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Proceedings ArticleDOI

CarSafe app: alerting drowsy and distracted drivers using dual cameras on smartphones

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TLDR
CarSafe is the first dual-camera sensing app for smartphones and represents a new disruptive technology because it provides similar advanced safety features otherwise only found in expensive top-end cars.
Abstract
We present CarSafe, a new driver safety app for Android phones that detects and alerts drivers to dangerous driving conditions and behavior. It uses computer vision and machine learning algorithms on the phone to monitor and detect whether the driver is tired or distracted using the front-facing camera while at the same time tracking road conditions using the rear-facing camera. Today's smartphones do not, however, have the capability to process video streams from both the front and rear cameras simultaneously. In response, CarSafe uses acontext-aware algorithm that switches between the two cameras while processing the data in real-time with the goal of minimizing missed events inside (e.g., drowsy driving) and outside of the car (e.g., tailgating). Camera switching means that CarSafe technically has a "blind spot" in the front or rear at any given time. To address this, CarSafe uses other embedded sensors on the phone (i.e., inertial sensors) to generate soft hints regarding potential blind spot dangers. We present the design and implementation of CarSafe and discuss its evaluation using results from a 12-driver field trial. Results from the CarSafe deployment are promising -- CarSafe can infer a common set of dangerous driving behaviors and road conditions with an overall precision and recall of 83% and 75%, respectively. CarSafe is the first dual-camera sensing app for smartphones and represents a new disruptive technology because it provides similar advanced safety features otherwise only found in expensive top-end cars.

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Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

David Forsyth, +1 more
TL;DR: Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance and describes numerous important application areas such as image based rendering and digital libraries.
Journal ArticleDOI

A Survey of the Connected Vehicle Landscape—Architectures, Enabling Technologies, Applications, and Development Areas

TL;DR: This paper summarizes the state of the art in connected vehicles—from the need for vehicle data and applications thereof, to enabling technologies, challenges, and identified opportunities—from extensibility and scalability to privacy and security.
Journal ArticleDOI

Driver Behavior Analysis for Safe Driving: A Survey

TL;DR: A proposal is made for the active of such systems into car-to-car communication to support vehicular ad hoc network's (VANET) primary aim of safe driving and the dissemination of driver behavior via C2C communication.
Proceedings ArticleDOI

The Design and Implementation of a Wireless Video Surveillance System

TL;DR: Experimental results show that Vigil allows a video surveillance system to support a geographical area of coverage between five and 200 times greater than an approach that simply streams video over the wireless network.
Journal ArticleDOI

Mobility Increases Localizability: A Survey on Wireless Indoor Localization using Inertial Sensors

TL;DR: This article surveys this new trend of mobility enhancing smartphone-based indoor localization and discusses how mobility assists localization with respect to enhancing location accuracy, decreasing deployment cost, and enriching location context.
References
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Proceedings ArticleDOI

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Book

Pattern Recognition and Machine Learning (Information Science and Statistics)

TL;DR: Looking for competent reading resources?
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