Learning Generic Human Body Models

1. Würtz, R.P. (ed.): Organic Computing. Springer, Heidelberg (2008)

   Google Scholar 

2. Poggio, T., Bizzi, E.: Generalization in vision and motor control. Nature 431, 768–774 (2004)

   Article  Google Scholar 

3. Walther, T., Würtz, R.P.: Learning to look at humans - what are the parts of a moving body. In: Perales, F.J., Fisher, R.B. (eds.) AMDO 2008. LNCS, vol. 5098, pp. 22–31. Springer, Heidelberg (2008)

   Chapter  Google Scholar 

4. Walther, T., Würtz, R.P.: Unsupervised learning of human body parts from video footage. In: Proceedings of ICCV workshops, Kyoto, pp. 336–343. IEEE Computer Society, Los Alamitos (2009)

   Google Scholar 

5. Kumar, M.P., Torr, P.H.S., Zisserman, A.: Learning layered motion segmentations of video. International Journal of Computer Vision 76(3), 301–319 (2008)

   Article  Google Scholar 

6. Bear, M.F., Connors, B.W., Paradiso, M.A.: Neuroscience – Exploring the Brain, 3rd edn. Lippinscott Williams & Wilkins (2006)

   Google Scholar 

7. Kumar, M.P., Torr, P.H.S., Zisserman, A.: Objcut: Efficient segmentation using top-down and bottom-up cues. IEEE Trans. PAMI 32(3), 530–545 (2009)

   Article  Google Scholar 

8. Murphy, G.L.: The Big Book of Concepts. The MIT Press, Cambridge (2004)

   Google Scholar 

9. Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active shape models—their training and application. Comput. Vis. Image Underst. 61(1), 38–59 (1995)

   Article  Google Scholar 

10. Lee, Y.J., Grauman, K.: Shape discovery from unlabeled image collections. In: Proc. CVPR, pp. 2254–2261. IEEE, Los Alamitos (2009)

    Google Scholar 

11. Besl, P.J., McKay, N.D.: A method for registration of 3-D shapes. IEEE Trans. PAMI 14(2), 239–256 (1992)

    Article  Google Scholar 

12. Rusinkiewicz, S., Levoy, M.: Efficient variants of the ICP algorithm. In: Proc. 3rd Intl. Conf. 3D Digital Imaging and Modeling, pp. 145–152 (2001)

    Google Scholar 

13. Eriksen, R.D.: Image processing library 98 (2006), http://www.mip.sdu.dk/ipl98/

14. Elgammal, A., Muang, C., Hu, D.: Skin detection - a short tutorial (2009)

    Google Scholar 

15. Deng, Y., Manjunath, B.: Unsupervised segmentation of color-texture regions in images and video. IEEE Trans. PAMI 23(8), 800–810 (2001)

    Article  Google Scholar 

16. Christoudias, C., Georgescu, B., Meer, P.: Synergism in low-level vision. In: Proc. ICPR, Quebec City, Canada, vol. 4, pp. 150–155 (2002)

    Google Scholar 

17. Felzenszwalb, P.F., Huttenlocher, D.P.: Pictorial structures for object recognition. Int. J. Comput. Vision 61(1), 55–79 (2005)

    Article  Google Scholar 

18. Sminchisescu, C., Triggs, B.: Kinematic jump processes for monocular 3D human tracking. In: Computer Vision and Pattern Recognition, pp. I:69–76 (2003)

    Google Scholar 

19. Shotton, J., Blake, A., Cipolla, R.: Efficiently combining contour and texture cues for object recognition. In: British Machine Vision Conference (2008)

    Google Scholar 

20. Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient matching of pictorial structures. In: Proc. ICPR, vol. 2, pp. 66–73 (2000)

    Google Scholar 

21. Noriega, P., Bernier, O.: Multicues 2D articulated pose tracking using particle filtering and belief propagation on factor graphs. In: Proc. ICPR, pp. 57–60 (2007)

    Google Scholar 

22. Ferrari, V., Marin-Jimenez, M., Zisserman, A.: Progressive search space reduction for human pose estimation. In: Proc. CVPR, pp. 976–983 (2008)

    Google Scholar 

23. Niebles, J.C., Han, B., Ferencz, A., Fei-Fei, L.: Extracting moving people from internet videos. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 527–540. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

24. Marcin, E., Vittorio, F.: Better appearance models for pictorial structures. In: Proc. BMVC (September 2009)

    Google Scholar 

25. Kumar, M.P., Torr, P.H.S., Zisserman, A.: Efficient discriminative learning of parts-based models. In: Proc. ICCV (2009)

    Google Scholar 

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