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Title: Evaluation of interest point matching methods for projective reconstruction of 3d scenes.
Authors: Brito, Darlan Nunes de
Nunes, Cristiano Fraga Guimarães
Pádua, Flávio Luis Cardeal
Lacerda, Anisio Mendes
Keywords: Point matching methods
Camera self-calibration
Projective reconstruction
Issue Date: 2016
Citation: BRITO, D. N. de et al. Evaluation of interest point matching methods for projective reconstruction of 3d scenes. IEEE Latin America Transactions, v. 14, p. 1393-1400, 2016. Disponível em: <>. Acesso em: 02 out. 2017.
Abstract: This work evaluates the application of different state-of-the-art methods for interest point matching, aiming the robust and efficient projective reconstruction of three-dimensional scenes. Projective reconstruction refers to the computation of the structure of a scene from images taken with uncalibrated cameras. To achieve this goal, it is essential the usage of an effective point matching algorithm. Even though several point matching methods have been proposed in the literature, their impacts in the projective reconstruction task have not yet been carefully studied. Our evaluation uses as criterion the estimated epipolar, reprojection and reconstruction errors, as well as the running times of the algorithms. Specifically, we compare five different techniques: SIFT, SURF, ORB, BRISK and FREAK. Our experiments show that binary algorithms such as, ORB and BRISK, are so accurate as float point algorithms like SIFT and SURF, nevertheless, with smaller computational cost.
ISSN: 15480992
Appears in Collections:DECSI - Artigos publicados em periódicos

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