By Paul Debevec (auth.), Marc Pollefeys, Luc Van Gool, Andrew Zisserman, Andrew Fitzgibbon (eds.)
This quantity comprises the ?nal model of the papers initially offered on the moment SMILE workshop 3D constitution from a number of photos of Large-scale Environments, which was once hung on 1-2 July 2000 along with the 6th ecu convention in desktop imaginative and prescient at Trinity university Dublin. the topic of the workshop used to be the visible acquisition of types of the 3D global from photos and their software to digital and augmented fact. over the past few years large growth has been made during this region. at the one hand very important new insightshavebeenobtainedresultinginmore exibilityandnewrepresentations.Onthe different hand a couple of options have come to adulthood, yielding powerful algorithms providing stable effects on genuine picture info. in addition helping applied sciences – equivalent to electronic cameras, pcs, disk garage, and visualization units – have made issues attainable that have been infeasible quite a few years in the past. commencing the workshop was once Paul Debevec s invited presentation on image-based modeling,rendering,andlighting.Hepresentedanumberoftechniquesforusingdigital photographs of genuine scenes to create 3D types, digital digital camera strikes, and reasonable desktop animations.Theremainderoftheworkshopwasdividedintothreesessions:Computation and Algorithms, visible Scene Representations, and prolonged Environments. After every one consultation there has been a panel dialogue that incorporated all audio system. those panel discussions have been prepared by means of invoice Triggs, Marc Pollefeys, and Tomas Pajdla respectively, who brought the themes and moderated the dialogue. Asubstantialpartoftheseproceedingsarethetranscriptsofthediscussionsfollowing each one paper and the entire panel classes. those discussions have been of very prime quality and have been an essential component of the workshop.
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Additional resources for 3D Structure from Images — SMILE 2000: Second European Workshop on 3D Structure from Multiple Images of Large-Scale Environments Dublin, Irleand, July 1–2, 2000 Revised Papers
Here, we measure the goodness of a model by the geometric AIC [4,5,6], which is a special form of Akaike’s AIC . The model with the smallest geometric AIC is preferred. See  for other model selection criteria. 40 Y. Kanazawa and K. Kanatani homographies ........ affine transformations similarities rigid motions translations Fig. 4. Hierarchy of image transformations. 1 8-Parameter Homographies Let JˆH8 be the resulting residual of eq. (7). 2 2 (10) is estimated by eq. (9). 5-Parameter Homographies If the camera rotates by R around the center of the lens and changes the focal length from f to f , the resulting homography has the form H=F where F = diag(1, 1, −1 f ), f0 R F, F = diag(1, 1, (11) f ).
Although the renormalization algorithm dramatically reduces the instability of the mapping, as demonstrated in , it cannot remove the distortion completely. However, further improvement is theoretically impossible with this technique. In this paper, we will show that this limitation can be broken through by incorporating our knowledge about the source of the instability. , the group of translations, the group of rigid motions, the group of similarities, or the group of affine transformations.
SMILE 2000, LNCS 2018, pp. 35–51, 2001. c Springer-Verlag Berlin Heidelberg 2001 36 Y. Kanazawa and K. Kanatani (a) (b) Fig. 1. (a) If images with a very small overlap are used for mosaicing, a large distortion may result even in the presence of small noise. (b) Some part of the image may appear from the other side of the frame. In  this instability was demonstrated by using real images. An accurate algorithm was also presented for computing a homography from point correspondences using a technique called renormalization, which not only produces a statistically optimal solution but also evaluates the reliability of the computed solution in quantitative terms.