An optimal algorithm for approximate nearest neighbor searching
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
Digital Image Processing
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Shape Indexing Using Approximate Nearest-Neighbour Search in High-Dimensional Spaces
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
WLAN Location Determination via Clustering and Probability Distributions
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
The Location Stack: A Layered Model for Location in Ubiquitous Computing
WMCSA '02 Proceedings of the Fourth IEEE Workshop on Mobile Computing Systems and Applications
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Practical robust localization over large-scale 802.11 wireless networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Error characteristics and calibration-free techniques for wireless LAN-based location estimation
Proceedings of the second international workshop on Mobility management & wireless access protocols
The Horus WLAN location determination system
Proceedings of the 3rd international conference on Mobile systems, applications, and services
Features for Recognition: Viewpoint Invariance for Non-Planar Scenes
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
PERCOM '08 Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications
Positioning and Orientation in Indoor Environments Using Camera Phones
IEEE Computer Graphics and Applications
Indoor Positioning and Navigation with Camera Phones
IEEE Pervasive Computing
Error Estimation for Indoor 802.11 Location Fingerprinting
LoCA '09 Proceedings of the 4th International Symposium on Location and Context Awareness
SurroundSense: mobile phone localization via ambience fingerprinting
Proceedings of the 15th annual international conference on Mobile computing and networking
Markov localization using correlation
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Empirical evaluation of the limits on localization using signal strength
SECON'09 Proceedings of the 6th Annual IEEE communications society conference on Sensor, Mesh and Ad Hoc Communications and Networks
LOC8: A Location Model and Extensible Framework for Programming with Location
IEEE Pervasive Computing
Hybrid Indoor Location Estimation System Using Image Processing and WiFi Strength
WNIS '09 Proceedings of the 2009 International Conference on Wireless Networks and Information Systems
Growing an organic indoor location system
Proceedings of the 8th international conference on Mobile systems, applications, and services
Automatic mitigation of sensor variations for signal strength based location systems
LoCA'06 Proceedings of the Second international conference on Location- and Context-Awareness
Place-Its: a study of location-based reminders on mobile phones
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
Vision-based global localization and mapping for mobile robots
IEEE Transactions on Robotics
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This paper introduces a multisensor architecture to fuse data acquired from different sensors available in commodity smartphones in order to build accurate location-based services, and pursuing a good balance between accuracy and performance. Using scale invariant features from the images captured using the smartphone camera, we perform a matching process against previously obtained images to determine the current location of the device. Several refinements are introduced to improve the performance and the scalability of our proposal. Location fingerprinting, based on IEEE 802.11, will be used to determine a cluster of physical points, or zone, where the device seems to be according to the received signal strength. In this way, we will reduce the number of images to analyze to those contained in the tentative zone. Additionally, accelerometers will also be considered in order to improve the system performance, by means of a motion estimator. This set of techniques enables a wide range of location-based applications.