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» SLAM via Variable Reduction from Constraint Maps
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ICRA
2005
IEEE
123views Robotics» more  ICRA 2005»
10 years 4 months ago
SLAM via Variable Reduction from Constraint Maps
- The two dominant forms of SLAM are based on Extended Kalman Filtering and Consistent Pose Estimation. We show that these are particular subsets of a more general view of the SLAM...
Kurt Konolige
ICML
2006
IEEE
10 years 11 months ago
Local distance preservation in the GP-LVM through back constraints
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
Joaquin Quiñonero Candela, Neil D. Lawrence
COCOA
2010
Springer
9 years 8 months ago
Feasibility-Based Bounds Tightening via Fixed Points
Abstract. The search tree size of the spatial Branch-and-Bound algorithm for Mixed-Integer Nonlinear Programming depends on many factors, one of which is the width of the variable ...
Pietro Belotti, Sonia Cafieri, Jon Lee, Leo Libert...
NIPS
2007
9 years 12 months ago
People Tracking with the Laplacian Eigenmaps Latent Variable Model
Reliably recovering 3D human pose from monocular video requires models that bias the estimates towards typical human poses and motions. We construct priors for people tracking usi...
Zhengdong Lu, Miguel Á. Carreira-Perpi&ntil...
ASAP
2011
IEEE
233views Hardware» more  ASAP 2011»
8 years 10 months ago
Accelerating vision and navigation applications on a customizable platform
—The domain of vision and navigation often includes applications for feature tracking as well as simultaneous localization and mapping (SLAM). As these problems require computati...
Jason Cong, Beayna Grigorian, Glenn Reinman, Marco...
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