Game Scene Research Articles

Application of Virtual Reality Technology and 3D Technology in Game Animation Production

With the increasing pressure of modern young people, they begin to look for various ways to relax. Among them, game animation makes them immersive and has a low experience cost, which is one of the best ways to relax. Therefore, animation games have been welcomed by more and more young people. However, virtual reality technology and 3D technology have played a huge role in the production of game animation. Therefore, this paper aimed to study how virtual reality technology and 3D technology were applied in game animation production and put forward their advantages. This paper also proposed a method based on virtual reality technology and 3D technology and analyzed the production of game animation. The experimental results of this paper showed that in the survey results of the popularity of the A game, only 56 experiencers thought its effect was good, accounting for 18%. There were 145 experiencers who disliked the A game because they thought the A game was very boring and the game scene was very simple. In the survey results of the popularity of the B game, 222 experiencers liked this game, accounting for 71.6%, and 43 experiencers did not like the B game because they thought the 3D effect of the B game would make them dizzy and uncomfortable. It can be seen that the integration of virtual reality technology and 3D technology into game animation production is more popular, so the research in this paper is meaningful.

Towards Sinophone Game Studies

The editor’s introduction discusses progress so far and possible future directions in the emerging field of Sinophone game studies, taken to mean the study of games – in this case, specifically video, computer, digital, or electronic games – in a Sinophone context, including mainland China and the broader Chinese-speaking world. Recent industry figures and news stories related to video gaming in the People’s Republic of China (PRC) paint a picture of continued expansion and growing global ambitions, albeit tempered by the regular introduction of fresh government regulations surrounding game content, gaming permissions for under-18s, game streaming, and game license approval. The eleven contributions to this issue, however, reflect the diversity of possible approaches to the study of Sinophone gaming, focusing not just on the often-conflicting politics and economics of the PRC games industry, but also exploring Taiwan’s flourishing indie game scene, political uses of games in Hong Kong, game-based representations of online and offline realities, issues in the transnational adaptation and localisation of games, and more besides. Sinophone game studies is a highly fruitful area of academic research that is intrinsically inter- and cross-disciplinary in nature and well placed to respond to some of the most pressing issues of our time, whether they be international conflict, ecological crisis, identity politics, minority rights, or even the development of disparate virtual worlds into a cross-platform ‘metaverse’ in which many of us may one day live our lives.

ARTISTIC REFLECTIONS IN THE GLOBAL SENSATIONAL SQUID GAME SERIES

Squid Game, Netflix platformunda yer alan dokuz bölümlük Güney Kore yapımı bir dizidir. Gerilim-dram türünün bir örneği olan dizide oyun sahnelerinde çocuksu masum temalar gösterilmesine rağmen gerçekte çokça kan ve şiddet unsuru yer almaktadır. Söz konusu dizide, birçok sahnede bilinçaltına yönelik etkileme yöntemleri uygulanmaktadır. Bilinçaltındaki bilgiler çağrışımlar yoluyla izleyici hem sorgulatıp hem de merak ettirmektedir. 
 Dijital platformların sıklıkla kullanıldığı günümüzde Squid Game dizisi; gerek sosyal medya paylaşım ve tartışmaları gerek konusu gerek içerdiği şiddet sahneleri ve gerekse küçük yaşta izleyiciler tarafından da izlenmesi gibi unsurlar nedeniyle dünya çapında adından söz ettirerek gündemde kalmayı başarmaktadır. Son dönemlerdeki popüler dizilerden olan Squid Game şiddet sahneleriyle çok tartışılsa da, bazı bölümlerde sanatsal göndermeler de bulunmaktadır. Rene Magritte, Van Gogh, Picasso, Claude Monet, Maurits Cornelis Escher, Friedrich Nietzscheve ve Jacaques Lacan gibi sanatçı ve düşünürlerin eserlerinden izler barındıran dizi bu bakımdan incelenmiştir. Bu amaçla araştırmada dizide yer verilen ve kimi sahnelerde kullanılan sanatsal yansımalar ve bu yansımalarla ilgili sanatçı eserlerine yapılan göndermeler ele alınmıştır.

