Neuromorphic Vision Data Coding: Classifying and Reviewing the Literature

TL;DR

This paper reviews neuromorphic vision data coding solutions, highlighting their importance for efficient data handling from sensors mimicking human visual processing, and introduces a new classification taxonomy for organizing this research field.

Contribution

It provides a comprehensive overview of NVDC solutions and proposes a novel taxonomy to better organize and analyze this emerging research area.

Findings

Current NVDC solutions vary widely in approach and efficiency.

The proposed taxonomy helps clarify research trends and gaps.

Future research directions are identified for improved coding methods.

Abstract

In recent years, visual sensors have been quickly improving towards mimicking the visual information acquisition process of human brain by responding to illumination changes as they occur in time rather than at fixed time intervals. In this context, the so-called neuromorphic vision sensors depart from the conventional frame-based image sensors by adopting a paradigm shift in the way visual information is acquired. This new way of visual information acquisition enables faster and asynchronous per-pixel responses/recordings driven by the scene dynamics with a very high dynamic range and low power consumption. However, depending on the application scenario, the emerging neuromorphic vision sensors may generate a large volume of data, thus critically demanding highly efficient coding solutions in order applications may take full advantage of these new, attractive sensors' capabilities. For this reason, considerable research efforts have been invested in recent years towards developing increasingly efficient neuromorphic vision data coding (NVDC) solutions. In this context, the main objective of this paper is to provide a comprehensive overview of NVDC solutions in the literature, guided by a novel classification taxonomy, which allows better organizing this emerging field. In this way, more solid conclusions can be drawn about the current NVDC status quo, thus allowing to better drive future research and standardization developments in this emerging technical area.