Title
New Vehicle Detection Method with Aspect Ratio Estimation for Hypothesized Windows
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.
Year
DOI
Venue
2015
10.3390/s151229838
SENSORS
Keywords
Field
DocType
vehicle detection,ACF,ROI estimation
Aspect ratio (image),Simulation,Support vector machine,Algorithm,Communication channel,Electronic engineering,Ground truth,Engineering,Estimation theory,Data file,Statistical hypothesis testing,Speedup
Journal
Volume
Issue
Citations 
15
12.0
0
PageRank 
References 
Authors
0.34
16
4
Name
Order
Citations
PageRank
Jisu Kim121128.11
Jeonghyun Baek2265.31
yongseo park300.34
Euntai Kim41472109.36