Quantum decision making in automatic driving

The behavior intention estimation and interaction between Autonomous Vehicles (AV) and human traffic participants are the key problems in Automatic Driving System (ADS). When the classical decision theory studies implicitly assume that the behavior of human traffic participants is completely rational. However, according to the booming quantum decision theory in recent years and actual traffic cases, traffic behaviors and other human behaviors are often irrational and violate the assumptions of classical cognitive and decision theory. This paper explores the decision-making problem in the two-car game scene based on quantum decision theory and compares it with the current mainstream method of studying irrational behavior-Cumulative Prospect Theory (CPT) model. The comparative analysis proved that the Quantum Game Theory (QGT) model can explain the separation effect which the classical probability model can’t reveal, and it has more advantages than CPT model in dealing with game scene decision-making. When two cars interact with each other, the QGT model can consider the interests of both sides from the perspective of the other car. Compared with the classical probability model and CPT model, the QGT is more realistic in the behavior decision-making of ADS.

Eye of the Beholder: Improved Relation Generalization for Text-Based Reinforcement Learning Agents

Text-based games (TBGs) have become a popular proving ground for the demonstration of learning-based agents that make decisions in quasi real-world settings. The crux of the problem for a reinforcement learning agent in such TBGs is identifying the objects in the world, and those objects' relations with that world. While the recent use of text-based resources for increasing an agent's knowledge and improving its generalization have shown promise, we posit in this paper that there is much yet to be learned from visual representations of these same worlds. Specifically, we propose to retrieve images that represent specific instances of text observations from the world and train our agents on such images. This improves the agent's overall understanding of the game scene and objects' relationships to the world around them, and the variety of visual representations on offer allow the agent to generate a better generalization of a relationship. We show that incorporating such images improves the performance of agents in various TBG settings.

Dynamic Motion Matching: Design and Implementation of a Context-Aware Animation System for Games

Despite modern game systems adopting motion matching to retrieve an appropriate short motion clip from a database in real-time, existing methods struggle to support complex gaming scenes due to their inability to adapt live the motion retrieval based on the context. This paper presents the design and implementation of a context-aware character animation system, synthesizing realistic animations suitable for complex game scenes from a large-scale motion database. This system, called dynamic motion matching (DyMM), enables geometry and objects aware motion synthesis by introducing a two-phase context computation: an offline subspace decomposition of motion clips for creating a set of retrieval sub-spaces tailored to specific contexts and a subspace ensemble matching to compare relevant sub-features to determine the most appropriate motion clip. We also show the system architecture and implementation details applicable to a production-grade game engine. We verified the effectiveness of our method with industry-level motion data captured by professional game artists for multiple configurations and character controllers. The results of this study show that, by finding motion clips that comply well with the scene context, one can leverage large motion capture datasets to create practical systems that generate believable and controllable animations for games.

Live Multiattribute Data Mining and Penalty Decision-Making in Basketball Games Based on the Apriori Algorithm.

The Apriori algorithm is used to conduct an in-depth analysis and research on the relationship between data mining and penalty decision of multiattribute data in the basketball game scene. The technical and tactical features are analyzed using an improved Apriori algorithm for association rule analysis of basketball game data. The algorithm generates association rules based on mining the set of frequent items among basketball technical actions. The improved algorithm can mine the technical moves that are more connected in the game data, and the analysis results are highly instructive. The technical and tactical directed analysis is divided into two parts: technical and tactical directed action analysis and technical and tactical directed cooperation analysis. The key action analysis uses Markov process-based data mining algorithm to analyze the basketball game data for key score transfer steps and key score loss transfer steps. The algorithm can find the key actions of scoring and key actions of conceding points in the game process, and the analysis results can guide basketball training and games, which has high practical value. Using the collated game data as the independent variable and the number of games won and lost as the dependent variable, logistic regression analysis is applied to derive the characteristics that affect winning. Again, the decision tree algorithm is used to select the significant features that affect winning and to make predictions of team performance. Finally, the technical statistics of the main players in the last three seasons are selected, and the association rule algorithm is applied to derive the degree of influence of player performance on the outcome of the game.

Investigating the Performance of Various Deep Neural Networks-based Approaches Designed to Identify Game Events in Gameplay Footage

Video games, in addition to representing an extremely relevant field of entertainment and market, have been widely used as a case study in artificial intelligence for representing a problem with a high degree of complexity. In such studies, the investigation of approaches that endow player agents with the ability to retrieve relevant information from game scenes stands out, since such information can be very useful to improve their learning ability. This work proposes and analyses new deep learning-based models to identify game events occurring in Super Mario Bros gameplay footage. The architecture of each model is composed of a feature extractor convolutional neural network (CNN) and a classifier neural network (NN). The extracting CNN aims to produce a feature-based representation for game scenes and submit it to the classifier, so that the latter can identify the game event present in each scene. The models differ from each other according to the following elements: the type of the CNN; the type of the NN classifier; and the type of the game scene representation at the CNN input, being either single frames, or chunks, which are n-sequential frames (in this paper 6 frames were used per chunk) grouped into a single input. The main contribution of this article is to demonstrate the greater performance reached by the models which combines the chunk representation for the game scenes with the resources of the classifier recurrent neural networks (RNN).

