video qualities, pre-processing methods, including data augmentation and pixel value normalization are used. Convolutional neural networks (CNN) are used for feature extraction to capture spatial patterns. The model uses AFPO-MI-NB classification to enhance classification accuracy and computational efficiency. AFPO allows for more adaptable feature weights, MI evaluates the relationship between visual features and the classification task, and NB classifier processes feature matrices for binary classification. The hybrid approach strengthens feature selection through global and local searches, resulting in a model that enhances classification accuracy and improves computational efficiency. According to the experimental data, this model provides a reliable solution for virtual montage identification across a variety of media formats, outperforming current techniques in terms of F1-score of 0.95, recall of 0.92, and precision of 0.97. This work has significant applications in automated digital media analysis, copyright enforcement, and content control.

随着数字媒体的快速发展，虚拟蒙太奇是将几种数字材料混合在一起，产生一种新的、视觉上吸引人的叙事方式的作品，它正变得越来越受欢迎。在数字时代，虚拟蒙太奇已经成为一种有效的技术，可以改善视觉叙事和跨平台的内容呈现。然而，数字内容的快速扩展使得有效识别和分类这些蒙太奇的先进方法成为必要。这项工作提出了一种新的虚拟蒙太奇识别方法，可以跨越广泛的视觉主题、内容类型和媒体分辨率，并利用Naïve贝叶斯（AFPO-MI-NB）模型的自适应授粉优化互信息。本研究的数据集包含来自虚拟蒙太奇检测数据集的各种内容，使模型能够有效地推广到来自现实世界的数据。为了提高模型处理各种图像和视频质量的能力，采用了数据增强和像素值归一化等预处理方法。卷积神经网络（CNN）用于特征提取，以捕获空间模式。该模型采用AFPO-MI-NB分类，提高了分类精度和计算效率。AFPO允许更具适应性的特征权重，MI评估视觉特征与分类任务之间的关系，NB分类器处理特征矩阵进行二值分类。混合方法通过全局和局部搜索加强特征选择，得到的模型提高了分类精度，提高了计算效率。实验数据表明，该模型为各种媒体格式的虚拟蒙太奇识别提供了可靠的解决方案，其f1得分为0.95，召回率为0.92，精度为0.97，优于现有技术。这项工作在自动数字媒体分析、版权执行和内容控制方面具有重要的应用。

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引用次数: 0