Finding hyper-structure in space: spatial parsing in 3D

Abstract

Spatial parsers augment spatial hypermedia systems by letting the computer perceive the informalbut visually apparent -groupings formed by humans working with a spatial hypermedia tool. A number of research systems implementing 2D spatial parsing have been described in recent years. This paper extends spatial parsing to 3D and describes an implementation of a tailorable 3D spatial parser for the Topos system: a 3D information organization tool for use on desktops, interactive whiteboards and tables. The parser maintains a proximity graph of the heterogeneous 3D objects and applies structure experts and global repression and reinforcement techniques to this graph to find structures. A number of issues pertaining to 3D parsing as opposed to 2D parsing are discussed. The paper also presents a simple and efficient 2D parser for 3D scenes and compares it to the true 3D parser.

Parsing and interpreting ambiguous structures in spatial hypermedia

“…o Representation media can be augmented in order to facilitate the manipulation of multiple objects and implicit structure (e.g. hierarchical click selection [1,17,20,21]). …”

“…Parsing of 3-D spaces has been explored in TOPOS by Nielsen and Ørbaek [17]. In their work, they noticed that spatial hypermedia systems that use 2-D or 2½-D representations often provide a fixed viewpoint of the information space.…”

“…This is evident in collaborative 3-D environments, where not only can different users interpret the same structures differently, but different users looking at the same objects can see very different arrangements depending on their location and perspective. This observation prompted the researchers to explore the use of a spatial parser that analyzes the 2-D projection of the space as it is perceived by the users [17].…”

“…Given that spatial parsing can be a demanding process, some parser designers have created algorithms that can parse the space incrementally [9,17,18]. For instance, some parsers maintain an abstraction of the existing relationships in the form of a graph, allowing them to detect which relationships are affected by the users' interactions such that they only need to reparse those regions [9,17].…”

“…Spatial hypermedia closes this communication gap by enabling systems to infer and understand some of the structures that humans implicitly create when reading and interacting with spatial hypermedia. Spatial hypermedia systems accomplish this by employing spatial parsers that analyze the information presentations and infer the implicit structure based on the proximity (how close are objects located), similarity (how alike is the appearance of objects) and regularity (how much do objects conform to specific arrangements such as lists) of the information objects [13,17].…”