Depth Edge Detection with Multi-Flash Imaging

Gabriela MartínezFinal Project – Processamento de Imagem

IMPA

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.

Method

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

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.

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

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.

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

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.

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

Results

● Ambient Edges

Results

● Ambient Edges

Results

● Ambient Edges

Results

● Ambient Edges

Results

● Ambient Edges

Results

● Edges Color

Results

● Edges Color

Results

● Edges Color

Results

● Edges Color

Results

● Edges Color