VOC [@PASCAL] and a subset of the 1200 most frequently used words that denote visually identifiable objects [@wordbank]. To further augment our set of candidate categories, several children ranging in ages from 4 to 8 were asked to name every object they see in indoor and outdoor environments. The final 272 candidates may be found in [the appendix]{}. Finally, the co-authors voted on a 1 to 5 scale for each category taking into account how commonly they occur, their usefulness for practical applications, and their diversity relative to other categories. The final selection of categories attempts to pick categories with high votes, while keeping the number of categories per super-category (animals, vehicles, furniture, etc.) balanced. Categories for which obtaining a large number of instances (greater than 5,000) was difficult were also removed. To ensure backwards compatibility all categories from PASCAL VOC [@PASCAL] are also included. Our final list of 91 proposed categories is in Fig. \[fig:dataanalysis\](a).

Non-iconic Image Collection
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Given the list of object categories, our next goal was to collect a set of candidate images. We may roughly group images into three types, Fig. \[fig:iconic\]: iconic-object images [@berg2009finding], iconic-scene images [@SUN] and non-iconic images. Typical iconic-object images have 