Abstract
In this paper, we propose a new on-road vehicle detection system. Appearance of vehicles in image has various ratios because of its many kinds of models such as sedan, SUV and truck. For this reason, using ROI with fixed ratio can cause the degradation for detecting vehicles of various models. To solve this problem, we propose a new vehicle detection system using estimating ratio of vehicles. The proposed method estimates the ratio of vehicle ROI and extracted feature based evaluated ratio. It shows robust detection performance for various vehicle models because it extracts the feature from compact ROI with exact vehicle size. In our experiments, histogram of oriented histogram (HOG) feature and support vector machine (SVM) are used for the vehicle detection system. In order to evaluate the detection performance, the Pittsburgh dataset including various vehicle models such as sedan, SUV, truck and bus is used. In this dataset, it is shown that the proposed method is more robust than previous works to detect various vehicle models.
Original language | English |
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Title of host publication | 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 2251-2252 |
Number of pages | 2 |
ISBN (Electronic) | 9781479960781 |
DOIs | |
Publication status | Published - 2014 Nov 14 |
Event | 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 - Qingdao, China Duration: 2014 Oct 8 → 2014 Oct 11 |
Publication series
Name | 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 |
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Other
Other | 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 |
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Country/Territory | China |
City | Qingdao |
Period | 14/10/8 → 14/10/11 |
Bibliographical note
Publisher Copyright:© 2014 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Automotive Engineering
- Mechanical Engineering