Computer Vision -- ACCV 2014: 12th Asian Conference on by Daniel Cremers, Ian Reid, Hideo Saito, Ming-Hsuan Yang

By Daniel Cremers, Ian Reid, Hideo Saito, Ming-Hsuan Yang

The five-volume set LNCS 9003--9007 constitutes the completely refereed post-conference court cases of the twelfth Asian convention on desktop imaginative and prescient, ACCV 2014, held in Singapore, Singapore, in November 2014.

The overall of 227 contributions provided in those volumes used to be rigorously reviewed and chosen from 814 submissions. The papers are prepared in topical sections on acceptance; 3D imaginative and prescient; low-level imaginative and prescient and lines; segmentation; face and gesture, monitoring; stereo, physics, video and occasions; and poster classes 1-3.

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Extra info for Computer Vision -- ACCV 2014: 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part II

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Automatic camera recovery for closed or open image sequences. , Neumann, B. ) ECCV 1998. LNCS, vol. 1406, pp. 311–326. Springer, Heidelberg (1998) 17. : Reconstruction from uncalibrated sequences with a hierarchy of trifocal tensors. In: Vernon, D. ) ECCV 2000. LNCS, vol. 1842, pp. 649–663. Springer, Heidelberg (2000) 18. : 3D models from extended uncalibrated video sequences. In: Proceeding 3DIM (2005) 19. : Sparse appearance based modeling for robot localization. In: IROS (2006) 20. : Local readjustment for high-resolution 3D reconstruction (2014) 18 S.

We can see from Table 1 and Fig. 5 that, on both sequential and unstructured data sets, MVGC obviously outperforms key frame and skeletal graph in average camera position errors after bundle adjustment while improving the efficiency of bundle adjustment by almost a magnitude. Figure 7 gives the qualitative demonstration of the outstanding performance of our method. Figure 6 also provides the visual demonstration of the graph simplification result of the Trevi data set. 2 Applications in Multi-view Stereo Both on the benchmark and Internet data sets, we use full image sets for SfM and MVGC to select a subset of views for dense 3D reconstruction.

Comput. Vis. 8, 123–151 (1992) 7. : Direct least-squares fitting of ellipses. IEEE Trans. Pattern Anal. Mach. Intell. 21, 476–480 (1999) Camera Calibration Based on the Common Self-polar Triangle 29 8. : Camera calibration using spheres: a semi-definite programming approach. In: Proceedings of IEEE International Conference on Computer Vision, pp. 782–789 (2003) 9. : Camera calibration: a quick and easy way to determine the scale factor. IEEE Trans. Pattern Anal. Mach. Intell. 13, 1240–1245 (1991) 10.

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