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Homework answers / question archive / CMSC 426 Rotobrush Introduction The aim of this project is to segment deformable object from a given video sequence

CMSC 426 Rotobrush Introduction The aim of this project is to segment deformable object from a given video sequence

Computer Science

CMSC 426 Rotobrush Introduction
The aim of this project is to segment deformable object from a given video sequence. This
document just provides an overview of what you need to do. For a full breakdown of how each
step in the pipeline works.
Implementation Overview
Download the starter code and data here
A brief description of each step (you’ll implement the steps in bold):
myRotobrush.m : Wrapper function.
initLocalWindows.m : Creates local windows on boundary of mask.
initColorModels.m : Initializes color models.
initShapeConfidences.m : Initializes shape confidences.
localFlowWarp.m : Calculates local window movement based on optical flow
between frames.
calculateGlobalAffine.m : Finds affine transform between two frames.
updateModels.m : Update shape and color models.
CMSC426 Computer Vision

showLocalWindows.m : Plots local windows.
showColorConfidences.m : Plots the color confidence for each local window.
equidistantPointsOnPerimeter.m : Find equally spaced points along the perimeter of a
Point Distribution:
Setup Local Windows: 5 pts
Initialize Color Models: 10pts
Compute Color Model Confidence: 5 pts
Initialize Shape Model: 10 pts
Compute Shape confidence: 5 pts
Estimate Entire-Object Motion: 5 pts
Estimate Local Boundary Deformation: 10 pts
Update Color Model (and color confidence): 15 pts
Combine Shape and Color Models: 5 pts
Merge Local Windows: 10 pts
Extract final foreground mask: 20 pts
For extra credit, implement any remaining part of the SnapCut paper (other than mentioned
above). Be innovative! Try to make your system robust as much as possible! Hint: Try to have
additional image features, something beyond shape and color!
Project Files
When running MyRotobrush.m , it must load a set of frames from the folder Frames/ . Assume
that the frames will be jpeg images of the form 1.jpg , 2.jpg , etc. Your program must then
prompt the user to specify a region of interest in the first frame (for example using the roipoly
tool), and then track the specified object through the rest of the frames. For each frame, draw
the tracked boundary in red and save the result with the same filename in Output/ .
Functions Allowed
For this project, roipoly, fitgmdist, estimateGeometricTransform, opticalFlowFarneback, vl_sift
(, imfilter, conv2, imrotate, im2double, rgb2gray, fspecial,
imtransform, imwarp (and imref2d), meshgrid, sub2ind, ind2sub and all other plotting and matrix
operation/manipulation functions are allowed.
11/4/22, 9:49 AM Rotobrush 3/4
Submission Guidelines
We will deduct points if your submission does not comply with the following guidelines.
File tree and naming
Your submission on Canvas must be a zip file, following the naming convention For example, The file must have the following
directory structure:
*(any dependencies of MyRotobrush.m)
When run, MyRotobrush.m must load a set of images from Images/Input/, and return the
resulting panorama.
Output Videos
You have been provided the frames from five video clips. Run your code on each set of frames
and create videos, named as indicated above. For each video track the following:
Frames1: Track the turtle. Source: An underwater video captured by Chahat at
Lakshadweep islands, India.
Frames2: Track the motorcycle and rider. Source.
Frames3: Track the gymnast. Source.
Frames4: Track the powerlifter, without the weights. Source.
Frames5: Track the lizard (including tail). Source.
11/4/22, 9:49 AM Rotobrush 4/4
You will be graded primarily based on your report.
The most important part is to understand and explain why your algorithm is working or
not working on a given dataset. What do you think are the drawbacks of your code!?
We want you to demonstrate an understanding of the concepts involved in the project, and to
show the output produced by your code.
Include visualizations of the output of each stage in your pipeline (as shown in the system
diagram on page 2), and a description of what you did for each step. Assume that we’re familiar
with the project, so you don’t need to spend time repeating what’s already in the course notes.
Instead, focus on any interesting problems you encountered and/or solutions you implemented.
As usual, your report must be full English sentences, not commented code. There is a word
limit of 1500 words and no minimum length requirement.

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