Name
Abstract | ||
|---|---|---|
This paper introduces an LBS multisensor system that acquires data from different sensors available in commodity smart phones to provide accurate location estimations. Our approach is based on the use of visual structure from motion techniques to run off-line 3D reconstructions of the environment from the correspondences among the SIFT descriptors of the training images. We present several solutions to reduce the deployment cost, in terms of time, and to minimize the interference degree within the environment, but also pursuing a good balance between accuracy and performance. To determine the position of the smartphones, we first obtain a coarse-grained estimation based on WiFi signals, digital compasses, and built-in accelerometers, making use of fingerprinting methods, probabilistic techniques, and motion estimators. Then, using images captured by the camera, we perform a matching process to determine correspondences between 2D pixels and model 3D points, but only analyzing a subset of the 3D model delimited by the coarse-grained estimation. We implement a resection process providing high localization accuracy when the camera has been previously calibrated, that is, we know intrinsic parameters like focal length, but it is also accurate if an auto-calibration process is required. Furthermore, our experimental tests show promising results, since we are able to provide high accuracy with an average error down to 15 cm in less than 0.5 seconds of response time, making this proposal suitable for applications combining location-services and augmented reality. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IPIN.2012.6418901 | Indoor Positioning and Indoor Navigation |
Keywords | Field | DocType |
accelerometers,cameras,motion estimation,sensor fusion,smart phones,wireless LAN,LBS multisensor system,SIFT descriptors,SIFT-based 3D models,WiFi signals,auto-calibration process,built-in accelerometers,camera,coarse-grained estimation,commodity smart phones,digital compasses,fingerprinting methods,interference degree,location based service,motion estimators,probabilistic techniques,run off-line 3D reconstructions,scale invariant feature transform,training images,visual structure,Image processing,SIFT,multisensor,smartphones,structure from motion,training | Computer vision,Scale-invariant feature transform,Accelerometer,Augmented reality,Sensor fusion,Artificial intelligence,Pixel,Probabilistic logic,Engineering,Motion estimation,Estimator | Conference |
ISSN | ISBN | Citations |
2162-7347 | 978-1-4673-1955-3 | 4 |
PageRank | References | Authors |
0.46 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonio Jesus Ruiz Ruiz | 1 | 4 | 0.46 |
| Pedro E. López-de-teruel | 2 | 52 | 9.75 |
| Óscar Cánovas | 3 | 41 | 7.15 |
| Lopez-de-Teruel, P.E. | 4 | 7 | 1.21 |