Active Viewing in Toddlers Facilitates Visual Object Learning: An Egocentric Vision Approach

Sven Bambach, David Crandall, Linda B. Smith, Chen Yu


Early visual object recognition in a world full of cluttered visual information is a complicated task at which toddlers are incredibly efficient. In their everyday lives, toddlers constantly create learning experiences by actively manipulating objects and thus self-selecting object views for visual learning. The work in this paper is based on the hypothesis that active viewing and exploration of toddlers actually creates high-quality training data for object recognition. We tested this idea by collecting egocentric video data of free toy play between toddler-parent dyads, and used it to train state-of-the-art machine learning models (Convolutional Neural Networks, or CNNs). Our results show that the data collected by parents and toddlers have different visual properties and that CNNs can take advantage of these differences to learn toddler-based object models that outperform their parent counterparts in a series of controlled simulations.

Papers & Presentations

Paper PDF CogSci 2016

The IU Computer Vision Lab's projects and activities have been funded, in part, by grants and contracts from the Air Force Office of Scientific Research (AFOSR), the Defense Threat Reduction Agency (DTRA), Dzyne Technologies, EgoVid, Inc., ETRI, Facebook, Google, Grant Thornton LLP, IARPA, the Indiana Innovation Institute (IN3), the IU Data to Insight Center, the IU Office of the Vice Provost for Research through an Emerging Areas of Research grant, the IU Social Sciences Research Commons, the Lilly Endowment, NASA, National Science Foundation (IIS-1253549, CNS-1834899, CNS-1408730, BCS-1842817, CNS-1744748, IIS-1257141, IIS-1852294), NVidia, ObjectVideo, Office of Naval Research (ONR), Pixm, Inc., and the U.S. Navy. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the U.S. Government, or any sponsor.