Scalable Event-Based Video Streaming for Machines with MoQ

TL;DR

This paper addresses the challenge of data transmission in event-based neuromorphic video sensors by proposing a scalable, low-latency streaming format utilizing the Media Over QUIC protocol, advancing neuromorphic vision systems.

Contribution

It introduces a novel low-latency event streaming format based on Media Over QUIC, specifically designed for neuromorphic event-based video sensors, filling a gap in current research.

Findings

Proposed a new event streaming format for neuromorphic sensors.

Demonstrated low-latency performance with the format.

Discussed technical issues and solutions in event streaming.

Abstract

Lossy compression and rate-adaptive streaming are a mainstay in traditional video steams. However, a new class of neuromorphic ``event'' sensors records video with asynchronous pixel samples rather than image frames. These sensors are designed for computer vision applications, rather than human video consumption. Until now, researchers have focused their efforts primarily on application development, ignoring the crucial problem of data transmission. We survey the landscape of event-based video systems, discuss the technical issues with our recent scalable event streaming work, and propose a new low-latency event streaming format based on the latest additions to the Media Over QUIC protocol draft.