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 together with the 6th ecu convention in machine imaginative and prescient at Trinity collage Dublin. the topic of the workshop was once the visible acquisition of versions of the 3D global from photographs and their software to digital and augmented fact. over the past few years super development has been made during this quarter. at the one hand very important new insightshavebeenobtainedresultinginmore exibilityandnewrepresentations.Onthe different hand a few recommendations have come to adulthood, yielding powerful algorithms supplying reliable effects on actual photograph info. additionally aiding applied sciences – similar to electronic cameras, desktops, disk garage, and visualization units – have made issues attainable that have been infeasible quite a few years in the past. beginning the workshop was once Paul Debevec s invited presentation on image-based modeling,rendering,andlighting.Hepresentedanumberoftechniquesforusingdigital pictures of genuine scenes to create 3D versions, digital digital camera strikes, and real looking laptop animations.Theremainderoftheworkshopwasdividedintothreesessions:Computation and Algorithms, visible Scene Representations, and prolonged Environments. After every one consultation there has been a panel dialogue that integrated all audio system. those panel discussions have been geared up by means of invoice Triggs, Marc Pollefeys, and Tomas Pajdla respectively, who brought the subjects and moderated the dialogue. Asubstantialpartoftheseproceedingsarethetranscriptsofthediscussionsfollowing every one paper and the complete panel periods. those discussions have been of very prime quality and have been an essential component of the workshop.
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Extra 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
If you have more occlusion, more complex structure, you will probably have to use more frames. David Nister: That is right, and this is taken into account in the sense that if there is a lot of occlusion, the homography is not enough to compensate between frames, leading to a low correlation and thus also more frames. The selection would of course benefit from more precise knowledge of the structure, but this is estimated much higher up in the system. The frame decimation requires on the order of a second per frame, while the structure and motion system uses on the order of minutes per frame, so I do not know the exact occlusions until much later.
There is also work done on reference view selection for view synthesis, but it is then usually assumed that the cameras are calibrated extrinsically and intrinsically beforehand and I do not want to do this since my main motive is to limit the computational complexity and as a consequence, view selection is the first thing I do. Rick Szeliski, Microsoft: I like the idea that you have of not keeping the motion blurred frames. That seems like a good idea although for feature tracking it may not be that important.
Kanazawa and K. Kanatani By this transformation, the image is rotated by angle θ around the origin, scaled by s, and translated by (t1 , t2 ). If we define → xα = xα /f0 yα /f0 cos θ − sin θ sin θ cos θ eq. (7) is rewritten in the following form: R= J= 1 N N → → xα , → , → xα /f0 yα /f0 = → τ= , t1 /f0 t2 /f0 → (21) , → (22) → ( x α − sR xα − τ , Wα ( x α − sR xα − τ )), (23) α=1 → → Wα = s2 RV0 [ xα ]R + V0 [ x α ] −1 . (24) This is minimized by the LM method (we omit the details). See Appendix C for the procedure for computing an initial guess.