Vision system for coarsely estimating motion parameters for unknown fast moving objects in space

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish
Article number2820
JournalSensors (Switzerland)
Volume17
Issue number12
DOIs
Publication statusPublished - 2017 Dec 5

Keywords

  • 3D reconstruction
  • Camera system
  • Feature point detection
  • Motion estimation
  • Robust estimation
  • Video tracking

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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