mlsanityData to 14 Oct 2026

Automatically identifying a mobile phone user's position within a vehicle

arXiv 2111.06306 ↗First posted 11 Nov 2021cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

Traffic-related injuries and fatalities are major health risks in the United States. Mobile phone use while driving quadruples the risk for a motor vehicle crash. This work demonstrates the feasibility of using the mobile phone camera to passively detect the location of the phone's user within a vehicle. In a large, varied dataset we were able correctly identify if the user was in the driver's seat or one of the passenger seats with 94.9% accuracy. This model could be used by application developers to selectively change or lock functionality while a user is driving, but not if the user is a passenger in a moving vehicle.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 19 references that are in the map. First posted on arXiv 11 Nov 2021.

Builds on

2 of 19 references.

References · 2

  1. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 7,005
  2. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,795

Built on by

Not cited yet.