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Applications of Light fields in Computer vision Week 2

Applications of Light fields in Computer vision Week 2. REU student: Amari Lewis P.H.D student: Aidean Sharghi. Applications of light fields in Computer Vision. The goals of this project is to examine : Object recognition Occlusion Detection 3D reconstruction of a scene.

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Applications of Light fields in Computer vision Week 2

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  1. Applications of Light fields in Computer visionWeek 2 REU student: Amari Lewis P.H.D student: AideanSharghi

  2. Applications of light fields in Computer Vision • The goals of this project is to examine : • Object recognition • Occlusion Detection • 3D reconstruction of a scene

  3. What is object recognition? • Given test image, we want to determine what the image is. • Steps for conventional object recognition: • Collect dataset • Divide into positive/ negative data • Extract features (ex: sift..) • Train a classifier for extracted features • Given a test image: Extract the features • Use the classifier to determine which object it is

  4. The problem • Conventional methods use 2d information of the objects for detection. • Example: a bottle and a picture of a bottle on a piece of paper.

  5. Lytro light field camera • Using the lytro camera we are able to include 3d information with one single shot. • The camera manages to capture all the light field direction, intensity and color.

  6. Light field camerahow it works…

  7. Stereo • The conventional way of capturing 3d information is using stereo • Finding the correspondents is difficult • However finding the correspondents can be avoided… \.

  8. epi • Epipolar plane images • Can be used to represent 3d information of the object • This project/research is based on using epi to describe the objects and increase the object recognition accuracy

  9. Steps: • Choose 5 categories for classification • Collect dataset using the light field camera • Extract the photos, using the lytro software

  10. 5 categories for dataset using light field camera • Bicycles • Bus • Trees/flowers • Buildings • trucks

  11. Ii. Collect dataset using the light field camera Tree

  12. iii. Refocus the image to the specific object bicycles

  13. Assignment • There has been a similar study to improve object recognition and tracking • Scale-invariant representation of light field images for object recognition and tracking • Ecolepolytechniquefederale de Lausanne (Switzerland)

  14. references • Ng, REN (2006). Digital light field photography (doctoral dissertation). Stanford University, Stanford, California.

  15. Thank you !!

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