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Image Processing and Pattern Recognition: 2D Multiple Object Tracking algorithm using SIFT and SVM

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Image Processing and Pattern Recognition: 2D object tracking

Alexandra Popov (12216685) Leroy Chika Anozie (12400952) Marcel Bühler (99211688)

28th of October 2015 designed with Matlab R2015a and VLFeat 0.9.20

----- How to start -----

run GUI.m in Matlab

----- GitHub URL -----

https://github.com/mbbuehler/kangoroo-tracking

----- Details -----

This object tracking algorithm uses different methods for finding key points and matching them. Using the GUI the are different parameters to select:

  1. Video: Choose the video you want to process, the initial rectangle is already set. You can choose from example videos from PrinctonTrackingBenchmark Website

  2. Matching algorithm: Choose between two matching algorithms a) euclidean distance b) SVM

  3. Display mode: Choose between rectangles or rectangles and actual key points

  4. Stop after very frame: Check if you want to see every frame before continuing manually

----- Modality of the code -----

  1. reading the images and preprocessing

  2. finding and describing the key points with VLFeat

  3. matching the key points from the neighbourhood: mode 1: matching key points with euclidean distance mode 2: matching key points using svm [trained with 99 tracking examples]

  4. Rectangles and (optionally) key points are showing the track of the selected object in the video

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