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Sensors 2015, 15(12), 30927-30941; doi:10.3390/s151229838

New Vehicle Detection Method with Aspect Ratio Estimation for Hypothesized Windows

1
The School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, Korea
2
Department of Electrical Engineering, Gachon University, Seongnam 461-701, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Felipe Jimenez
Received: 26 August 2015 / Revised: 26 November 2015 / Accepted: 3 December 2015 / Published: 9 December 2015
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [5467 KB, uploaded 9 December 2015]   |  

Abstract

All kinds of vehicles have different ratios of width to height, which are called the aspect ratios. Most previous works, however, use a fixed aspect ratio for vehicle detection (VD). The use of a fixed vehicle aspect ratio for VD degrades the performance. Thus, the estimation of a vehicle aspect ratio is an important part of robust VD. Taking this idea into account, a new on-road vehicle detection system is proposed in this paper. The proposed method estimates the aspect ratio of the hypothesized windows to improve the VD performance. Our proposed method uses an Aggregate Channel Feature (ACF) and a support vector machine (SVM) to verify the hypothesized windows with the estimated aspect ratio. The contribution of this paper is threefold. First, the estimation of vehicle aspect ratio is inserted between the HG (hypothesis generation) and the HV (hypothesis verification). Second, a simple HG method named a signed horizontal edge map is proposed to speed up VD. Third, a new measure is proposed to represent the overlapping ratio between the ground truth and the detection results. This new measure is used to show that the proposed method is better than previous works in terms of robust VD. Finally, the Pittsburgh dataset is used to verify the performance of the proposed method. View Full-Text
Keywords: vehicle detection; ACF; ROI estimation vehicle detection; ACF; ROI estimation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Kim, J.; Baek, J.; Park, Y.; Kim, E. New Vehicle Detection Method with Aspect Ratio Estimation for Hypothesized Windows. Sensors 2015, 15, 30927-30941.

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