Figure 1.

Performance of the bag-of-features classifier using 100 feature clusters. (Left) Classification accuracy given training on the 10 largest categories in the Caltech 101 sample set. Colored lines show accuracy for specific categories, while dashed black lines show overall accuracy for each level of training complexity. (Right) Accuracy by a classifier trained on 102 categories during a test in which n stimuli must be classified correctly for a trial to be “correct.” Performance for the classifier's 10 best (black) and worst (white) categories was gauged. Solid lines indicate cases in which classification was done perfectly, while dashed lines indicate cases where correct responses required at least one guess.