Controllable automatic generation of non‐player characters in 3D anime style

AbstractGame creators always use prefabricated models as non‐player characters (NPCs) to create an atmosphere for game scenes. However, players are likely to see different NPCs with the same 3D models because creators usually cannot prepare a high number of NPC models for big game scenes. In this article, we present an anime‐like character customization system, where each customizing parameter can adjust the shape or color for the corresponding part of the character model. Based on this system, we propose an improved approach for generating a rich variety of 3D anime‐like NPCs including body models and clothing items in different styles. We introduce a neural network to control the facial appearances, Gaussian mixture models to control the colors of hair and clothes, and a Bayesian network to control the outfits of clothing items. We demostrate that the proposed approach can maintain the variety and stability of the generated characters.

FaceEngage: Robust Estimation of Gameplay Engagement from User-Contributed (YouTube) Videos

Measuring user engagement in interactive tasks can facilitate numerous applications toward optimizing user experience, ranging from eLearning to gaming. However, a significant challenge is the lack of non-contact engagement estimation methods that are robust in unconstrained environments. We present FaceEngage, a non-intrusive engagement estimator leveraging user facial recordings during actual gameplay in naturalistic conditions. Our contributions are three-fold. First, we show the potential of using front-facing videos as training data to build the engagement estimator. We compile FaceEngage Dataset with over 700 picture-in-picture, realisitic, and user-contributed YouTube gaming videos (i.e., with both full-screen game scenes and time-synchronized user facial recordings in subwindows). Second, we develop FaceEngage system, that captures relevant gamer facial features from front-facing recordings to infer task engagement. We implement two FaceEngage pipelines: an estimator trained on user facial motion features inspired by prior psychological works, and a deep learning-enabled estimator. Lastly, we conduct extensive experiments and conclude: (i) certain user facial motion cues (e.g., blink rates, head movements) are engagement-indicative; (ii) our deep learning-enabled FaceEngage pipeline can automatically extract more informative features, outperforming the facial motion feature-based pipeline; (iii) FaceEngage is robust to various video lengths, users/game genres and interpretable. Despite the challenging nature of realistic videos, FaceEngage attains the accuracy of 83.8 percent and leave-one-user-out precision of 79.9 percent, both of which are superior to our face motion-based model.

Real-Time Locomotion on Soft Grounds With Dynamic Footprints

When we move on snow, sand, or mud, the ground deforms under our feet, immediately affecting our gait. We propose a physically based model for computing such interactions in real time, from only the kinematic motion of a virtual character. The force applied by each foot on the ground during contact is estimated from the weight of the character, its current balance, the foot speed at the time of contact, and the nature of the ground. We rely on a standard stress-strain relationship to compute the dynamic deformation of the soil under this force, where the amount of compression and lateral displacement of material are, respectively, parameterized by the soil’s Young modulus and Poisson ratio. The resulting footprint is efficiently applied to the terrain through procedural deformations of refined terrain patches, while the addition of a simple controller on top of a kinematic character enables capturing the effect of ground deformation on the character’s gait. As our results show, the resulting footprints greatly improve visual realism, while ground compression results in consistent changes in the character’s motion. Readily applicable to any locomotion gait and soft soil material, our real-time model is ideal for enhancing the visual realism of outdoor scenes in video games and virtual reality applications.

Procedural Video Game Scene Generation by Genetic and Neutrosophic WASPAS Algorithms

The demand for automated game development assistance tools can be fulfilled by computational creativity algorithms. The procedural generation is one of the topics for creative content development. The main procedural generation challenge for game level layout is how to create a diverse set of levels that could match a human-crafted game scene. Our game scene layouts are created randomly and then sculpted using a genetic algorithm. To address the issue of fitness calculation with conflicting criteria, we use weighted aggregated sum product assessment (WASPAS) in a single-valued neutrosophic set environment (SVNS) that models the indeterminacy with truth, intermediacy, and falsehood memberships. Results are presented as an encoded game object grid where each game object type has a specific function. The algorithm creates a diverse set of game scene layouts by combining game rules validation and aesthetic principles. It successfully creates functional aesthetic patterns without specifically defining the shapes of the combination of games’ objects.

