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HK UST * Hong Kong University of Science and Technology HK UST Modeling Hair from Multiple Views Y. Wei, E. Ofek, L. Quan and H. Shum.

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Presentation on theme: "HK UST * Hong Kong University of Science and Technology HK UST Modeling Hair from Multiple Views Y. Wei, E. Ofek, L. Quan and H. Shum."— Presentation transcript:

1 HK UST * Hong Kong University of Science and Technology HK UST Modeling Hair from Multiple Views Y. Wei, E. Ofek, L. Quan and H. Shum

2 HK UST Hair is a defining characteristic of human appearance

3 HK UST Overview Related work Principle of our approach Implementation Experimental results Conclusion

4 HK UST Related work Manual modeling Hadap and Magnenat-Thalmann 00, Kim et al. 02 (-) Tedious user interaction

5 HK UST Related work Image based rendering Matusik et al. 02 (+) Photo-Realistic (-) Long capture, Large storage (-) No animation

6 HK UST Related work Image based modeling – Difficult due to insufficient image resolution Typically 500 pixels for 50,000 hair fibers – Hair strands, groups of hair fibers, are visible Paris et al. 04, Grabli et al. 02

7 HK UST Paris et al. 2004 Hundreds of images Fixed view point Controlled and variable illuminations (+) Impressive results (-) Complex capturing (-) Controlled illumination (-) limited visibility

8 HK UST Our goals Modeling from multiple view points Easy capturing Complex hair styles Enable capturing dynamic scenes

9 HK UST Image Capturing Hand-Held camera Natural illumination condition

10 HK UST 2D image orientation of hair strands 2D orientation map Using oriented filter as in Paris’ work

11 HK UST 3D direction in one view 2D direction constrains the growth direction to a plane in space. Hair segment

12 HK UST Two images define a unique 3D direction 3D direction in two views D = N x N’ D N N’

13 HK UST Each image pair defines a unique direction 3D direction in multi-views Multiple images – Linear optimization D D minimizes Where ║ D ║ = 1 ΣjΣj (N j · D) 2 σj2σj2 2D orientation confidence NjNj

14 HK UST 3D Hair Growth according to 2D orientation Hair segment Hair fiber – a sequence of chained segments Initial growth direction – outward from scalp

15 HK UST Implementation Camera calibration Hair volume definition and fiber initialization Fiber growth and visibility determination Growth termination

16 HK UST Camera calibration Automatic calibration – quasi-dense approach (Lhuillier and Quan 05)

17 HK UST Hair volume S hair S hair, hair surface – Estimated from images

18 HK UST Approximating S hair using visual hull

19 HK UST Hair volume S scalp S scalp, scalp surface Generic head model Offset of S hair Ellipsoid

20 HK UST Hair initialization Generate root points on S scalp Define hair coverage of S scalp by projection on hair masks

21 HK UST Fiber Visibility Visible P – visibility determined by hair surface geometry P

22 HK UST Fiber Visibility P internal: Visibility is determined by the closest surface point. S hair P’ P

23 HK UST Fiber Visibility P internal: The deeper P is, the smoother the growth direction.

24 HK UST Growth Termination Exceeds pre-defined length Grows outside the hair bounding surface Large inconsistency between views S scalp S hair Visual hull

25 HK UST An Example of Hair Growth

26 HK UST An Example of Hair Growth

27 HK UST Experiments : Dark Hair

28 HK UST Smooth hair

29 HK UST

30 Curly hair

31 HK UST Conclusions Multi view approach Simple capture Open possibilities for hair motion capture. Automatic process (masks are still manual). High quality results.

32 HK UST Future work Capturing of dynamic hair using a set of multiple cameras Recovery of hair appearance

33 HK UST Previous work appear by courtesy of Sylvain Paris, Tae-Yong Kim and Wojciech Matusik. Some rendering provided by Florence Bertails, Hubert Nguyen Thanks

34 HK UST Previous work appear by courtesy of Sylvain Paris, Tae-Yong Kim and Wojciech Matusik. Some rendering provided by Florence Bertails, Hubert Nguyen Thanks

35 HK UST Thank You! HK UST

36 Hair fibers – too small to be captured 2D image orientation of hair strands Yet, hair strands are visible. 2D orientation map

37 HK UST Principle of our approach Using multiple view images – Ease of capturing – Strong geometry information 3D orientation from triangulation of 2D orientations Better estimation of head geometry Better visibility – Robustness from high data redundancy Automatic process

38 HK UST Using oriented filter as in Paris’ work Computation of 2D orientation of hair strands 2D orientation map (color coded)


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