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iNavigation: an image based indoor navigation system
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AI
DOI：10.1007/s11042-013-1656-9.png)
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Abstract
En 中文
This paper presents a novel image-based indoor navigation web application designed for mobile phone. It is inspired by Google Street View that features 360 degrees imagery for navigation. Ordinary data collection of image based navigation systems implements panorama cameras, so it is difficult to be extended to indoor environment. On the other hand, they cannot provide timely updates because it requires immense image data. This paper introduces a 'proof of concept' which only uses ordinary organized photo collections instead of panoramic photo to guide people through the building. It implements SIFT (scale-invariant feature transform) feature detection and ANN (approximately nearest neighbor) search to provide positioning service. People can upload query images to obtain current position. It also enables information sharing by using IPM (inverse perspective mapping) technique to figure out distance from a single query image, and update the query image into the image collection correctly based on the distance calculation.
Keywords:
Indoor
Navigation
Image
Photo-based
SIFT
IPM
ANN search
Best-bin-first
Journal
IF:
3
Papers:
1.9W
Citations:
3.2W