Image Compositing and Matting

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Image Compositing and Matting

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Image Compositing and Matting. Introduction. Matting and compositing are important operations in the production of special effects. These techniques enable directors to embed actors in a world that exists only in imagination, or to revive creatures that have been extinct for millions of years. - PowerPoint PPT Presentation

Transcript of Image Compositing and Matting

Page 1: Image Compositing and Matting

Image Compositing and Matting

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Introduction Matting and compositing are important operations in

the production of special effects. These techniques enable directors to embed actors in a world that exists only in imagination, or to revive creatures that have been extinct for millions of years.

During matting, foreground elements are extracted from a film or video sequence.

During compositing, the extracted foreground elements are placed over novel background images.

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Traditional approaches to matting Traditional approaches to matting include blu

e-screen matting and rotoscoping. The former requires filming in front of an expe

nsive blue screen under carefully controlled lighting

The latter demands talent and intensive user interaction.

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Rotoscoping Rotoscoping --- the process of tracking conto

urs in a video sequence

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Basic problem of blue screen matting Given an image of a foreground object shot in

front of a backing color (blue screen or green screen or other colors)

Obtain a matte of the foreground object so that the foreground object can be blended into a new background image using the matte to produce a new composite image.

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Notations Let C = [R, G,B] denote a color with 0 ≤ R, G, B ≤ 1. Let denotes a transparency value with 0 ≤ ≤ 1. Foreground image color: Cf = [Rf ,Gf ,Bf ], f = 1 Backing (screen) color: Ck = [0, 0,Bk], k = 1 (assumi

ng blue screen) Original foreground object color: Co = [Ro,Go,Bo] Background image color: Cb = [Rb,Gb,Bb], b = 1 Composite image color: Cc = [Rc,Gc,Bc]

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Problem Statement Given Cf and Cb at corresponding pixels, and

Ck a known backing color, and assuming Cf = oCo + (1 − o)Ck

Determine o and Co, which then gives the composite color Cc = oCo + (1 − o)Cb at the corresponding point, for all points that Cf and Cb share in common.

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Solution Since Cf = oCo + (1 − o)Ck , we have:

4 unknowns, 3 equations…

Rf = oRo Gf = oGo

Bf = oBo + (1 − o)Bk .

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Case 1: No Blue There is no blue in Co, i.e., Bo=0, and Bk≠0. Then

This case is very restrictive. It rules out many colors, including grays

because grays have blue.

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Case 2: Gray and Skin Color Assume Ro=aBo (or Go=aBo) and Bk≠0 Then

where

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Example 1: Gray

Then

This case applies to science fiction movie in which the spaceships are mostly gray.

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Example 2: Skin Color

This case applies to human faces, hands, legs, etc.

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Solution for General Cases To solve the matting problem in general:

Need to take the same image with two different backing colors.

This gives four equations for solving the four unknowns

Case 1: Use Two Different Shades of Blue. Case 2: Use Two Different Backing Colors.

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Case 1 Use two different shades of blue Bk1 and Bk2 a

s backing colors.

Then

so

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Case 2 Use two different backing colors Ck1 and Ck2.

Or

Over-constrained, 1 unknowns, three equations

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Case 2: Solution 1 Adding up 3 equations:

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Case 2: Solution 2 Apply least squares method Define:

Then

Least-squares

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Least-Squares Set

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Case 1 Example

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Case 2 Example

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Other Developments in Matting Matting Without Blue Screen A method proposed by Ruzon and Tomasi

User specify object region and boundary region. Alpha value of object region is set to 1. Alpha value of boundary region is computed by es

timating the contributions of neighboring objects’ colors.

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Example

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Bayesian Approach

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Shadow Matting Pull a matte of shadow. Acquire photometric and geometric properties

of the target scene by sweeping oriented linear shadows across it.

Then, composite the shadow onto the scene.

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Example

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Environmental Matting

Left: alpha matte. Middle: environment matte. Right: photo.

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References1. Y.-Y. Chuang, B. Curless, D. H. Salesin, and R. Szeliski. A baye

sian approach to digital matting. In Proc. IEEE CVPR, pages II–264–II–271, 2001.

2. Y.-Y. Chuang, D. B. Goldman, B. Curless, D. H. Salesin, and R. Szeliski. Shadow matting and compositing. ACM Transactions on Graphics, 22(3):494–500, July 2003.

3. M. A. Ruzon and C. Tomasi. Alpha estimation in natural images. In Proc. IEEE CVPR, pages 18–25, 2000.

4. A. R. Smith and J. F. Blinn. Blue screen matting. In Proc. ACM SIGGRAPH, pages 259–268, 1996.

5. D. E. Zongker, D. M. Werner, B. Curless, and D. H. Salesin. Environment matting and compositing. In Proc. SIGGRAPH, pages 205–214, 1999.

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Digital Compositing Digital compositing means “digitally manipula

ted integration of at least two source images to produce a new image.”

The new image must appear realistic. It must be completely and seamlessly integrat

ed, as if it were actually photographed by a single camera.

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Example 1

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Example 2

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More examples http://www.beezlebugbit.com/digital/efx/efx_t

op.htm

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Main Topics Alpha blending: blending foreground and bac

kground Keying: separating foreground and backgrou

nd Luma, chroma, difference keying

Rig removal: removing unwanted elements

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Alpha Blending C = [α F + (1 – α) B] If α = 1, then C = F, foreground is shown, i.e.,

foreground is opaque. If α = 0, then C = B, background is shown, i.

e., foreground is transparent. 0 < α < 1: semi-transparent, e.g., shadow, sm

oke, etc. If α ranges from 0 to 255, then the formula be

comes: C = [α F + (1 – α) B] / 255

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Example: No Background

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Example: With Background

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Note For shadow, must take fractional value (0 <

α < 1). Otherwise, shadow looks unreal.

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Boundary area at boundary area should also be fractional.

Otherwise, have dark fringes; unrealistic.

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Summary A good matte ha

s fractional in shadow, and along object boundaries and shadow boundaries.

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Keying Separating foreground from background, crea

ting a matte of foreground. Also called pulling a matte (of foreground), or

keying out (i.e., making transparent) background.

Recall: A good matte has fractional a in shadow, and alon

g object boundaries and shadow boundaries.

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Basic methods Luma keying: based on luminance (i.e., inten

sity) Chroma keying: based on color (i.e., blue scr

een, green screen) Difference keying: requires a clean plate, i.e.,

a background image without the foreground element.

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Basic Idea Compute difference bet

ween foreground and background (based on luma, chroma, or color)

Very small diff = 0. Very large diff = 1. Intermediate diff inte

rmediate

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Luma Keying Key out the background based on luminance. Useful when background has a uniform lumin

ance that is very different from foreground luminance.

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Result

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Chroma Keying Key out the background based on color. Useful when background has a uniform color

that is very different from foreground color. Example: Image shot with blue screen.

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Characteristics of blue screen image

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Difference Keying More general than luma and chroma keying. Key out background based on pixel-wise color di

fference between foreground and background footage.

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Final Composition

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Rig Removals Rigs are equipment that support the actors or the pr

ops. Sometimes, rigs cannot be removed by keying alone. So, have to apply masking technique to remove rigs. Need clean plate of background footage. If camera moves, then need motion-controlled came

ra: Computer controls camera to move the same way t

wice: Without foreground objects; get clean plate. With foreground objects.

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Basic Idea Apply a mask to mask out the rig. Then, replace pixels in masked area by corre

sponding pixels in clean plate background. If rig moves in footage, then have to animate

the mask accordingly.