Abstract
Abstract. As the interest in indoor spaces increases, there is a growing need for indoor spatial applications. As these spaces grow in complexity and size, research is being carried out towards effective and efficient representation. Omnidirectional images give a snapshot of interiors and give visually rich content, but only contain pixel data. For it to be used in providing indoor services, its limitations must be overcome. First, the images must be connected to each other to represent indoor space continuously based on spatial relationships that may be provided by topological data. Second, the objects and spaces that we see in these images must also be recognized. This paper presents a study on how to link omnidirectional images and an IndoorGML data without the need for data conversion, provision of reference data, or use of different data models in order to provide Indoor Location-Based Service (LBS). We introduce the use of the Spatial Extended Point (SEP) to characterize the relationship between the omnidirectional image and the topological data. Position information of the object is used to define a region of 3D space, to determine the inclusion relationship of an IndoorGML node. We conduct an experimental implementation of the integrated data in the form of a 3D Virtual Tour. The connection of the Omnidirectional images is demonstrated by a visualization of navigation through a hallway towards a room’s interior delivered to the user through a clicking action on the image.
Highlights
Nowadays, spatial applications move towards the indoors and as these spaces continue to be more complex the interest in applications (Giudice et al, 2010)
Various techniques have been made available by previous studies in representing indoor space, and focus is given to topological datasets that allow for efficient and accurate spatial analysis
This paper proposes a data fusion method between omnidirectional images and topological data using the concept of Spatial Extended Point
Summary
Spatial applications move towards the indoors and as these spaces continue to be more complex the interest in applications (Giudice et al, 2010). As various researchers approach this problem differently, various forms of data have been used to represent the various aspects of the indoor environment, primarily as the representation method depends on the purpose of the intended service. These variations in data generation, management, and application becomes the source of problems in implementation due to issues of compatibility and connectivity (Ahn et al, 2018). Various approaches have been explored for this purpose, such as data conversion, exploring relationships through attributes, or referring to an external reference data These methods aim for consistency in representation in geometric and topological aspects to increase understanding of the relationships of the features themselves that are represented
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