Image-based Indoor Positioning System: Fast Image Matching using Omnidirectional Panoramic Images

摘要

In this paper, we developed an image-based indoor localization system using omnidirectional panoramic images to which location information is added. By the combination of the robust image matching by PCA-SIFT and fast nearest neighbor search algorithm based on Locality Sensitive Hashing (LSH), our system can estimate users' positions with high accuracy and in a short time. To improve the precision, we introduced the "confidence" of the image matching results. We conducted experiments at the Railway Museum and we obtained 426 omnidirectional panoramic reference images and 1067 supplemental images for image matching. Experimental results using 126 test images demonstrated that the location detection accuracy is above 90% with about 2.2s of processing time.