Adaptive Temporal Compressive Sensing for Video

TL;DR

This paper presents an adaptive temporal compressive sensing method for video that dynamically adjusts compression based on scene complexity, enabling real-time implementation without quality loss.

Contribution

It introduces a generalized adaptive CS algorithm that adjusts compression ratios in real-time based on scene dynamics, compatible with various hardware systems.

Findings

Effective scene complexity estimation from compressed data

Real-time adaptive compression achieved

Compatible with diverse hardware systems

Abstract

This paper introduces the concept of adaptive temporal compressive sensing (CS) for video. We propose a CS algorithm to adapt the compression ratio based on the scene's temporal complexity, computed from the compressed data, without compromising the quality of the reconstructed video. The temporal adaptivity is manifested by manipulating the integration time of the camera, opening the possibility to real-time implementation. The proposed algorithm is a generalized temporal CS approach that can be incorporated with a diverse set of existing hardware systems.