Page 134 - Kaleidoscope Academic Conference Proceedings 2022

Session 2: Augmented reality systems: design and implementation

S2.1 A framework for the design, implementation and evaluation of a multi-variant Augmented Reality
application*
Sophie Westfahl and Dany Meyer-Renner (University of Applied Sciences Neu-Ulm, Germany);
Antoine Bagula (University of the Western Cape, South Africa)

Augmented Reality (AR) is one of the key technologies of the fourth Industrial Revolution (4IR)
and plays an increasingly important role in many companies. However, while the demand for new
AR applications is rapidly increasing, fundamental best practices and frameworks for the industrial
AR sector are still scarce or in their infancy stage. This paper addresses this gap by proposing a
framework for the design and efficient implementation of AR applications with multiple models
and variants. The proposed framework is built around: i) a development process that describes the
different steps for the design of a model-based AR application and its implementation with Unity
and Vuforia model targets; and ii) a multilayer orchestration model that describes the different
interactions between a user and a server layer. The proposed framework is successfully
implemented, and its performance analyzed using both quantitative and qualitative evaluation
based on the Brooke's System Usability Scale.

S2.2 Enhancing user experience in pedestrian navigation based on Augmented Reality and landmark
recognition*
Dhananjay Kumar, Shreayaas Iyer, Easwar Raja and Ragul Kumar (Anna University, MIT
Campus, Chennai, India); Ved P. Kafle (National Institute of Information and Communications
Technology, Japan)

Pedestrian navigation using traditional mapping systems is constrained by the inherent limitations
of the existing digital online mapping services. The major challenges include complete reliance on
GPS for user localization and inferior user experience caused by lack of information about the
surroundings especially in unknown environments. In this paper, we design and develop a marker-
less augmented reality based pedestrian navigation system which can handle navigation even in
the absence of GPS as well as improve user experience by providing a novel landmark recognition
feature, which allows users to identify nearby buildings or streets during navigation. To mitigate
the absence of GPS signal, a user localization method utilizing a step-count based distance
estimator is proposed. The performance comparison with existing state of the art techniques and
devices shows locational accuracy of 2.5 meters on average and step-count detection accuracy
increase of nearly 0.5% with latency of 70 milliseconds in an urban environment. The proposed
solution is intended to be used as a mobile application on smartphones and has a potential to
contribute to the smart city-related standardization activities of ITU-T Study Group 16.

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