Entertainment Computing最新文献

This paper introduces a novel software tool developed to serve as an editor for the manual construction of decision trees, characterized by their generic nature, flexibility, and adaptability across a wide range of applications and game development scenarios. The editor enables straightforward definition and modification of decision tree elements and data, dynamically updating to meet changing needs and contexts. A key feature of this tool is its capability to export decision trees in a standardized interchange format, enhancing interoperability by allowing seamless integration with other computational platforms, including game engines. We demonstrate the utility and versatility of our editor with three distinct and comprehensive use cases, highlighting its potential as a significant contribution to interactive technology. The tool facilitates the development of decision trees, enhancing informed decision-making and strategic planning, and supports personalized learning to improve engagement and outcomes.

This work introduces “Cancer: Now What?”, an innovative serious game designed for healthcare training with unlimited, comprehensive clinical scenarios. Focused on the diagnosis of breast cancer and other benign findings, the game is engineered to enhance the diagnostic skills of healthcare professionals by immersing them in a variety of diagnostic challenges related to clinical reasoning practice. It features AI-driven morphing to dynamically portray characters’ emotional responses, deepening player engagement and emotional connection. Despite some punctual challenges with visual artifacts in the morphing animations, the integration of real-life clinical reasoning with computational techniques highlights the game’s potential to advance clinical reasoning practice. This collaboration between game architects and medical experts highlights the substantial contributions of serious games to medical education, elevating them beyond mere entertainment to become essential educational tools.

With the continuous development of digital entertainment technology and sensing equipment, interactive sports game experience is becoming more and more important in physical training systems. The purpose of this study is to explore the application potential of interactive sports game experience based on digital entertainment technology and sensing devices in physical training systems. This paper expounds the problems existing in traditional physical training, including boredom and lack of interest. The application of digital entertainment technology and sensing equipment in the field of games and their potential advantages in physical training are analyzed. Combining game design principle and sports training theory, a series of interactive sports game scenes and corresponding movements are designed. By comparing with traditional physical training methods, we found that interactive sports game experience based on digital entertainment technology and sensing equipment has obvious advantages in improving the accuracy of sports actions and enhancing the participation in sports. Digital entertainment + sports game experience can stimulate the interest and motivation of individuals, improve the effect of physical training, and bring new opportunities for development in the field of physical training.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder, characterised by deficits of social communication and social interaction, along with restricted and repetitive patterns in behaviours, activities and interests. People diagnosed with ASD may need lifetime treatment for social inclusion and control of stereotypical behaviour, on which art therapy has played an important role. Dance Movement Therapy (DMT) has been applied with technology for interventions in social and motor rehabilitation. It has helped people with ASD to integrate in society and develop motor skills, though there are few studies that focus on their artistic expression through the dance and free movements. This review spans the interventions of DMT in technology for people with autism and other neurodevelopmental disorders, during the last six years, with a query on the technologies and application cases. The purpose of this study is to review more than 50 studies and discuss the most relevant technological aspects classified according to the application theme. Our general contribution is to give an overview of the current state of the art and provide guidelines for future research on DMT applications for people with ASD, orientated in the development of technologies that combine dance and visual arts for therapy uses. This research highlights how technology can enhance DMT by creating immersive and interactive environments that facilitate better engagement and expression for individuals with ASD. The study emphasises the importance of multidisciplinary approaches, involving artists, designers, and therapists, to develop richer, more inclusive therapeutic experiences. The findings suggest that technology does not need to be advanced or expensive to be effective; simplicity and user-friendliness are key to successful interventions.

