The hypothesis that image datasets gathered online “in the wild“ can produce biased object recognizers, e.g. preferring professional photography or certain viewing angles, is studied.
A new “in the lab“ data collection infrastructure is proposed consisting of a drone which captures images as it circles around objects.
It's inexpensive and easily replicable nature may also potentially lead to a scalable data collection effort by the vision community.
The procedure's usefulness is demonstrated by creating a dataset of Objects Obtained With fLight (OOWL).
Currently, OOWL contains 120,000 images of 500 objects and is the largest “in the lab“ image dataset available when both number of classes and objects per class are considered.
OOWL "In the Wild"
This work was partially funded by NSF awards IIS-1546305 and IIS-1637941, a gift from Northrop Grumman, and NVIDIA GPU donations.