3D Object Reconstruction Using Multiple Linear Light Sources in Image Scanner

Advisor ：趙春棠 Chun-Tang ChaoMaster ：鍾明軒 Ming-Hsuan Chung

01

Outline ABSTRACT INTRODUCTION

• Image scanner• Photometric models

Purpose Materials and Methods

• 3D shape estimation using two groups of two light sources• Surface normal vectors and color estimation• Specular components estimation

EXPERIMENTAL RESULTS• Shape estimation by two groups of two light sources• Specular estimation by multiple light sources• Shape and specular estimation for complex object

CONCLUSION FUTURE WORKS REFERENCES

02

Abstract

• Discusses a 3D shape measurement device based on an image scanner.

• Shape reconstruction method using the image scanner is one of the photometric stereo method applied to multiple linear light sources.

03

INTRODUCTION

• The reflectance intensity on the object surface depends on the object shape, color, specular components and so on.

• It is difficult to estimate these components directly from only one image intensity, therefore the photometric stereo method which uses some images have been developed.

• Employ the iterative process in which the shape, color and specular reflection components are estimated alternatively.

• Propose new method to estimate object shape, color and specular components at each point on a surface using several images taken by light sources located at different positions.

• In experiments, by using synthetic scanned images we discuss optimal position and number of light sources to estimate object shape and specular components.

04

INTRODUCTION• Image scanner

Figure01. Image scanner

05

INTRODUCTION

Figure02. Arrangement of K1 Figure03. Arrangement of K2

• Image scanner

06

INTRODUCTION

Charge-coupled Device

• Image scanner

07

INTRODUCTION• Photometric models

Equation 01. The illuminant intensity is attenuated according to the distance from the light source

Equation 02. The Lambertian reflectance property on the object surface

08

INTRODUCTION

Equation 03. Torrance-Sparrow’s model

Equation 04. Cosθ (x, y) in Torrance-Sparrow’s model

Figure4. Vectors of specular reflection

Equation 05. γ(i) (x, y) in Torrance-Sparrow’s model

09

• Photometric models

INTRODUCTION

Equation 08. The photometric model of the reflectance intensity

Equation 09. The photometric model of the reflectance intensity considering only the Lambertian reflection in our method.

10

• Photometric models

Purpose

• A method to recover object shape, color and reflectance properties from scanned images taken by an image scanner.

• These devices are usually very expensive for the general person to use it.

• The calibration operation and the treatment is troublesome.

• It can be also used as a low cost and easy operating shape scanner.

11

Materials and Methods

Figure05. Outline of method

12

Materials and Methods• 3D shape estimation using two groups of two light sources

Figure06. Arrangement of two light source(a)_Same direction from a point on the object surface

Equation 10. The ratio of these photometric models is derived as a equation only for z.

13

Materials and Methods

Figure06. Arrangement of two light source(b)_Two groups of light sources

Equation 11. The ratio of these photometric models is derived as a equation only for z.

14

• 3D shape estimation using two groups of two light sources

Materials and Methods• Surface normal vectors and color estimation

Equation 12. The surface normal vector (nx, ny, nz) and color (the Lambertian albedos) ρ(c) (c = {r, g, b}) at (x, y) on the object surface are estimated by minimizing

Equation 13. The surface normal vector (N) and the direction of light source (Li) is smaller than a threshold angle (t2)

15

Materials and Methods

Equation 14. The specular reflection PS(ic)(x, y)

Equation 15. Equation is a linear equation about log ρs(c) and 1/σ2

(c)

16

• Surface normal vectors and color estimation

Materials and Methods

Equation 16. The linear least squares

Equation 17. Include only the Lambertian reflection (no specular reflection)

17

• Surface normal vectors and color estimation

Materials and Methods

Equation 18. The surface normal vector (N) and the direction of

light source (Li) is smaller than a threshold angle (t2)

• 3D shape estimation using two groups of two light sources

18

EXPERIMENTAL RESULTS• Shape estimation by two groups of two light sources

Figure08. Input scanned images

Table01. ALBEDO VALUES ON VIRTUAL HEMISPHERE

19

EXPERIMENTAL RESULTS

Figure07. Arrangement of light sources in shape estimation

20

• Shape estimation by two groups of two light sources

EXPERIMENTAL RESULTS

Figure09. Estimated shapes

21

• Shape estimation by two groups of two light sources

EXPERIMENTAL RESULTS

Figure10. Cross-section view of estimated shapes

22

• Shape estimation by two groups of two light sources

EXPERIMENTAL RESULTS

Figure11. RMS errors of height z

23

• Shape estimation by two groups of two light sources

EXPERIMENTAL RESULTS• Specular estimation by multiple light sources

Figure12. Arrangement of light sources in specular estimation

24

EXPERIMENTAL RESULTS

Figure13. Finally estimated shapes

25

• Specular estimation by multiple light sources

EXPERIMENTAL RESULTS

Figure14(a). Finally estimated shapes components

20 light sources26

• Specular estimation by multiple light sources

EXPERIMENTAL RESULTS

Figure14(b). Finally estimated shapes components

10 light sources27

• Specular estimation by multiple light sources

EXPERIMENTAL RESULTS

Figure14(c). Finally estimated shapes components

6 light sources28

• Specular estimation by multiple light sources

EXPERIMENTAL RESULTS• Shape and specular estimation for complex object

Figure15. Part of input scanned images of complex object

29

EXPERIMENTAL RESULTS

Figure16. Estimated shapes of complex object

30

• Shape and specular estimation for complex object

EXPERIMENTAL RESULTS

Figure17. Estimated specular components of complex object31

• Shape and specular estimation for complex object

CONCLUSION

• Discuss the method to measure the 3D shape, color and specular reflections of the object from scanned images using the image scanner.

• Propose the shape estimation method using two groups of two light sources located in same direction.

• The surface normal vectors, color and specular components estimation method using several light sources located on a circular path.

32

FUTURE WORKS

• Discuss the method to estimate specular components accurately using active moving light sources

• Examine the effectiveness of the proposed method using the actual scanner

33

REFERENCES

• [1] H.Ukida and K.Konishi, “3D Shape Reconstruction Using Three Light Sources in Image Scanner,” IEICE Trans. on Inf. & Syst., Vol.E84-D, No.12, pp.1713–1721, Dec. 2001.

• [2] R.J.Woodham, “Photometric Method for Determining Surface Orientation from Multiple Images,” Optical Engineering, Vol.19, No.1, pp.139– 144, 1980.

• [3] H. Ukida, Y.Tanimoto, T.Sano and H.Yamamoto, “3D shape, color and specular estimation using an image scanner with multiple illuminations,” Measurement Science and Technology, Vol.20, 104014, 10pp, 2009.

• [4] H. Ukida, Y.Tanimoto, T.Sano and H.Yamamoto, “3D Object Shape and Reflectance Property Reconstruction Using Image Scanner,” 2009 IEEE InternationalWorkshop on Imaging System and Techniques Proceedings, May 2009.

• [5] K.E.Torrance and E.M.Sparrow, “Theory for off-specular reflection from roughened surfaces,” In Journal of Optical Society of America, Vol.57, No.9, pp.1105–1114, 1967.

34