By Ingela Nyström, Johan Nysjö, Filip Malmberg (auth.), Halimah Badioze Zaman, Peter Robinson, Maria Petrou, Patrick Olivier, Timothy K. Shih, Sergio Velastin, Ingela Nyström (eds.)
The two-volume set LNCS 7066 and LNCS 7067 constitutes the court cases of the second one overseas visible Informatics convention, IVIC 2011, held in Selangor, Malaysia, in the course of November Sept. 11, 2011.
The seventy one revised papers offered have been conscientiously reviewed and chosen for inclusion in those complaints. they're equipped in topical sections named computing device imaginative and prescient and simulation; digital photo processing and engineering; visible computing; and visualisation and social computing. additionally the 1st quantity comprises keynote speeches in complete paper size, and one keynote abstract.
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Extra info for Visual Informatics: Sustaining Research and Innovations: Second International Visual Informatics Conference, IVIC 2011, Selangor, Malaysia, November 9-11, 2011, Proceedings, Part I
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3D Imaging in Medicine, 2nd edn. CRC Press, Inc. (2000) 11. : A framework for evaluating image segmentation algorithms. Computerized Medical Imaging and Graphics 30(2), 75–87 (2006) 12. : Visualization and Haptics for Interactive Medical I age Analysis. D. thesis, Uppsala University (2008) 13. org/x3d/ (accessed on April 27, 2011) 14. : Snakes, Shapes, and Gradient Vector Flow. IEE Transactions on Image Processing 7(3), 359–369 (1998) Evaluation of Unsupervised Segmentation Algorithms for Silhouette Extraction in Human Action Video Sequences Adolfo Mart´ınez-Us´o, G.
Foraging theory for dimensionality reduction of clustered data. 1007/s10994-009-5156-0 8. : SVD and Signal Processing II: Algorithms, Analysis andApplications. Elsevier Science (1991) 9. : Incremental PCA for OnLine Visual Learning and Recognition. In: Proceedings of the 16th International Conference on Pattern Recognition, pp. 781–784 (2002) 10. : Candid Covariance Free Incremental Principal Component Analysis. IEEE Transaction on Pattern Analysis and Machine Intelligence 25, 1034–1040 (2003) 11.
The evaluation of the quality of the results has been done by means of comparing the resulting silhouettes (R) to the ground-truth binary mask (GT ). To this end, three objective metrics have been used: – The first metric is an overlapping measure (OV) that has been often used in the literature [15]. It is quite simple but efficient. For each frame k of a sequence the following expression is worked out: OV (k) = 1 − GT ∩ R GT ∪ R (1) – The objective evaluation metric MPEGqm (MPEG quality measure) was proposed in [14] and has been widely adopted by the research community due to its simplicity.