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IJCAI
1997
13 years 10 months ago
Learning Topological Maps with Weak Local Odometric Information
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
Hagit Shatkay, Leslie Pack Kaelbling
CVPR
2009
IEEE
15 years 3 months ago
Locally Time-Invariant models of Human Activities using Trajectories on the Grassmanian
Human activity analysis is an important problem in computer vision with applications in surveillance and summarization and indexing of consumer content. Complex human activities...
Pavan Turaga, Rama Chellappa
PRL
2010
130views more  PRL 2010»
13 years 7 months ago
Automatic configuration of spectral dimensionality reduction methods
In this paper, our main contribution is a framework for the automatic configuration of any spectral dimensionality reduction methods. This is achieved, first, by introducing the m...
Michal Lewandowski, Dimitrios Makris, Jean-Christo...
COMPGEOM
2006
ACM
14 years 2 months ago
Lower bounds on locality sensitive hashing
Given a metric space (X, dX), c ≥ 1, r > 0, and p, q ∈ [0, 1], a distribution over mappings H : X → N is called a (r, cr, p, q)-sensitive hash family if any two points in...
Rajeev Motwani, Assaf Naor, Rina Panigrahy
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 1 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer