Detecting Car Speed using Object Detection and Depth Estimation: A Deep Learning Framework
This addresses the problem of over-speeding detection for traffic enforcement in areas lacking expensive equipment, though it appears incremental as it applies existing deep learning techniques to a new application.
The paper tackles vehicle speed estimation by proposing a deep learning framework that uses object detection and depth estimation from handheld devices like mobile phones, aiming to provide an alternative to traditional LIDAR or radar-based speed guns.
Road accidents are quite common in almost every part of the world, and, in majority, fatal accidents are attributed to over speeding of vehicles. The tendency to over speeding is usually tried to be controlled using check points at various parts of the road but not all traffic police have the device to check speed with existing speed estimating devices such as LIDAR based, or Radar based guns. The current project tries to address the issue of vehicle speed estimation with handheld devices such as mobile phones or wearable cameras with network connection to estimate the speed using deep learning frameworks.