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Application of light fields in computer visionAMARI LEWIS – REU STUDENT
AIDEAN SHARGHI- PH.D STUENT
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Main objective increase object recognition through using the EPI of light field images
Using the light field camera
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Using the Lytro light field camera
conventional methods- involve using 2D information Light field images- captures all 3D information in a single shot. Using the Lytro light field camera to collect dataset camera captures light field direction, intensity and color
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Datasets- 1. Collected own dataset using the Lytro light field camera
◦ Bikes◦ Buildings◦ Trees◦ Vehicles
- Studying the 7 different image perspectives
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2. Dataset from Switzerland using the iphone video◦ Buildings
– 50 categories- Ranging from 4-30 videos- Extracted 300 frames from each video
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Epipolar planar images- EPI It is a 2D representation or slice of an image
Taking the same line from each image and putting it on top of each other
Using the multiple shots taken from the camera and the extracted frames
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Light field
7 lines from each of the images concatenated- total of 1080
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Concatenated the 300 lines – total 720
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Implementing DCT Steps: Separate the RGB into 3 channels
Calculate the row-wise mean- calculates the mean of each row to create a vector
Calculate the DCT for each channels
Concatenate some coefficients, using as a feature vector (smaller)
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For classification Apply Principal component analysis (PCA) gmm- Gaussian mixture model Linear SVM
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Best Results Using this method on EPIs
◦ Lytro Light field camera dataset 77% accuracy
• Switzerland dataset 96% accuracy
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Thank you