Difference between revisions of "SoC 2008 Masking in GUI"

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==Introduction==
 
The objective of this project is to provide the user with an easy to use interface for quickly creating blending masks. After the images are aligned and shown in the preview window, users will have the option of creating blending masks. Currently the goal is to provide option for mask creation in the preview window. Since it already shows the aligned images, it would be easier for users to create appropriate masks when all the images aligned.
 
The objective of this project is to provide the user with an easy to use interface for quickly creating blending masks. After the images are aligned and shown in the preview window, users will have the option of creating blending masks. Currently the goal is to provide option for mask creation in the preview window. Since it already shows the aligned images, it would be easier for users to create appropriate masks when all the images aligned.
  
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==Project Outline==
  
 
'''Editing Features'''
 
'''Editing Features'''
----
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*Option for zooming in/out
 
*Option for zooming in/out
 
*Set brush stroke size
 
*Set brush stroke size
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'''Project Plan'''
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==Timeline==
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1. Before Start of Coding Phase:  
 
1. Before Start of Coding Phase:  
 
* Determine input data type, format  and how the user will interact
 
* Determine input data type, format  and how the user will interact
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2.1 Before Mid Term Evaluation
 
2.1 Before Mid Term Evaluation
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Implement a basic framework that can –
 
Implement a basic framework that can –
 
* take an image stack of a particular format.
 
* take an image stack of a particular format.
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* perform image segmentation on the stack of images (3D segmentation problem where the user will only need to roughly mark the region on a small subset of the images)
 
* perform image segmentation on the stack of images (3D segmentation problem where the user will only need to roughly mark the region on a small subset of the images)
 
At the end of this stage the segmentation algorithm should be able to correctly identify similar region in successive images.
 
At the end of this stage the segmentation algorithm should be able to correctly identify similar region in successive images.
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==References==
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[1] Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images
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[http://www.csd.uwo.ca/~yuri/Abstracts/iccv01-abs.html webpage]
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[2] Lazy Snapping [http://research.microsoft.com/~jiansun/papers/LazySnapping_SIGGRAPH04.pdf paper] [http://research.microsoft.com/~jiansun/videos/LazySnapping_Tiny.wmv video]
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[3] Interactive Digital Photomontage [http://grail.cs.washington.edu/projects/photomontage/ webpage]
  
 
[[Category:Community:Project]]
 
[[Category:Community:Project]]

Revision as of 05:23, 9 May 2008

Introduction

The objective of this project is to provide the user with an easy to use interface for quickly creating blending masks. After the images are aligned and shown in the preview window, users will have the option of creating blending masks. Currently the goal is to provide option for mask creation in the preview window. Since it already shows the aligned images, it would be easier for users to create appropriate masks when all the images aligned.

Project Outline

Editing Features

  • Option for zooming in/out
  • Set brush stroke size
  • Polygon editing mode for fine-tuning boundary regions


Timeline

1. Before Start of Coding Phase:

  • Determine input data type, format and how the user will interact
  • Construct a preliminary design of the software
  • Outline of how the algorithm will work
  • Finalize the scope of the project

2. Coding Phase:

2.1 Before Mid Term Evaluation

Implement a basic framework that can –

  • take an image stack of a particular format.
  • allow users to mark regions
  • incorporate algorithm to learn the color model from the user defined area
  • start implementing 2D multi-label image segmentation

2.2 After Mid Term Evaluation

  • perform image segmentation on the stack of images (3D segmentation problem where the user will only need to roughly mark the region on a small subset of the images)

At the end of this stage the segmentation algorithm should be able to correctly identify similar region in successive images.

References

[1] Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images webpage

[2] Lazy Snapping paper video

[3] Interactive Digital Photomontage webpage