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Sensors 2017, 17(12), 2820; https://doi.org/10.3390/s17122820

Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

Graduate School of Information Sciences, Tohoku University, Aramaki Aza Aoba 6-6-01, Aoba-Ku, Sendai 980-8579, Japan
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Received: 30 October 2017 / Revised: 27 November 2017 / Accepted: 1 December 2017 / Published: 5 December 2017
(This article belongs to the Special Issue Video Analysis and Tracking Using State-of-the-Art Sensors)
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Abstract

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. View Full-Text
Keywords: feature point detection; 3D reconstruction; motion estimation; camera system; robust estimation; video tracking feature point detection; 3D reconstruction; motion estimation; camera system; robust estimation; video tracking
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Chen, M.; Hashimoto, K. Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space. Sensors 2017, 17, 2820.

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