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

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Presentation on theme: "Depth Edge Detection with Multi- Flash Imaging Gabriela Martínez Final Project – Processamento de Imagem IMPA."— Presentation transcript:

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

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 F k+ ● F k =F k+ -A ● For all pixels x, F max (x)=max k (F k (x)) ● For each k create R k (x)=F k (x)/F max (x) ● For each R k traverse epipolar ray e k ● Find pixels y with negative transition, mark y

6 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. ● Depth edge detection has been reduced to an intensity edge detection. ● It is easy to solve using Sobel kernel convolution.

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 ● AmbientEdges

11 Results ● AmbientEdges

12 Results ● AmbientEdges

13 Results ● AmbientEdges

14 Results ● Ambient Edges

15 Results ● Edges Color

16 Results ● Edges Color

17 Results ● Edges Color

18 Results ● Edges Color

19 Results ● Edges Color


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