Faculty Publications

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Publications by NITK Faculty

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Subject: search.filters.subject.Augmented reality

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    ARTSAM: Augmented Reality App for Tool Selection in Aircraft Maintenance
    (Springer Science and Business Media Deutschland GmbH, 2023) Satish, N.; Kumar, C.R.S.
    Aircraft Maintenance is an advanced task requiring highly skilled engineers. Facilitating the Aircraft maintenance by providing proper tools and equipment is essential in ensuring good maintenance work. Aircraft Maintenance Technicians (AMTs) require precise knowledge and customized tools to perform their duties. They are responsible for an airplane’s safety and efficiency, and rely on a few basic pieces of equipment for a wide range of jobs pertaining to airplane maintenance. Specific maintenance tasks require unique tools. And while the AMTs could probably improvise and get the job done anyway, specialized tools exist for a reason–they help get the job done correctly and improvising will lead to unnecessary labor and a compromised aircraft. For example, an incorrectly sized screwdriver or screw causes wear and tear and makes the job harder. Besides, traditional tool management requires employees to manually check in and out each tool, which is time consuming. A Tool Selector app which recognises and tags tools in real time will help AMTs in determining how it is used in a particular task. Through this app, the AMTs can be guided through animations to perform specific tasks, such as replacement of Oil Filter from an aircraft engine. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Predicting the Determinants of Augmented Reality Technologies in E-commerce Applications: A SEM and ANN Modeling
    (Springer Science and Business Media Deutschland GmbH, 2025) Anand, K.; Sheena, S.
    Augmented reality (AR) technologies are the most promising technologies for e-commerce applications. This study has used the UTAUT theory, extending with privacy risk, which may impact the user’s decision to try AR features in e-commerce apps. The paper investigated factors using a two-stage approach comprising of Structural Equation Model (SEM) and an Artificial Neural Network (ANN). The validation of the model is performed with the IBM SPSS AMOS 24 and IBM SPSS 25 software. The results revealed performance expectancy as a noteworthy determinant through the analysis. Further privacy risks involved while using AR features of online shopping apps negatively impact the influence on the choice of the users to try out the technology. The proposed model has explained the user behavioral intention with 36.7%, whereas using ANN has predicted with an accuracy of 48.9%, indicating the model has high predictive power. This study’s theoretical and practical insights will contribute to developing and refining augmented reality systems in e-commerce applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
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    Guided depth image reconstruction from very sparse measurements
    (SPIE spie@spie.org, 2018) Balure, C.S.; Bhavsar, A.; Ramesh Kini, M.
    Depth images captured from modern depth cameras generally suffer from low spatial resolution, noise, and missing regions. These kinds of images cannot be used directly in applications related to depth images, e.g., robot navigation, 3DTV, and augmented reality, which basically need high-resolution input images with no noise o missing regions to function properly. To address the problem of low spatial resolution, noise degradation, and missing regions in depth images, we propose methods based on a guidance color image for depth reconstruction (DR) from sparse depth inputs and depth image super-resolution (SR). We also suggest a scenario wherein these problems can be integrated and addressed simultaneously. Further, we also demonstrate applications of the proposed approach for depth image denoising and depth image inpainting. In our approach, the guidance color image is used for obtaining the segment cues by applying mean-shift (MS) or simple linear iterative clustering (SLIC) segmentation on it. These strong segment cues help in aiding the DR and SR problems by considering the corresponding segments in the input depth image, and estimate the unknown pixels by either plane fitting or median filling approaches. Furthermore, we explore both direct and pyramidal (hierarchical) approaches for SR and DR-SR for higher upsampling factor. As such, our approaches are relatively simpler than some of the contemporary methods, yet the experimental results of the proposed methods show superior performance as compared with some other state-of-the-art DR and SR methods. © 2018 SPIE and IS&T.
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    An empirical examination of user’s adoption of AR in e-commerce apps in a developing country: evidence from India
    (Emerald Publishing, 2025) Anand, K.; S, S.
    Purpose The e-commerce industry is witnessing rapid growth by offering convenience in shopping. However, it fails to provide a virtual experience of the products, creating excessive product returns and posing challenges to the companies, customers and environment. The use of augmented reality (AR) bridges the gap between the customers and products. The purpose of this study is to explore the customer perspective towards adopting AR in online shopping, which can reduce excessive product returns, creating sustainable business practices. Design/methodology/approach Online survey was used in the data collection process. A total of 1,029 valid responses collected via judgement sampling were analysed using covariance-based structural equation modelling with AMOS software. Findings Trust is significantly influenced by performance expectancy, effort expectancy, social influence and facilitating conditions. Likewise, performance expectancy, hedonic motivation and trust significantly affect behavioural intention. Meanwhile, effort expectancy, social influence, facilitating conditions on behavioural intention and hedonic motivation on trust were found to have an insignificant influence. Practical implications This study investigates users’ behavioural intention towards AR in online shopping apps using the Unified Theory of Acceptance and Use of Technology (UTAUT2) with trust in the Indian context, providing valuable insights into implementing AR technology and enhancing the realism of virtual product experiences. Originality/value This study aims to investigate users’ behavioural intention by providing a research model that extends the UTAUT2 model, including trust. The objective is to analyse the factors influencing the adoption of a novel technology in a developing country, specifically in the Indian context. © 2025 Emerald Publishing Limited