Authors:
Pramod Chandrashekhariah
;
Gabriele Spina
and
Jochen Triesch
Affiliation:
Johann Wolfgang Goethe University, Germany
Keyword(s):
Active Vision, Unsupervised Learning, Autonomous Vision System, Vision for Robotics, Humanoid Robot,
iCub, Object Recognition, Visual Attention, Stereo Vision, Intrinsic Motivation.
Related
Ontology
Subjects/Areas/Topics:
Active and Robot Vision
;
Computer Vision, Visualization and Computer Graphics
;
Early and Biologically-Inspired Vision
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Visual Attention and Image Saliency
Abstract:
We present a “curious” active vision system for a humanoid robot that autonomously explores its environment
and learns object representations without any human assistance. Similar to an infant, who is intrinsically
motivated to seek out new information, our system is endowed with an attention and learning mechanism
designed to search for new information that has not been learned yet. Our method can deal with dynamic
changes of object appearance which are incorporated into the object models. Our experiments demonstrate
improved learning speed and accuracy through curiosity-driven learning.