Topological mapping for mobile robots using a combination of sonar and vision sensing
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Pose tracking from natural features on mobile phones
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
Combining Harris interest points and the SIFT descriptor for fast scale-invariant object recognition
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Polly: a vision-based artificial agent
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
A color interest operator for landmark-based navigation
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Machine learning for high-speed corner detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
A computational model for the integration of linked data in mobile augmented reality applications
Proceedings of the 8th International Conference on Semantic Systems
Identification of scene locations from geotagged images
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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We present a recognition-based user tracking and augmented reality system that works in extreme large scale areas. The system will provide a user who captures an image of a building facade with precise location of the building and augmented information about the building. While GPS cannot provide information about camera poses, it is needed to aid reducing the searching ranges in image database. A patch-retrieval method is used for efficient computations and real-time camera pose recovery. With the patch matching as the prior information, the whole image matching can be done through propagations in an efficient way so that a more stable camera pose can be generated. Augmented information such as building names and locations are then delivered to the user. The proposed system mainly contains two parts, offline database building and online user tracking. The database is composed of images for different locations of interests. The locations are clustered into groups according to their UTM coordinates. An overlapped clustering method is used to cluster these locations in order to restrict the retrieval range and avoid ping pong effects. For each cluster, a vocabulary tree is built for searching the most similar view. On the tracking part, the rough location of the user is obtained from the GPS and the exact location and camera pose are calculated by querying patches of the captured image. The patch property makes the tracking robust to occlusions and dynamics in the scenes. Moreover, due to the overlapped clusters, the system simulates the "soft handoff" feature and avoid frequent swaps in memory resource. Experiments show that the proposed tracking and augmented reality system is efficient and robust in many cases.