Distributed algorithms and protocols
Distributed algorithms and protocols
IEEE Transactions on Pattern Analysis and Machine Intelligence
GHT: a geographic hash table for data-centric storage
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
The Trimmed Iterative Closest Point Algorithm
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Fusing Points and Lines for High Performance Tracking
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Distributed localization of networked cameras
Proceedings of the 5th international conference on Information processing in sensor networks
A review of recent range image registration methods with accuracy evaluation
Image and Vision Computing
Determining vision graphs for distributed camera networks using feature digests
EURASIP Journal on Applied Signal Processing
Q-SIFT: Efficient feature descriptors for distributed camera calibration
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Machine learning for high-speed corner detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
A self-localization system with global error reduction and online map-building capabilities
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part III
Modeling Coverage in Camera Networks: A Survey
International Journal of Computer Vision
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Stereo-based 3D distributed smart camera networks are useful in a broad range of applications. Knowledge of the relative locations and orientations of nodes in the network is an essential prerequisite for true 3D sensing. A novel spatial calibration method for a network of pre-calibrated stereo smart cameras is presented, which obtains pose estimates suitable for collaborative 3D vision in a distributed fashion using two stages of registration on robust 3D point sets. The method is initially described in a geometrical sense, then presented in a practical implementation using existing vision and registration algorithms. Experiments using both software simulations and physical devices are designed and executed to demonstrate performance.