In this paper, we explore a novel strategy for fast computation of the look-ahead Rao-Blackwellised Particle Filtering (la-RBPF) algorithm for the simultaneous localization and mappping (SLAM) problem in the probabili...
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ISBN:
(纸本)9781479931743
In this paper, we explore a novel strategy for fast computation of the look-ahead Rao-Blackwellised Particle Filtering (la-RBPF) algorithm for the simultaneous localization and mappping (SLAM) problem in the probabilistic robotics framework. We show that the complexity of the existing algorithm can be substantially reduced by computing for the Kalman filtering prediction and update steps to only a representative particle of a group of particles offering the same robot's poses. Simulation results reveal the potential of the proposed method in reducing the computational time steps as compared to the original la-RBPF algorithm without affecting the performance. The test results also show its superior estimation accuracy as compared to the standard RBPF SLAM algorithm when the number of particles is small.
This paper presents a general variable step-size (VSS) adaptive filter. The variable step-size normalized least mean square (VSSNLMS) and VSS affine projection algorithms (VSSAPA) are particular examples of adaptive a...
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ISBN:
(纸本)9781479925810
This paper presents a general variable step-size (VSS) adaptive filter. The variable step-size normalized least mean square (VSSNLMS) and VSS affine projection algorithms (VSSAPA) are particular examples of adaptive algorithms covered by this generic adaptive filter. Then, a new VSS partial rank (VSSPR) adaptive filter algorithm based on the generic VSS adaptive filter is introduced for noise cancellation in speech enhancement. The proposed algorithm has faster convergence rate and lower steady state mean square error compare with ordinary PRA. The good performance of the new algorithm is demonstrated via simulation results in attenuating the noise.
In this paper we present a fast implementation of an automatic non-photorealistic image processing technique which transforms an input image frame of a video stream into a non-photorealistic abstracted cartoon stylise...
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ISBN:
(纸本)9781479968435
In this paper we present a fast implementation of an automatic non-photorealistic image processing technique which transforms an input image frame of a video stream into a non-photorealistic abstracted cartoon stylised render. The approach presented utilises a fast cosine integral image method to create a separable bilateral filtering stage which operates in constant time. This is subsequently put through a colour quantisation stage and combined with an edge overlay system to generate the abstracted image output. The algorithm is implemented with OpenCV on a Beagleboard-xM running Angstrom GNU/Linux to demonstrate the improved performance obtained utilising the cosine integral image bilateral filter over the OpenCV standard bilateral filter implementation, and to demonstrate further performance improvements can be obtained through utilising optimised routines on the ARM NEON floating point unit of the Beagleboard-xM.
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