TY  - INPR
A1  - Klimmasch, Lukas
A1  - Lelais, Alexander
A1  - Lichtenstein, Alexander
A1  - Shi, Bertram E.
A1  - Triesch, Jochen
T1  - Learning of active binocular vision in a biomechanical model of the oculomotor system
T2  - bioRxiv
N2  - We present a model for the autonomous learning of active binocular vision using a recently developed biome-chanical model of the human oculomotor system. The model is formulated in the Active Efficient Coding (AEC) framework, a recent generalization of classic efficient coding theories to active perception. The model simultaneously learns how to efficiently encode binocular images and how to generate accurate vergence eye movements that facilitate efficient encoding of the visual input. In order to resolve the redundancy problem arising from the actuation of the eyes through antagonistic muscle pairs, we consider the metabolic costs associated with eye movements. We show that the model successfully learns to trade off vergence accuracy against the associated metabolic costs, producing high fidelity vergence eye movements obeying Sherrington’s law of reciprocal innervation.
Y1  - 2017
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/72434
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-724342
IS  - 160721
ER  -