@inproceedings{47eb67e110cd4a179db24c461afb15f4,
title = "Self-calibrating active depth perception via motion parallax",
abstract = "A hallmark of biological systems is their ability to self-calibrate sensory-motor loops during their development. Understanding the principles of such self-calibration will enable the design of robots with similar autonomous learning abilities. Here we consider the problem of active depth perception based on motion parallax. When an observer moves sideways while looking at an object with a single eye, the eye rotation necessary to keep the object at the center of gaze provides information about the object's distance. Based on the recently proposed active efficient coding (AEC) approach, we present a self-calibrating system which autonomously learns to represent image motion and perform compensatory eye rotations to keep the object fixated during side-to-side movements - thereby learning to actively estimate the object's distance. A neural network is used to provide a calibrated depth estimate. We evaluate the system's performance in simulation and in a hardware implementation.",
keywords = "Active Depth Perception, Active Efficient Coding, Autonomous Learning, Motion Parallax, Self-Calibration",
author = "Tanapol Prucksakorn and Sungmoon Jeong and Jochen Triesch and Hosun Lee and Chong, \{Nak Young\}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, ICDL-EpiRob 2016 ; Conference date: 19-09-2016 Through 22-09-2016",
year = "2017",
month = feb,
day = "7",
doi = "10.1109/DEVLRN.2016.7846798",
language = "English",
series = "2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, ICDL-EpiRob 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "103--108",
booktitle = "2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, ICDL-EpiRob 2016",
address = "United States",
}