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Fast Non-minimal Solvers for Planar Motion Compatible Homographies

Örnhag, Marcus Valtonen (författare)
Lund University,Lunds universitet,Matematik LTH,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Mathematics (Faculty of Engineering),Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
Fred, Ana (redaktör/utgivare)
De Marsico, Maria (redaktör/utgivare)
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di Baja, Gabriella Sanniti (redaktör/utgivare)
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 (creator_code:org_t)
SCITEPRESS - Science and Technology Publications, 2019
2019
Engelska 12 s.
Ingår i: ICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods. - : SCITEPRESS - Science and Technology Publications. - 9789897583513 ; , s. 40-51
  • Konferensbidrag (refereegranskat)
Abstract Ämnesord
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  • This paper presents a novel polynomial constraint for homographies compatible with the general planar motion model. In this setting, compatible homographies have five degrees of freedom-instead of the general case of eight degrees of freedom-and, as a consequence, a minimal solver requires 2.5 point correspondences. The existing minimal solver, however, is computationally expensive, and we propose using non-minimal solvers, which significantly reduces the execution time of obtaining a compatible homography, with accuracy and robustness comparable to that of the minimal solver. The proposed solvers are compared with the minimal solver and the traditional 4-point solver on synthetic and real data, and demonstrate good performance, in terms of speed and accuracy. By decomposing the homographies obtained from the different methods, it is shown that the proposed solvers have future potential to be incorporated in a complete Simultaneous Localization and Mapping (SLAM) framework.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Nyckelord

Homography
Planar Motion
Polynomial Solver
Trajectory Recovery
Visual Odometry

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