An O(nlogn) implementation of the Douglas-Peucker algorithm for line simplification
SCG '94 Proceedings of the tenth annual symposium on Computational geometry
Cartographic line simplification and polygon CSG formulæ in O(n log* n) time
WADS '97 Selected papers presented at the international workshop on Algorithms and data structure
Polygonal approximations that minimize the number of inflections
SODA '93 Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms
A data model and data structures for moving objects databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Approximation Algorithms for k-Line Center
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Approximate query processing using wavelets
The VLDB Journal — The International Journal on Very Large Data Bases
Tracking a moving object with a binary sensor network
Proceedings of the 1st international conference on Embedded networked sensor systems
Spatio-temporal data reduction with deterministic error bounds
The VLDB Journal — The International Journal on Very Large Data Bases
Catching elephants with mice: Sparse sampling for monitoring sensor networks
ACM Transactions on Sensor Networks (TOSN)
Using mobile phones to determine transportation modes
ACM Transactions on Sensor Networks (TOSN)
Streaming Algorithms for Line Simplification
Discrete & Computational Geometry
IBM infosphere streams for scalable, real-time, intelligent transportation services
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
A unified framework for approximating and clustering data
Proceedings of the forty-third annual ACM symposium on Theory of computing
Coresets for discrete integration and clustering
FSTTCS'06 Proceedings of the 26th international conference on Foundations of Software Technology and Theoretical Computer Science
Mahout in Action
From high definition image to low space optimization
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
The single pixel GPS: learning big data signals from tiny coresets
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
iDiary: from GPS signals to a text-searchable diary
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
Generating storylines from sensor data
Pervasive and Mobile Computing
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The wide availability of networked sensors such as GPS and cameras is enabling the creation of sensor networks that generate huge amounts of data. For example, vehicular sensor networks where in-car GPS sensor probes are used to model and monitor traffic can generate on the order of gigabytes of data in real time. How can we compress streaming high-frequency data from distributed sensors? In this paper we construct coresets for streaming motion. The coreset of a data set is a small set which approximately represents the original data. Running queries or fitting models on the coreset will yield similar results when applied to the original data set. We present an algorithm for computing a small coreset of a large sensor data set. Surprisingly, the size of the coreset is independent of the size of the original data set. combining map-and-reduce techniques with our coreset yields a system capable of compressing in parallel a stream of O(n) points using space and update time that is only O(log n). We provide experimental results and compare the algorithm to the popular Douglas-Peucker heuristic for compressing GPS data.