The implementation and evaluation of the field of view in 3D PC game

This research developed a 3D third-person game, made open and closed scenes, through experiments to investigate the field of view suitable for different scenes. Playing 3D games can sometimes cause 3D discomfort or motion sickness. There are many people who have this kind of 3D discomfort. In the research on this issue, the authenticity of the game or the physiological impact of the observer was discussed in detail; however, the impact of the design of the game itself was less discussed. The field of view in the game scene is likely to cause motion sickness. This experimental method uses the adjustment method in psychophysics to test whether the player is comfortable with different scenes. According to the test of different scenarios, the average and standard deviation of the most comfortable visual field are obtained. The viewing angles of different scenes are significantly different, and the best viewing angle of a closed scene is larger than that of an open scene.

Development of Surface EMG Game Control Interface for Persons with Upper Limb Functional Impairments

In recent years, surface Electromyography (sEMG) signals have been effectively applied in various fields such as control interfaces, prosthetics, and rehabilitation. We propose a neck rotation estimation from EMG and apply the signal estimate as a game control interface that can be used by people with disabilities or patients with functional impairment of the upper limb. This paper utilizes an equation estimation and a machine learning model to translate the signals into corresponding neck rotations. For testing, we designed two custom-made game scenes, a dynamic 1D object interception and a 2D maze scenery, in Unity 3D to be controlled by sEMG signal in real-time. Twenty-two (22) test subjects (mean age 27.95, std 13.24) participated in the experiment to verify the usability of the interface. From object interception, subjects reported stable control inferred from intercepted objects more than 73% accurately. In a 2D maze, a comparison of male and female subjects reported a completion time of 98.84 s. ± 50.2 and 112.75 s. ± 44.2, respectively, without a significant difference in the mean of the one-way ANOVA (p = 0.519). The results confirmed the usefulness of neck sEMG of sternocleidomastoid (SCM) as a control interface with little or no calibration required. Control models using equations indicate intuitive direction and speed control, while machine learning schemes offer a more stable directional control. Control interfaces can be applied in several areas that involve neck activities, e.g., robot control and rehabilitation, as well as game interfaces, to enable entertainment for people with disabilities.

Searching in clutter: Visual behavior and performance of expert action video game players

Searching for targets among distractors in visual scenes can be more difficult due to the presence of clutter. However, studies in various domains have shown differentiated effects according to the expertise of the searcher. The present study extended these findings to the domain of action video games expertise. 58 participants, split in 2 groups (action video game players and non-action video game players) searched for targets in visual scenes under two clutter conditions (uncluttered and high clutter). Reaction times and accuracy served as measures of performance, and the visual behavior was assessed using the number and duration of eye fixations. Our findings suggest that visual clutter has a negative influence on performance and alters the visual behavior during visual search in action video game scenes. Our results also suggest that expert action video game players might use different visual strategies to cope with clutter, leading however to no performance benefits.

Improving Deep Object Detection Algorithms for Game Scenes

The advancement and popularity of computer games make game scene analysis one of the most interesting research topics in the computer vision society. Among the various computer vision techniques, we employ object detection algorithms for the analysis, since they can both recognize and localize objects in a scene. However, applying the existing object detection algorithms for analyzing game scenes does not guarantee a desired performance, since the algorithms are trained using datasets collected from the real world. In order to achieve a desired performance for analyzing game scenes, we built a dataset by collecting game scenes and retrained the object detection algorithms pre-trained with the datasets from the real world. We selected five object detection algorithms, namely YOLOv3, Faster R-CNN, SSD, FPN and EfficientDet, and eight games from various game genres including first-person shooting, role-playing, sports, and driving. PascalVOC and MS COCO were employed for the pre-training of the object detection algorithms. We proved the improvement in the performance that comes from our strategy in two aspects: recognition and localization. The improvement in recognition performance was measured using mean average precision (mAP) and the improvement in localization using intersection over union (IoU).

An Algorithm of Scene Information Collection in General Football Matches Based on Web Documents

In order to obtain the scene information of the ordinary football game more comprehensively, an algorithm of collecting the scene information of the ordinary football game based on web documents is proposed. The commonly used T-graph web crawler model is used to collect the sample nodes of a specific topic in the football game scene information and then collect the edge document information of the football game scene information topic after the crawling stage of the web crawler. Using the feature item extraction algorithm of semantic analysis, according to the similarity of the feature items, the feature items of the football game scene information are extracted to form a web document. By constructing a complex network and introducing the local contribution and overlap coefficient of the community discovery feature selection algorithm, the features of the web document are selected to realize the collection of football game scene information. Experimental results show that the algorithm has high topic collection capabilities and low computational cost, the average accuracy of equilibrium is always around 98%, and it has strong quantification capabilities for web crawlers and communities.

