Depth Edge Detection with Multi-Flash Imaging

1. Gabriela Martínez Final Project – Processamento de Imagem IMPA Depth Edge Detection with Multi-Flash Imaging

2. Introduction • Classic: given a single two dimensional image, how can one detect edges of important features?? • Ramesh et al, introduce an algorithm based on multi-flash imaging, input: 5 images.

3. Method • The algorithm needs minimum of five images: Ambient, and four flashes images positioned above, below, right and left of the lens.

4. Method • To detect an edge passing trough a pixel, consider the epipolar ray corresponding to the line between the flash and the pre-image of the pixel.

5. Algorithm Description • Ambient Image A • n pictures with a light source Fk+ • Fk=Fk+-A • For all pixels x, Fmax(x)=maxk(Fk(x)) • For each k create Rk(x)=Fk(x)/Fmax(x) • For each Rk traverse epipolar ray ek • Find pixels y with negative transition, mark y

6. Depth edge detection has been reduced to an intensity edge detection. It is easy to solve using Sobel kernel convolution. Remarks • The value of ratio images at “flash” pixels is roughly1; for “shadowed” pixels, the value is close to 0. • Intensity shows a sharp negative transition.

7. Implementation • The algorithm was implemented in matlab. To solve the intensity edge detection problem use Sobel kernel, generated by fspecial, and then use imfilter. • Threshold: After computing the confidence map, separate it in two images (low confidence 0.5, high confidence 1) then connect them using bwlabel

8. Comments • The algorithm is easy to implement and it requires little computation. • A robust classification to distinguish depth edges from texture edges. • Making use of the epipolar relationship between flash and cast shadows to extract geometric features theres no need to create 3D scene reconstruction.

9. References • Ramesh et al. Non-photorealistic Camera: Depth Edge Detection and Stylized Rendering using Multi-Flash Imaging. ACM Siggraph 2004. • Tien-Tsin Wong. Solving Visibility with Epipolar Geometry. The Chinese University of Hong Kong. • Gonzalez R. Woods R. Digital Image Processing Using Matlab. Editorial Prentice Hall

10. Results • Ambient Edges

11. Results • Ambient Edges

12. Results • Ambient Edges

13. Results • Ambient Edges

14. Results • Ambient Edges

15. Results • Edges Color

16. Results • Edges Color

17. Results • Edges Color

18. Results • Edges Color

19. Results • Edges Color