Efficient selection of multiple objects on a large scale

The task of multiple object selection (MOS) in immersive virtual environments is important and still largely unexplored. The difficulty of efficient MOS increases with the number of objects to be selected. E.g. in small-scale MOS, only a few objects need to be simultaneously selected. This may be accomplished by serializing existing single-object selection techniques. In this paper, we explore various MOS tools for large-scale MOS. That is, when the number of objects to be selected are counted in hundreds, or even thousands. This makes serialization of single-object techniques prohibitively time consuming. Instead, we have implemented and tested two of the existing approaches to 3-D MOS, a brush and a lasso, as well as a new technique, a magic wand, which automatically selects objects based on local proximity to other objects. In a formal user evaluation, we have studied how the performance of the MOS tools are affected by the geometric configuration of the objects to be selected. Our studies demonstrate that the performance of MOS techniques is very significantly affected by the geometric scenario facing the user. Furthermore, we demonstrate that a good match between MOS tool shape and the geometric configuration is not always preferable, if the applied tool is complex to use.