Corisco: Robust edgel-based orientation estimation for generic camera models

Autor(es)

Werneck, Nicolau Leal ^[1] ; Reali Costa, Anna Helena ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, LTI, BR-05508900 Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Image and Vision Computing; v. 31, n. 12, p. 969-981, DEC 2013.
• Citações Web of Science: 1

Resumo

The estimation of camera orientation from image lines using the anthropic environment restriction is a well-known problem, but traditional methods to solve it depend on line extraction, a relatively complex procedure that is also incompatible with distorted images. We propose Corisco, a monocular orientation estimation method based on edgels instead of lines. Edgels are points sampled from image edges with their tangential directions, extracted in Corisco using a grid mask. The estimation aligns the measured edgel directions with the predicted directions calculated from the orientation, using a known camera model. Corisco uses the M-estimation technique to define an objective function that is optimized by two algorithms in sequence: RANSAC, which gives robustness and flexibility to Corisco, and FilterSQP, which performs a continuous optimization to refine the initial estimate, using closed formulas for the function derivatives. Corisco is the first edgel-based method able to analyze images with any camera model, and it also allows for a compromise between speed and accuracy, so that its performance can be tuned according to the application requirements. Our experiments demonstrate the effectiveness of Corisco with various camera models, and its performance surpasses similar edgel-based methods. The accuracy displayed a mean error below 2 degrees for execution times above 8 s in a conventional computer, and above 3 degrees for less than 2 s. (C) 2013 Elsevier B.V. All rights reserved. (AU)

• Processo FAPESP: 11/19280-8 - CogBot: integrando informação perceptual e conhecimento semântico na robótica cognitiva
• Beneficiário: Anna Helena Reali Costa
• Modalidade de apoio: Auxílio à Pesquisa - Regular