Periphery-fovea multi-resolution driving model guided by human attention

Ye Xia, Jinkyu Kim, John Canny, Karl Zipser, Teresa Canas-Bajo, David Whitney

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Inspired by human vision, we propose a new periphery-fovea multi-resolution driving model that predicts vehicle speed from dash camera videos. The peripheral vision module of the model processes the full video frames in low resolution with large receptive fields. Its foveal vision module selects sub-regions and uses high-resolution input from those regions to improve its driving performance. We train the fovea selection module with supervision from driver gaze. We show that adding high-resolution input from predicted human driver gaze locations significantly improves the driving accuracy of the model. Our periphery-fovea multi-resolution model outperforms a uni-resolution periphery-only model that has the same amount of floating-point operations. More importantly, we demonstrate that our driving model achieves a significantly higher performance gain in pedestrian-involved critical situations than in other non-critical situations. Our code is publicly available at https://github.com/pascalxia/periphery-fovea-driving.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1756-1764
Number of pages9
ISBN (Electronic)9781728165530
DOIs
Publication statusPublished - 2020 Mar
Externally publishedYes
Event2020 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2020 - Snowmass Village, United States
Duration: 2020 Mar 12020 Mar 5

Publication series

NameProceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020

Conference

Conference2020 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2020
Country/TerritoryUnited States
CitySnowmass Village
Period20/3/120/3/5

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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