İki Boyutlu Video Oyunlarında Sinir Stili Aktarımı Kullanarak Otomatik Oyun Mekaniği ve Estetiği Üretimi

Video game research is an ever-changing and dynamic area where sophisticated methods and algorithms are being developed. Procedural content generation (PCG), which aims to merge user-generated assets with algorithms to automate and improve video game content, has been the core of this sophistication. However, the outcomes are primarily reflected in game aesthetics, not in the game mechanics and gameplay. In this study, we introduce the “game scene as a canvas” concept where simple prototype game development pipelines, that can convert a 2D game-level image into a game development environment with ready-to-use colliders and artistically different styles that enhance the game aesthetics, are introduced. To do so, edge-based and color-based features of the input game level image are extracted using the Canny edge detector, Simple Linear Iterative Clustering, and Felzenszwalb segmentation. The Unity game engine is then used to generate colliders based on the provided edge and color features where the game level is style transferred with spatial control. Results of different neural style transfer algorithms are presented on benchmark games such as Super Mario and Kid Icarus. Results show that this study can become a promising tool to simplify 2D video game development, focusing on game mechanics and aesthetics.

Multi-modal physiological signals based fear of heights analysis in virtual reality scenes

Fear of heights (FoH) analysis and its association to physiological signals can better help understand people’s emotion and quantify human’s behavior, which have been found important in many applications, such as disease analysis, affective computing, etc. Existing studies are mainly on how to alleviate FoH while little literature on FoH analysis has been reported in the past. In this paper, we present the studies of correlation on FoH to multi-modal physiological signals in the virtual reality (VR). To stimulate the FoH to participants, 4 types of VR scenarios that consist of the virtual scene of the VR game “Richie’s plank experience” and the realistic stimulus of hitting by basketball are adopted in the experiment. The synchronized eye movement (EMO), pupil, and electrocardiogram (ECG) of 17 healthy subjects with an even mix of men and women are recorded for FoH analysis. The observations on the FoH analysis carried out in the paper are two-fold: (1) The recognition ability of multi-modal physiological signals for HoF has been evaluated using ReliefF feature selection algorithm. The results show that pupil feature based model generally achieves the best classification performance for FoH. Multiple features consisted of pupil diameter, power spectral density (PSD) of EMO, pupil, ECG, and mean value of EMO can effectively quantify the variability. (2) The FoH analysis model built on the correlation analysis algorithms combined with multi-modal feature-level fusion and strategy-level fusion methods can effectively overcome the drawbacks of conventional statistical models.

A Re-presentation of the Chinese Traditional Art by the VR Technology in the Digital Age: Taking Mogao Grottoes in Dunhuang as an Example

As President Xi Jinping pointed out, “Throughout the history of world civilization, mankind has experienced the agricultural revolution, the industrial revolution and the information revolution.” With the rapid development of the information technology, we are living in a new era of digitization with the digital technology in rapid development, our way of life is being reconstructed by the Internet, and we are being more attracted by the spread of network information culture. In recent years, virtual reality technology has been deeply infiltrated into our lives, and this technology integrates the development results of the computer graphics technology, the computer simulation technology, the artificial intelligence, the sensing technology, the display technology, the network parallel processing and other technologies. The world is in accelerating digitization, so is the art world, with the emergence of the digital technologies highly associated with computers. Nowadays, the virtual reality technology has been applied in many literary and artistic fields, such as the VR immersion experience in games, the VR live game scenes, the VR films and the VR museums, and the emergence of the VR technology has given artists new artistic thinking and creative inspiration. For Chinese traditional art is an important part of the history of Chinese art development, we should vigorously protect and carry forward the traditional art, so as to avoid the disappearance of the traditional art. For this reason, we must conform to the trend of the times, change the old ideas, take advantage of the digital technology and the virtual reality VR, and keep pace with the times. The digital technology shouldn’t be excluded from representing the traditional art as a new development medium and method. Taking the Chinese traditional frescoes of Mogao Grottoes in Dunhuang as an example, this paper tries to discuss how the VR technology is used to digitally re-present the Chinese traditional art for communication.