Computer Science, Information Technology and Telecommunications

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Browsing Computer Science, Information Technology and Telecommunications by Subject "Augmented reality"

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    Enhanced device-based 3d object manipulation technique for handheld mobile augmented reality
    (Universiti Teknologi Malaysia, 2019) Goh, Eg Su
    3D object manipulation is one of the most important tasks for handheld mobile Augmented Reality (AR) towards its practical potential, especially for realworld assembly support. In this context, techniques used to manipulate 3D object is an important research area. Therefore, this study developed an improved devicebased interaction technique within handheld mobile AR interfaces to solve the largerange 3D object rotation problem as well as issues related to 3D object position and orientation deviations in manipulating 3D object. The research firstly enhanced the existing device-based 3D object rotation technique with an innovative control structure that utilizes the handheld mobile device tilting and skewing amplitudes to determine the rotation axes and directions of the 3D object. Whenever the device is tilted or skewed exceeding the threshold values of the amplitudes, the 3D object rotation will start continuously with a pre-defined angular speed per second to prevent over-rotation of the handheld mobile device. This over-rotation is a common occurrence when using the existing technique to perform large-range 3D object rotations. The problem of over-rotation of the handheld mobile device needs to be solved since it causes a 3D object registration error and a 3D object display issue where the 3D object does not appear consistent within the user’s range of view. Secondly, restructuring the existing device-based 3D object manipulation technique was done by separating the degrees of freedom (DOF) of the 3D object translation and rotation to prevent the 3D object position and orientation deviations caused by the DOF integration that utilizes the same control structure for both tasks. Next, an improved device-based interaction technique, with better performance on task completion time for 3D object rotation unilaterally and 3D object manipulation comprehensively within handheld mobile AR interfaces was developed. A pilot test was carried out before other main tests to determine several pre-defined values designed in the control structure of the proposed 3D object rotation technique. A series of 3D object rotation and manipulation tasks was designed and developed as separate experimental tasks to benchmark both the proposed 3D object rotation and manipulation techniques with existing ones on task completion time (s). Two different groups of participants aged 19-24 years old were selected for both experiments, with each group consisting sixteen participants. Each participant had to complete twelve trials, which came to a total 192 trials per experiment for all the participants. Repeated measure analysis was used to analyze the data. The results obtained have statistically proven that the developed 3D object rotation technique markedly outpaced existing technique with significant shorter task completion times of 2.04s shorter on easy tasks and 3.09s shorter on hard tasks after comparing the mean times upon all successful trials. On the other hand, for the failed trials, the 3D object rotation technique was 4.99% more accurate on easy tasks and 1.78% more accurate on hard tasks in comparison to the existing technique. Similar results were also extended to 3D object manipulation tasks with an overall 9.529s significant shorter task completion time of the proposed manipulation technique as compared to the existing technique. Based on the findings, an improved device-based interaction technique has been successfully developed to address the insufficient functionalities of the current technique.
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    Speech-enabled augmented reality to enhance learning experience for the non-native english speaking children
    (Universiti Teknologi Malaysia, 2020) Che Dalim, Che Samihah
    The fourth industrial revolution has not only changed the face of the industry but it has also transformed the design of the education system, whereby it has also impacted education to children who are now an essential group of technology users. Traditional learning methods are less interactive, in which most digital learning applications for children have been developed without the involvement of children in the design process, and hence causing them not to meet the development and priorities of children and consequently making the learning experience less effective. Hence, this research explores the nonwhile learning English through a combination of augmented reality (AR) and speech recognition by involving them in the design process using informant design methods. An AR interface called TeachAR, which can be interacted with or without speech input was developed to investigate the effectiveness of the combination of AR and speech recognition in learning English terms for colours, three-dimensional (3D) shapes, and English words for spatial relationships. This research began with an observational test and interview sessions involving children, as well as a literature review to identify the design requirements. The findings from this activity are subsequently translated into several forms of coded prototypes, in which the usability of these prototypes, as well as the suitability of the assessment method, was tested on a group of children in a pilot test. Test results indicate that the design of the TeachAR interface is capable of creating realistic spatial illusions. Simultaneously, the children prefer to play and gain more new knowledge by using the AR interface as compared to the non-AR. Subsequently, a final assessment with 120 preschool children was conducted using pre- and posttests, surveys, video observations, and interview methods to assess the children's performance in terms of knowledge gain, enjoyment, task completion time, and ease of use. Eight different groups consisted of children between the age of four and sixyear- old were formed: four tested AR interfaces and four tested non-AR interfaces. Each participant must perform an assignment using one of the eight interfaces. Data were then analysed using a rank-based non-parametric test. The findings of the study statistically prove that the participants' knowledge acquisition increased significantly through the integrated AR and speech recognition interface, with shorter and significant task completion time for the group using the AR interface. Although participants admitted that the use of speech recognition was not easy, participants who used the AR interface, whether with voice recognition or without it, recorded higher enjoyment scores as compared to the participants who used the non-AR interface. Overall, the results of the study illustrate that children's involvement in the design process can generate practical applications as teaching tools. The integration of AR and speech recognition technology increases engagement in learning and enhances knowledge gain. Real-time interaction enhances children's enjoyment in exploring further learning.
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    Usability framework for mobile augmented reality language learning
    (Universiti Teknologi Malaysia, 2022) Lim, Kok Cheng
    After several decades since its introduction, the existing ISO9241-11 usability framework is still vastly used in Mobile Augmented Reality (MAR) language learning. The existing framework is generic and can be applied to diverse emerging technologies such as electronic and mobile learning. However, technologies like MAR have interaction properties that are significantly unique and require different usability processes. Hence, implementing the existing framework on MAR can lead to non-optimized, inefficient, and ineffective outcomes. Furthermore, state-of-the-art analysis models such as machine learning are not apparent in MAR usability studies, despite evidence of positive outcomes in other learning technologies. In recent MAR learning studies, machine learning benefits such as problem identification and prioritization were non-existent. These setbacks could slow down the advancement of MAR language learning, which mainly aims to improve language proficiency among MAR users, especially in English communication. Therefore, this research proposed the Usability Framework for MAR (UFMAR) that addressed the currently identified research problems and gaps in language learning. UFMAR introduced an improved data collection method called Individual Interaction Clustering-based Usability Measuring Instrument (IICUMI), followed by a machine learning-driven analysis model called Clustering-based Usability Prioritization Analysis (CUPA) and a prioritization quantifier called Usability Clustering Prioritization Model (UCPM). UFMAR showed empirical evidence of significantly improving usability in MAR, capitalizing on its unique interaction properties. UFMAR enhanced the existing framework with new abilities to systematically identify and prioritize MAR usability issues. Through the experimental results of UFMAR, it was found that the IICUMI method was 50% more effective, while CUPA and UCPM were 57% more effective than the existing framework. The outcome through UFMAR also produced 86% accuracy in analysis results and was 79% more efficient in framework implementation. UFMAR was validated through three cycles of the experimental processes, with triangulation through expert reviews, to be proven as a fitting framework for MAR language learning.