COLOR-ATTRIBUTES RELATED IMAGE RETRIEVAL

Student: Kylie Gorman Mentor: Yang Zhang

DEBUGGING

 Problem with data and not with classification  Rewrote pipeline  Continued with Bird 200 data set: 11,788 images  Began with Dense SIFT  Approximate accuracy known  Takes 3-4 days  First ran with only 60 categories instead of 200 to speed up process  Found small error after first day, switched to 40 categories

NEW PIPELINE

 Begin with extracting Dense SIFT features  Training and Testing  Calculate PCA codebook  Train only  Obtain feature matrices  Train and Test  Calculate GMM codebook  Train only  Get fisher vectors  Train and Test  Train, Classify, and Predict

MAIN CHANGES

 All Code  Fewer classes  Written specifically for Bird 200 dataset

CURRENT PROGRESS

 Completed Steps:   Extracted Dense SIFT Features  PCA codebook  Feature Matrices  GMM codebook  Fisher Vectors Current Progress   Training and Classifying By today  Calculate Precision  Determine if improvement was made

FUTURE GOALS

 Complete Pipeline today and throughout weekend  Calculate accuracy and determine if there was improvement  If no improvement, determine why  If improvement, compare our results with new color descriptor