319 search results - page 4 / 64 » On the scalability of robot localization using high-dimensio... |
SIGMOD
2000
ACM
13 years 11 months ago
2000
ACM
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
KDD
2004
ACM
14 years 7 months ago
2004
ACM
The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...
MM
2010
ACM
13 years 7 months ago
2010
ACM
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and object recognition. However, such descriptors are typically of ...
NPL
1998
13 years 7 months ago
1998
Abstract. Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as b...
ICRA
2006
IEEE
14 years 1 months ago
2006
IEEE
— In this paper, we present a delayed algorithm for landmark initialization based on a Scaled Unscented Filter. The algorithm efficiently gives well-conditioned feature location...