An exploratory research of ARCore's feature detection
Anna Eklind, Love Stark · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2018
Augmented reality has been on the rise for some time now and begun making its way onto the mobile market for both IOS and Android. In 2017 Apple released ARKit for IOS which is a software development kit for developing augmented reality applications. To counter this, Google released their own variant called ARCore on the 1st of march 2018. ARCore is also a software development kit for developing augmented reality applications but made for the Android, Unity and Unreal platforms instead. Since ARCore is released recently it is still unknown what particular limitations may exist for it. The purpose of this paper is give an indication to companies and developers about ARCore’s potential limitations. The goal with this paper and work is to map how well ARCore works during different circumstances, and in particular, how its feature detection works and behaves. A quantitative research was done with the usage of the case study method. Various tests were performed with a modified test-application supplied by Google. The tests included testing how ARCore’s feature detection, the process that analyzes the environment presented to the application. This which enables the user of an application to place a virtual object on the physical environment. The tests were done to see how ARCore works during different light levels, different types of surfaces, different angles and the difference between having the device stationary or moving. From the testing that were done some conclusions could be drawn about the light levels, surfaces and differences between a moving and stationary device. More research and testing following these principles need to be done to draw even more conclusions of the system and its limitations. How these should be done is presented and discussed.