Abstract
Nowadays, the importance and utilization of spatial information are recognized. Particularly in urban areas, the demand for indoor spatial information draws attention and most commonly requires high-precision 3D data. However accurate, most methodologies present problems in construction cost and ease of updating. Images are accessible and are useful to express indoor space, but pixel data cannot be applied directly to provide indoor services. A network-based topological data gives information about the spatial relationships of the spaces depicted by the image, as well as enables recognition of these spaces and the objects contained within. In this paper, we present a data fusion methodology between image data and a network-based topological data, without the need for data conversion, use of a reference data, or a separate data model. Using the concept of a Spatial Extended Point (SEP), we implement this methodology to establish a correspondence between omnidirectional images and IndoorGML data to provide an indoor spatial service. The proposed algorithm used position information identified by a user in the image to define a 3D region to be used to distinguish correspondence with the IndoorGML and indoor POI data. We experiment with a corridor-type indoor space and construct an indoor navigation platform.
Highlights
Most services involving spatial data are available for outdoors, compared to the indoors [1], despite being more crucial in urban areas, where people generally spend more time in a structure [2] or where navigation in cases of evacuation is experiencing more delay [3]
We demonstrate a procedure to establish a relationship between omnidirectional images and IndoorGML data for providing indoor space applications
Indoor space has been expressed in various ways in previous studies, with each method differing in method of collection and generation, emphasized aspect of space, and applications
Summary
Most services involving spatial data are available for outdoors, compared to the indoors [1], despite being more crucial in urban areas, where people generally spend more time in a structure [2] or where navigation in cases of evacuation is experiencing more delay [3]. As this concern gains attention, various approaches in representation have been attempted across applications, as this depends on the field and intent of service [4].
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call