Scale-based Exploded Views: Evaluating Object Selection Methods on Mobile Devices
Many 3D exploded view diagrams are too expensive for use on relatively low powered mobile devices, particularly for large models. In this thesis, we evaluate a low-complexity scale-based 3D exploded view method that is designed to help find and select small and occluded objects from 3D models on mobile devices. The system preprocesses a 3D model by categorizing each object into different layers based on each object's size. The exploded view can then peel the scale-based layers from the object based on user input. In a comparative user study, our method was found to require generally less time than an alternate low cost explosion technique when performing several selection tasks. Moreover, it significantly reduced the number of wrong targets selected. This is important given that our application is targeted for use in mobile-assisted manufacturing and repair environments with a low tolerance for user error.