Background: Augmented Reality has become a popular technology in recent years. Two of the most prominent AR APIs are ARCore, developed by Google, and We- bXR, an open standard for AR and Virtual Reality (VR) experiences on the web. A comparative analysis of the performance of these APIs in terms of CPU load, network latency, and frame rate is needed to determine which API is more suitable for cloud-based object visualisation AR applications that are integrated with Firebase. Firebase is a cloud-based backend-as-a-service platform made for app development. Objectives: This study aims to provide a comparative analysis of the performance of the ARCore API and WebXR API for an object visualisation application integrated with Firebase Cloud Storage. The objective is to analyze and compare the performance of the APIs in terms of latency, frame rate, and CPU load to provide insights into their strengths and weaknesses and identify the key factors that may influence the choice of API for object visualisation. Methods: To achieve the objectives, two object visualisation AR applications were developed using ARCore API and WebXR API with Firebase cloud. The frame rate, CPU load, and latency were used as performance metrics, the performance data was collected from the applications. The collected data was analysed and visualized to provide insights into the strengths and weaknesses of each API. Results: The results of the study provided a comparative analysis of the performance of the ARCore API and WebXR API for object visualisation applications. The performance metrics of the AR applications, including frame rate, CPU load, and latency, were analyzed and visualized. WebXR API was found to be performing better in terms of CPU load and frame rate, while ARCore API was found to be performing better in terms of latency. Conclusion: The study concluded that the WebXR API showcased advantages in terms of lower CPU load, and higher frame rates compared to the ARCore API which has reduced network latency. These results suggest that the WebXR API is more suitable for efficient and responsive object visualization in augmented reality applications.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:bth-25185 |
Date | January 2023 |
Creators | Shaik, Abu Bakr Rahman, Asodi, Venkata Sai Yakkshit Reddy |
Publisher | Blekinge Tekniska Högskola, Institutionen för datavetenskap |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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