Serious Games have been shown to have many uses, such as for learning and cultural engagement. Furthermore, research has shown that some types of game experiences can have significant social benefits, such as a study by Wang, Taylor and Sun, which showed that playing cooperative video games can improve family satisfaction and closeness. In this article, we present the design and evaluation of Alice Dalí AR (2022), a locative augmented-reality smartphone game designed as a cultural experience for families to engage with art, music and storytelling. Alice Dalí AR features 12 illustrations produced by Dalí in 1969 for the iconic story Alice’s Adventures in Wonderland by Lewis Carrol. We applied a multisensory design methodology based on synesthesia, where art shapes and color palettes from Dalí’s paintings were “transposed” to music genre and music language. The play experience involves using a radar to find AR music art encounters through which a story of Wonderland emerges. The design offers a cultural and social play experience that can help strengthen family connections and knowledge exchange across generations, and at the same time encourage players to spend time outside in healthy walking activities. We present the results of a user study, which shows evidence of cultural engagement and increased intergenerational emotional bonding. The Alice Dalí AR app is available from the Google and Apple app stores.¹

The acquisition of computational thinking and coding skills is of special significance in helping adult learners keep pace with a new context where those skills are required for many parts of the workforce. However, there is an agreement in the scientific literature that important challenges exist, such as keeping student engagement and the requirement of developing problem-solving skills, and not just learning the code syntax. The inclusion of digital Game-Based Learning (GBL) has shown great potential. To better understand how it can be helpful to adult learners in STEM degrees, a study was conducted on the application of two very popular commercial video games in different introductory programming courses at an online university, during the introduction of basic programming topics (CS1). The methods combined a descriptive qualitative and a quantitative approach, using a reflective journals and questionnaires, which helped students consider and express their experiences, how they interacted with the games, how the games helped them better understand the topics, and realize their personal progress and potential. Results showed that the use of these games as educational resources had a positive impact in their engagement and sense of self-efficacy, but only if some important instructional considerations are taken into account.

Computer Graphics (CG) advancements have allowed the creation of more realistic Virtual Humans (VH) through modern techniques for animating the VH body and face, thereby affecting perception. From traditional methods, including blend shapes, to driven animations using facial and body tracking, these advancements can potentially enhance the perception of comfort and realism in relation to VHs. Previously, Psychology studied facial movements in humans, with some works separating expressions into macro and micro expressions. Also, some previous CG studies have analyzed how macro and micro expressions are perceived, replicating psychology studies in VHs, encompassing studies with realistic and cartoon VHs, and exploring different VH technologies. However, instead of using facial tracking animation methods, these previous studies animated the VHs using blendshapes interpolation. To understand how the facial tracking technique alters the perception of VHs, this paper extends the study to macro and micro expressions, employing two datasets to transfer real facial expressions to VHs and analyze how their expressions are perceived. Our findings suggest that transferring facial expressions from real actors to VHs significantly diminishes the accuracy of emotion perception compared to VH facial animations created by artists.

Using new media to enhance the visual and creative quality of cinema and television works may also give a new means for the general public to create and distribute these works, improving the ease of film and television production and distribution. This paper studies the production and dissemination paths of new media film and television content based on 5G technology and then uses neural networks to evaluate the effectiveness of the method and complete the following work: 1) To begin, we’ll discuss the current state of new media film and television production and distribution research both domestically and internationally. 2) The development approach of film and television production and dissemination under the new media environment is proposed. The basic principles of BPNN and PSO are introduced, and then the PSO-BP model is constructed. 3) Collect the experimental data set and then select the optimal parameters of the model through experiments. The experimental results obtained by inputting the test data into the model are compared with the actual values, and it is found that the error between the estimated value of the model and the exact value is tiny.

Real-time strategy (RTS) games present a unique challenge for AI agents due to the combination of several fundamental AI problems. While Deep Reinforcement Learning (DRL) has shown promise in the development of autonomous agents for the genre, existing architectures often struggle with games featuring maps of varying dimensions. This limitation hinders the agent’s ability to generalize its learned strategies across different scenarios. This paper proposes a novel approach that overcomes this problem by incorporating Spatial Pyramid Pooling (SPP) within a DRL framework. We leverage the GridNet architecture’s encoder–decoder structure and integrate an SPP layer into the critic network of the Proximal Policy Optimization (PPO) algorithm. This SPP layer dynamically generates a standardized representation of the game state, regardless of the initial observation size. This allows the agent to effectively adapt its decision-making process to any map configuration. Our evaluations demonstrate that the proposed method significantly enhances the model’s flexibility and efficiency in training agents for various RTS game scenarios, albeit with some discernible limitations when applied to very small maps. This approach paves the way for more robust and adaptable AI agents capable of excelling in sequential decision problems with variable-size observations.