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Georgia Tech's
Computational Photography
Portfolio
Apurva Gupta
apurva.gupta@gatech.edu
PHOTO-MOSAIC
not ‘Pixel Perfect’, but ‘Picture Perfect’
Final Project
Slice Source
image into
tiles
Resize images
from the image
corpus keeping
their aspect ratio
Find average
brightness of each
color channel of the
corpus images
Compare the
distance of the
average brightness
of each image with
the average
brightness of source
image.
Replace each pixel
in the source image
with the image
with the least
distance
PHOTO-MOSAIC
not ‘Pixel Perfect’, but ‘Picture Perfect’
Average Brightness
Median Brightness
Assignment #1
A Photograph is a Photograph
Camera: NIKON COOLPIX S3100
F-Stop: f/5.5
Exposure time: 1/1000 sec
ISO speed: ISO-80
Focal length: 18mm
Exposure bias: 0 step
Max aperture: 3.4
Metering Mode: Pattern
Flash Mode: No Flash
Dimension: 3240 X 4320
The Capitol
Assignment #2
Black and White
Used nested loop to traverse each pixel and checked the threshold value of 128. Value greater that 128 corresponded to 255
while the smaller one was changed to 0.
Horizontal Flip
Used nested loop to traverse each column in the image matrix. The (x,y) pixel values in each column was replaced with the
value of (x, height-y) pixel value and stored in another 2D array.
Average of two images
Used nested loop to traverse the images and added the (x,y)th pixels of both the images and divided the
values by 2. This was stored in a 2D array.
Assignment #3
Epsilon Photography
Epsilon Photography
Ghosts on Road
Assignment #4
Camera Obscura
The Setup
Pin Hole was created by covering the window.
Pinhole
The Image
This wasn’t
visible through
eye but came
up well on
camera. The
edges are not
sharp since it
was a big pin
hole. The
building
specifics were
not visible at
all but the sky
came out really
good.
The Image
Assignment #5
Gradients and Edges
X Gradient
For the X gradient, I
subtracted the ith pixel from
i+1th pixel looping through the
columns.
For the Y gradient, I subtracted
the ith pixel from i+1th pixel
looping through the rows.
Y Gradient
Original image
Kernel image
Black and white image
Threshold - 100
Original image
Kernel image
Black and white image
Threshold - 150
Edge Detection
Assignment #6
Blending
Output
Black
White
Mask
BlackWhite
Mask
Output Output
When converting the output to grayscale, it looks as It there
is shadow of tree on the surface .
To create this mask, I took the Black image and using the
threshold of 128 and changed the pixel value to 0 or 255
Black White Mask Output
Similarly I created masks for black image and tried to blend it with the white image.
I tried these with various threshold values to create masks and check the resultant
blending.
Mask OutputMask Output
Assignment #7
Feature Detection and Matching
Score: 3/10
Lighting
Score: 2/10
Rotation
Score: 4/10
Sample
Score: 10/10
Scale
Assignment #8
Panorama
Sample Panorama created using inbuilt Phone feature
Assignment #9
Photos of Space
Photosynth
Ford Museum + Campionile
Link to Photosynth
Site 2 (Campionile)
Link to Photosynth
Panorama
Campionile
Link for Panorama
Photosphere
Campionile + Labspace
Photosphere of Campionile
Photosphere of Labspace
Assignment #10
HDR
Output with the given set of
images
Output with the given set of images on the right.
Output with the given set of images on the right.
Assignment #11
Video Textures
Output Link:
https://drive.google.com/file/d/0B5Ncl02d4dOeS2JxeVIycEVMdmc/view?usp=sharing
https://drive.google.com/file/d/0B5Ncl02d4dOeNjVXS3BEa0pLeFU/view?usp=sharing

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