Name
Abstract | ||
|---|---|---|
This paper presents a novel method for discovering change-points in a time series of elements in the set of rigid-body motion in space SE(3). Although numerous change-points detection techniques are available for dealing with scalar, or vector, time series, the generalization of these techniques to more complex structures may require overcoming difficult challenges. The group SE(3) does not satisfy closure under linear combination. Consequently, most of the statistical properties, such as the mean, cannot be properly estimated in a straightforward manner. We present a method that takes advantage of the Lie group structure of SE(3) to adapt a difference of means method. Especially, we show that the change-point in SE(3) can be discovered in its Lie algebra se(3) that forms a vector space. The performance of our method is evaluated through both synthetic and real-data. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-25382-9_16 | Communications in Computer and Information Science |
Field | DocType | Volume |
Linear combination,Mean difference,Lie group,Vector space,Change detection,Algebra,Pattern recognition,Computer science,Scalar (physics),Principal geodesic analysis,Artificial intelligence,Lie algebra | Conference | 229 |
ISSN | Citations | PageRank |
1865-0929 | 0 | 0.34 |
References | Authors | |
20 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Loic Merckel | 1 | 19 | 3.72 |
| Toyoaki Nishida | 2 | 1097 | 196.19 |