NDLI: A filter method for pose estimation of maneuvering target

Content Provider	IEEE Xplore Digital Library
Author	Feili Hou Feng Zhu
Copyright Year	2004
Description	Author affiliation: Shenyang Inst. of Autom., Chinese Acad. of Sci., Shenyang, China (Feili Hou; Feng Zhu)
Abstract	A filter method is presented for 3D pose (position and orientation) estimation of an arbitrary moving target from a monocular image sequence. Problem considered here is error propagation from image features to pose parameters. To this end, we have derived a combination of two filter schemes. The first filter scheme uses maneuver detection technique, in which the criterion of an optimal detector is deduced, two detectors suitable for fast and slow maneuvers are analyzed, and limited memory filtering is adopted for maneuver correction. In the second filter, a robust model is established via Lagrange interpolation and numerical integration, and the possibility of filter divergence is avoided by employing an adaptively estimated fading factor. Finally, generalized pseudo Bayes algorithm is employed to combine the two filter models for better filter performance. Superior to previous approaches that were limited to slow and smooth motion, this filter method is applicable for a maneuvering target that acts in an unknown manner. Moreover, it is suitable for real-time environment in terms of the following aspects: the structure of the filter is simplified by avoiding the need of EKF, the computational cost is much reduced by running six filters on the six pose sequences in parallel; the process to extract the feature points is simplified due to the predicted feature locations; time efficiency is increased because the sequence of image frames is allowed to be at unequal intervals. Simulation results and implement of a system for multi-mobile robots formation show the capacity of this algorithm.
Starting Page	2396
Ending Page	2403
File Size	524836
Page Count	8
File Format	PDF
ISBN	0780384636
DOI	10.1109/IROS.2004.1389767
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-09-28
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Detectors Adaptive filters Image sequences Filtering Robustness Lagrangian functions Interpolation Fading Computational efficiency Feature extraction
Content Type	Text
Resource Type	Article

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