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Feature-based human motion parameter estimation with radar
TLDR
The authors focus on a fast feature-based approach to estimate human motion features for real-time applications to provide a realistic look-alike of the real motion of the person. Expand
Human walking estimation with radar
Radar can be used to observe humans that are obscured by objects such as walls. These humans cannot be visually observed. The radar measurements are used to animate an obscured human in virtualExpand
Discretization errors in the Hough transform
TLDR
The Hough transform was improved by O'Gorman and Clowes by taking into account the gradient direction and the resulting scatter of the peaks can be reduced by using a weighting function in the transform. Expand
Absorption and scattering correction in fluorescence confocal microscopy
In three‐dimensional (3‐D) fluorescence images produced by a confocal scanning laser microscope (CSLM), the contribution of the deeper layers is attenuated due to absorption and scattering of bothExpand
Possibilistic decision making in sensor systhems
TLDR
The possibilistic decision maker is less sensitive to inaccuracies in a piortknowledge and cost estimates than the Bayesian decision maker at the expense of a degraded performance in situations where accurate a priori knowledge and cost estimetes are available. Expand
Bias reduction for stereo based motion estimation with applications to large scale visual odometry
TLDR
It is shown that bias in the motion estimates can be caused by incorrect modeling of the uncertainties in landmark locations, and there exists a relation between the bias, the true motion and the distribution of landmarks in space. Expand
UvA Trilearn 2003 Team Description
TLDR
The main features of the UvA Trilearn soccer simulation team, which participated for the first time at the RoboCup-2001 competition, are described and some conclusions and future research directions are described. Expand
Fast Translation Invariant Classification of (HRR) Range Profiles in a Zero Phase Representation
TLDR
A new alignment method is proposed, the time-smoothed zero phase representation, which is compared to existing alignment methods in terms of classification performance and has two main advantages compared to those described in the known literature. Expand
Navigation of a mobile robot on the temporal development of the optic flow
TLDR
The robot navigation task presented in this paper is to drive through the center of a corridor, based on a sequence of images from an on-board camera, using the structure contained in the temporal derivatives of the optic flow to compare the environment structure and hence the system state. Expand
Traffic Light Control by Multiagent Reinforcement Learning Systems
TLDR
This chapter describes multiagent reinforcement learning techniques for automatic optimization of traffic light controllers, which can automatically discover efficient control strategies for complex tasks, such as traffic control, for which it is hard or impossible to compute optimal solutions directly and hard to develop hand-coded solutions. Expand
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