Evaluation of the impact of lossy compression on event camera-based computer vision tasks

Bowen Huang; Davi Lazzarotto; Touradj Ebrahimi

doi:10.1117/12.2676419

4 October 2023 Evaluation of the impact of lossy compression on event camera-based computer vision tasks

Bowen Huang, Davi Lazzarotto, Touradj Ebrahimi

Proceedings Volume 12674, Applications of Digital Image Processing XLVI; 126740C (2023) https://doi.org/10.1117/12.2676419
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Abstract

In the field of image acquisition, Dynamic Vision Sensors (DVS) present an innovative methodology, capturing only the variations in pixel brightness instead of absolute values and thereby revealing unique features. Given that the primary deployment of DVS is within embedded systems characterized by their constrained transmission and storage capabilities, the emphasis on data compression becomes significant. Nonetheless, such a compression could potentially compromise the efficacy of computer vision (CV) applications. This study investigates the implications of a lossy compression technique, premised on point cloud representation, for event data in CV tasks. Multiple scenarios under various compression intensities are applied to event data, and the experiments indicate the feasibility of attaining reduced bitrates while incurring minimal impact in CV task performance.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bowen Huang, Davi Lazzarotto, and Touradj Ebrahimi "Evaluation of the impact of lossy compression on event camera-based computer vision tasks", Proc. SPIE 12674, Applications of Digital Image Processing XLVI, 126740C (4 October 2023); https://doi.org/10.1117/12.2676419

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