Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/100924
Type: Artigo de periódico
Title: Line Based Camera Calibration In Machine Vision Dynamic Applications
Author: Tommaselli A.M.G.
Tozzi C.L.
Abstract: The problem of dynamic camera calibration considering moving objects in close range environments using straight lines as references is addressed. A mathematical model for the correspondence of a straight line in the object and image spaces is discussed. This model is based on the equivalence between the vector normal to the interpretation plane in the image space and the vector normal to the rotated interpretation plane in the object space. In order to solve the dynamic camera calibration, Kalman Filtering is applied; an iterative process based on the recursive property of the Kalman Filter is defined, using the sequentially estimated camera orientation parameters to feedback the feature extraction process in the image. For the dynamic case, e.g. an image sequence of a moving object, a state prediction and a covariance matrix for the next instant is obtained using the available estimates and the system model. Filtered state estimates can be computed from these predicted estimates using the Kalman Filtering approach and based on the system model parameters with good quality, for each instant of an image sequence. The proposed approach was tested with simulated and real data. Experiments with real data were carried out in a controlled environment, considering a sequence of images of a moving cube in a linear trajectory over a flat surface.
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Rights: aberto
Identifier DOI: 
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-0033353464&partnerID=40&md5=6554f0ca00eeaeaecbb059aa6fd2ece9
Date Issue: 1999
Appears in Collections:Unicamp - Artigos e Outros Documentos

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