Object-Attribute-Relation Representation Based Video Semantic Communication

TL;DR

This paper proposes an object-attribute-relation (OAR) semantic framework for video transmission that improves low bit-rate coding and enhances joint source-channel coding (JSCC) performance, outperforming traditional methods like H.265.

Contribution

It introduces OAR as a semantic representation for videos to facilitate low bit-rate coding and improve JSCC, with experimental validation on traffic surveillance datasets.

Findings

OAR-based coding outperforms H.265 at lower bit-rates.

OAR enhances JSCC robustness and efficiency.

The approach improves video transmission quality in low-bandwidth scenarios.

Abstract

With the rapid growth of multimedia data volume, there is an increasing need for efficient video transmission in applications such as virtual reality and future video streaming services. Semantic communication is emerging as a vital technique for ensuring efficient and reliable transmission in low-bandwidth, high-noise settings. However, most current approaches focus on joint source-channel coding (JSCC) that depends on end-to-end training. These methods often lack an interpretable semantic representation and struggle with adaptability to various downstream tasks. In this paper, we introduce the use of object-attribute-relation (OAR) as a semantic framework for videos to facilitate low bit-rate coding and enhance the JSCC process for more effective video transmission. We utilize OAR sequences for both low bit-rate representation and generative video reconstruction. Additionally, we incorporate OAR into the image JSCC model to prioritize communication resources for areas more critical to downstream tasks. Our experiments on traffic surveillance video datasets assess the effectiveness of our approach in terms of video transmission performance. The empirical findings demonstrate that our OAR-based video coding method not only outperforms H.265 coding at lower bit-rates but also synergizes with JSCC to deliver robust and efficient video transmission.