Using low-level optical flow to efficiently identify the driving state in automatic driving

Yinting Wang

doi:10.1117/12.2626559

20 December 2021 Using low-level optical flow to efficiently identify the driving state in automatic driving

Yinting Wang

Proceedings Volume 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021); 1215510 (2021) https://doi.org/10.1117/12.2626559
Event: International Conference on Computer Vision, Application, and Design (CVAD 2021), 2021, Sanya, China

Abstract

The analysis of driving status has always been one of the important research directions in the field of autonomous driving. With the development of deep learning, convolutional neural networks have become a hot spot in optical flow computing technology. This article mainly describes the difference between the calculation method of optical flow in deep learning and low-level optical flow calculation, and uses a low-level optical flow algorithm to realize more accurate and efficient analysis, calculation, and recognition of the driving state of autonomous driving based on the data in the KITTI database. Finally, it summarizes the existing problems and puts forward ideas.

Citation Download Citation

Yinting Wang "Using low-level optical flow to efficiently identify the driving state in automatic driving", Proc. SPIE 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021), 1215510 (20 December 2021); https://doi.org/10.1117/12.2626559

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