Abstract: Game engines generate high dependence of developed games on provided implementation resources. Feature modeling is a technique that captures commonalities and variabilities results of domain analysis to provide a basis for automated configuration of concrete products. This paper presents the Minimal Engine for Digital Games (MEnDiGa), a simplified collection of game assets based on game features capable of building small and casual games regardless of their implementation resources. It presents minimal features in a representative hierarchy of spatial and game elements along with basic behaviors and event support related to game logic features. It also presents modules of code to represent, interpret, and adapt game features to provide the execution of configured games in multiple game platforms. As a proof of concept, a clone of the Doodle Jump game was developed using MEnDiGa assets and compared with original game version. As a result, a new G-factor based approach for game construction is provided, which is able to separate the core of game elements from the implementation itself in an independent, reusable, and large-scale way. PubDate: Tue, 11 Jul 2017 07:38:21 +000
Abstract: Current techniques for the creation and exploration of virtual worlds are largely unable to generate sound natural environments from ecological data and to provide interactive web-based visualizations of such detailed environments. We tackle this challenge and propose a novel framework that (i) explores the advantages of landscape maps and ecological statistical data, translating them to an ecologically sound plant distribution, and (ii) creates a visually convincing 3D representation of the natural environment suitable for its interactive visualization over the web. Our vegetation model improves techniques from procedural ecosystem generation and neutral landscape modeling. It is able to generate diverse ecological sound plant distributions directly from landscape maps with statistical ecological data. Our visualization model integrates existing level of detail and illumination techniques to achieve interactive frame rates and improve realism. We validated with ecology experts the outcome of our framework using two case studies and concluded that it provides convincing interactive visualizations of large natural environments. PubDate: Thu, 18 May 2017 00:00:00 +000
Abstract: Mobile devices are rapidly becoming the new medium of educational and social life for young people, and hence mobile educational games have become an important mechanism for learning. To help school-aged children learn about the fascinating world of plants, we present a mobile educational game called Little Botany, where players can create their own virtual gardens in any location on earth. One unique feature of Little Botany is that the game is built upon real-world data by leveraging data integration mechanism. The gardens created in Little Botany are augmented with real-world location data and real-time weather data. More specifically, Little Botany is using real-time weather data for the garden location to simulate how the weather affects plants growth. Little Botany players can learn to select what crops to plant, maintain their own garden, watch crops to grow, tend the crops on a daily basis, and harvest them. With this game, users can also learn plant structure and three chemical reactions. PubDate: Wed, 22 Mar 2017 00:00:00 +000
Abstract: The visualization of tomato growth can be used in 3D computer games and virtual gardens. Based on the growth theory involving the respiration theory, the photosynthesis, and dry matter partition, a visual system is developed. The tomato growth visual simulation system is light-and-temperature-dependent and shows plausible visual effects in consideration of the continuous growth, texture map, gravity influence, and collision detection. In addition, the virtual tomato plant information, such as the plant height, leaf area index, fruit weight, and dry matter, can be updated and output in real time. PubDate: Sun, 19 Mar 2017 09:38:23 +000
Abstract: A narrative structure is one of the main components to constitute the genre of Massively Multiplayer Online Role-Playing Games (MMORPGs). Meanwhile Real Money Trade (RMT) enables a player to adjust an ex post level of challenge by skipping the narrative structure of a game. However, RMT may concurrently disturb a player who enjoys game following the narrative structure hierarchically. In pursuance of developing the knowledge about the relationship between RMT and the usage of MMORPG, we investigate the role of the strictness of predetermined narrative structure. We present the dual structure of societies to describe a player that arbitrarily decides to reside in a virtual society. Then we adopt the social nominalism to explain how individual motif of playing a game is expanded to the nature of game. Finally, we argue that a game with weakly predetermined narrative structure is more positively associated with RMT volume, since these games arouse a player’s sentiment of fun by relying more on their socially oriented motivation. With empirical evidence from the Korean MMORPGs market, we proved the hypothesis. PubDate: Sun, 19 Feb 2017 00:00:00 +000
Abstract: We propose to use a supervised machine learning technique to track the location of a mobile agent in real time. Hidden Markov Models are used to build artificial intelligence that estimates the unknown position of a mobile target moving in a defined environment. This narrow artificial intelligence performs two distinct tasks. First, it provides real-time estimation of the mobile agent’s position using the forward algorithm. Second, it uses the Baum–Welch algorithm as a statistical learning tool to gain knowledge of the mobile target. Finally, an experimental environment is proposed, namely, a video game that we use to test our artificial intelligence. We present statistical and graphical results to illustrate the efficiency of our method. PubDate: Tue, 14 Feb 2017 00:00:00 +000
Abstract: We propose a dynamic projection mapping system with effective machine-learning and high-speed edge-based object tracking using a single IR camera. The machine-learning techniques are used for precise 3D initial posture estimation from 2D IR images, as a detection process. After the detection, we apply an edge-based tracking process for real-time image projection. In this paper, we implement our proposal and actually achieve dynamic projection mapping. In addition, we evaluate the performance of our proposal through the comparison with a Kinect-based tracking system. PubDate: Sun, 12 Feb 2017 06:55:40 +000
Abstract: The aim of the study is to develop a new instrument to measure engagement in videogame play termed as consumer videogame engagement. The study followed the scale development procedure to develop an instrument to measure the construct of consumer videogame engagement. In this study, we collected the data in two different phases comprising study 1 () and study 2 (). We employed SPSS 22.0 for exploratory factor analysis using study 1 respondents to explore the factors for consumer videogame engagement and reliability analysis. Results of EFA resulted with six-factor solution. We further used SmartPLS 3.0 software on study 2 respondents to further confirm the six-factor solution as reflective measurement model on the first-order level, and three second-order formative constructs on the second-order or higher-order level as formative measurement model. Results of the reflective measurement model and formative measurement model evidenced that consumer videogame engagement has strong psychometric properties and is a valid instrument to measure engagement in videogame play. Results also confirmed that consumer videogame engagement is a multidimensional construct as well as a reflective-formative construct. The study is unique in its investigation as it develops an instrument to measure engagement in videogame play which comprises the cognitive, affective, and behavioral dimensions. PubDate: Tue, 31 Jan 2017 14:01:41 +000
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