A Biologically Motivated Software Retina for Robotic Vision Applications

Siebert, J. P. , Schmidt, A., Aragon Camarasa, G. , Hockings, N., Wang, X. and Cockshott, W. (2016) A Biologically Motivated Software Retina for Robotic Vision Applications. European Conference on Computer Vision, ECCV2016, Workshop on Biological and Artificial Vision​, Amsterdam, The Netherlands, 08 Oct 2016.

Abstract

We present work in progress to address current limitations in image analysis by Deep Convolutional Neural Networks. By applying structural constraints based on known properties of the human visual system we propose to facilitate learning simple scale and rotation transformations, which contribute to large computational demands for training and opaqueness of the learned structure. We propose to apply a version of the retino-cortical transform to reduce the dimensionality of the input image space by a factor of e×100, and map this spatially to transform rotations and scale changes into spatial shifts. By reducing the input image size accordingly, and therefore learning requirements, we aim to develop a compact and lightweight robot vision sensor using a smartphone as the target platform. We also consider the visual processing architectural issues that must be addressed to integrate the mobile phone based front-end within a larger robot cognitive vision system.

• Item Type: Conference or Workshop Item
• Keywords: Retino-cortical transform, smart cameras, deep learning, CNN, robot vision, biologically motivated computer vision.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Schmidt, Dr Adam and Siebert, Dr Paul and Cockshott, Dr William and Hockings, Mr Nick and Aragon Camarasa, Dr Gerardo and Wang, xiaomeng
• Authors: Siebert, J. P., Schmidt, A., Aragon Camarasa, G., Hockings, N., Wang, X., and Cockshott, W.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: College of Science and Engineering > School of Computing Science
• Research Group: Computer Vision for Autonomous Systems within IDA

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