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학술대회 Initial Closed-Form Solution to Mapping from Unknown Planar Motion of an Omni-Directional Vision Sensor
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저자
김재헌, 최진성
발행일
201412
출처
International Symposium on Visual Computing (ISVC) 2014 (LNCS 8888), v.8888, pp.609-619
DOI
https://dx.doi.org/10.1007/978-3-319-14364-4_59
협약과제
14MS5600, 3D 프린팅을 위한 실물 정보 기반 3D 콘텐츠 생성 및 편집 기술(표준화연계), 최진성
초록
This paper proposes a novel method to construct a stationary environment map and estimate the ego-motion of a sensor system from unknown planar motion by using an omni-directional vision sensor. Most environments where sensor moves to obtain maps are limited to two-dimensional space. However, conventional ?쒾tructure from Motion (SFM)?? algorithms cannot be applied to planar motion and onedimensional measurements because they use the epipolar geometry. We propose an algorithm that can be applied to two-dimensional space. Since the number of parameters to be estimated is reduced, computational advantages can be obtained for large map reconstruction. Proposed algorithm exploits the azimuths of features which are obtained from an omni-directional vision sensor and gives robust results against the noise of image information by taking advantage of large field of view. A relation between observed azimuth and motion parameters of a vision sensor are constrained by a nonlinear equation. The proposed method obtains closed form solutions to all the motion parameters and an environment map through a two-step procedure. These estimation results can be used as a good initial seed for the incremental reconstruction of a large map.
KSP 제안 키워드
Ego-motion, Environment map, Epipolar geometry, Field of view(FOV), Image information, Motion parameters, Nonlinear equations, Omni-directional vision, Planar motion, Sensor system, Two-dimensional space