Increasing Compression Ratio of Low Complexity Compressive Sensing Video Encoder with Application-Aware Configurable Mechanism

TL;DR

This paper proposes a configurable low-complexity compressive sensing video encoder that adapts to application needs, significantly improving compression ratio while maintaining high tracking success rates.

Contribution

It introduces an application-aware configurable mechanism for compressive sensing video encoding, optimizing complexity and compression ratio based on practical application requirements.

Findings

Achieves up to 60x compression ratio with high tracking success.

Configurable GOP and measurement matrix improve compression efficiency.

Maintains over 90% tracking success at high compression ratios.

Abstract

With the development of embedded video acquisition nodes and wireless video surveillance systems, traditional video coding methods could not meet the needs of less computing complexity any more, as well as the urgent power consumption. So, a low-complexity compressive sensing video encoder framework with application-aware configurable mechanism is proposed in this paper, where novel encoding methods are exploited based on the practical purposes of the real applications to reduce the coding complexity effectively and improve the compression ratio (CR). Moreover, the group of processing (GOP) size and the measurement matrix size can be configured on the encoder side according to the post-analysis requirements of an application example of object tracking to increase the CR of encoder as best as possible. Simulations show the proposed framework of encoder could achieve 60X of CR when the tracking successful rate (SR) is still keeping above 90%.