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Week 5 Report. Shelby Thompson. This week…. 1 research paper Coded more Used PubFig83 dataset to run tests on. Using the PubFig83 dataset…. Used training, testing and image IDs Compute pairwise distance between images Did so by computing cosine distance between matrix rows.
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Week 5 Report Shelby Thompson
This week… • 1 research paper • Coded more • Used PubFig83 dataset to run tests on
Using the PubFig83 dataset… • Used training, testing and image IDs • Compute pairwise distance between images • Did so by computing cosine distance between matrix rows
Using PubFig83 dataset… • Next created a zero matrix as big as distance matrix • Iterated over the training and testing IDs • If the train and test IDs were equal set that spot in the zero matrix to 1
Created kNN graph… • Iterated over the distance matrix • Sorted it in declining order • Found top 5 k-neighboors • Set all other rows in the matrix to 0
Created kNN graph (cont)… • Iterated over each row/threshold • Iterate based on (i,i) where I is row number • Set all rows above threshold to 0 or Inf (they appear different)
Research Paper A Survey of Recent Advances in Face Detection By: Cha Zhang and Zhengyou Zhang (Briefly reviewed this article)
Article Focus… • Review past decade of development in face detection • Uses Viola-Jones face detector • Survey other algorithms and feature extractors • Goal is to find the best algorithm
Experiment… • The authors focused more on surveying and researching current face detection methods • Examined different face detection methods and how they improved • Focus on boosted algorithms, like AdaBoost • Examined popular programs like iPhoto and Picassa
Goals for next week… • Continue to work on my codes • Experiment with writing some of my MatLab code in Java • Find out what Enrique wants me to do next