By Wei Zeng, Yun Zeng, Yang Wang, Xiaotian Yin, Xianfeng Gu, Dimitris Samaras (auth.), David Forsyth, Philip Torr, Andrew Zisserman (eds.)
The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed court cases of the tenth ecu convention on laptop imaginative and prescient, ECCV 2008, held in Marseille, France, in October 2008.
The 243 revised papers provided have been conscientiously reviewed and chosen from a complete of 871 papers submitted. The 4 books hide the complete variety of present concerns in desktop imaginative and prescient. The papers are prepared in topical sections on acceptance, stereo, humans and face acceptance, item monitoring, matching, studying and lines, MRFs, segmentation, computational images and lively reconstruction.
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Additional info for Computer Vision – ECCV 2008: 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part III
5 shows alignment results for examples with no obvious visual correspondence. Despite the lack of direct visual correspondence, the scene alignment algorithm attempts to rebuild the house (17), change the shape of the door into a circle (18) or reshuﬄe boats (20). Some failure cases are shown in Fig. 6. Typically, these are caused 36 C. Liu et al. by the lack of visually similar images in the video database. Note that, typically, alignment improves ranking of the K-nearest neighbors. This is illustrated in Fig.
The SIFT descriptors are quantized into visual words in (c). In order to improve the clarity of the visualization by mapping similar cluster centers to similar colors, cluster centers have been sorted according to the ﬁrst principal component of the SIFT descriptor obtained from a subset of our dataset. An alternative visualization of the continuous values of the SIFT descriptor is shown in (d). e. the ﬁrst component is mapped into R+G+B, the second is mapped into R-G and the third into R/2 + G/2-B).
224–237. Springer, Heidelberg (2004) 8. : A search engine for 3d models. In: ACM TOG, pp. 83–105 (2003) 9. : Shape distributions. In: ACM TOG, vol. 21, pp. 807–832 (2002) 10. : Expression-invariant representations of faces. IEEE Trans. Image Processing 16(1), 188–197 (2007) 11. : Correspondence labelling for wide-timeframe free-form surface matching. In: ICCV (2007) 12. : Fusion of summation invariants in 3d human face recognition. In: CVPR (2006) 13. : A fast 3d correspondence method for statistical shape modeling.