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Sequential updating of projective and affine structure from motion tg dating dc

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Martin Bujnak, Department of Computer Graphics and Image Processing Faculty of Mathematics, Physics and Informatics, Comenius University Bratislava, Slovakia. Martin Samuelcik Aim: To obtain 3D mesh of the scene from images captured by uncalibrated hand-held camera Key words: Structure-from-motion, Uncalibrated video, Self calibration, Feature tracking, Dense reconstruction, Radial lens distortion This thesis aims to create complete 3D reconstruction of real scene from uncalibrated video sequence.My work deals with image features correspondence problem reduced to feature tracking throughout image sequence, camera tracking with retrieving cameras positions and camera calibration, and finally dense scene reconstruction represented in 3D mesh.I emphasize the advantages of an approach based on fusing image-pair reconstructions.With regard to the projective approach, I argue that its trade-off of simplicity versus accuracy/robustness needs more careful experimental examination, and I advocate more research on the effects of calibration error on Euclidean reconstruction.The structure is updated sequentially over an image sequence, in contrast to schemes which employ a batch process.A specialisation of the algorithm to recover structure and camera position modulo an affine transformation is described, together with a method to periodically update the affine coordinate frame to prevent drift over time.Experimental method for lens radial distortion detection based on two-view geometry is also presented here.This thesis presented a sequential approach for creating calibrated motion and structure from un-calibrated video sequence with dense 3D reconstruction of the space.

In this work we address the problem of projective reconstruction from multiple views with missing data.

In this paper an approach is presented that obtains virtual models from sequences of images.

The system can deal with uncalibrated image sequences acquired with a hand held camera.

Based on tracked or matched features the relations between multiple views are computed.

From this both the structure of the scene and the motion of the camera are retrieved.