Realtime Vehicle Detection using Dashboard Camera
Date Issued
2015
Date
2015
Author(s)
Kao, Hao-Cheng
Abstract
Intellectual transportation system is gaining more and more attentions in recent years. The system is designed to improve human safety for drivers, passengers and pedestrians. In order to have the ability of making high level decision the system needs to have some basic information. Detecting nearby vehicles is usually important because it provides the essential part of the driving context. Vehicle detection covers a wide range from detecting the bounding box of vehicles in the captured image to inferring the position, speed and even the intent of the vehicles detected. In this work we focus on the bounding box detection part for a single image. First we give an analyze of the state-of-the-art approaches related to this task. Then we further test some candidates of proposal generation and classification approach. And we show that the trade off between accuracy and speed can be done via adjusting parameters of these algorithms. Finally we show that by using different resolution image in proposal generation algorithm and classification algorithm can be a step toward realtime processing.
Subjects
realtime vehicle detection
proposal generation
vehicle classification
Type
thesis
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ntu-104-R02922122-1.pdf
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