On-road precise vehicle detection system using ROI estimation

Jisu Kim, Jeonghyun Baek, Euntai Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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 languageEnglish
Title of host publication2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2251-2252
Number of pages2
ISBN (Electronic)9781479960781
DOIs
Publication statusPublished - 2014 Jan 1
Event2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 - Qingdao, China
Duration: 2014 Oct 82014 Oct 11

Other

Other2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
CountryChina
CityQingdao
Period14/10/814/10/11

Fingerprint

Trucks
Support vector machines
Degradation
Experiments

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Automotive Engineering
  • Mechanical Engineering

Cite this

Kim, J., Baek, J., & Kim, E. (2014). On-road precise vehicle detection system using ROI estimation. In 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 (pp. 2251-2252). [6958041] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC.2014.6958041
Kim, Jisu ; Baek, Jeonghyun ; Kim, Euntai. / On-road precise vehicle detection system using ROI estimation. 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 2251-2252
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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.",
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Kim, J, Baek, J & Kim, E 2014, On-road precise vehicle detection system using ROI estimation. in 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014., 6958041, Institute of Electrical and Electronics Engineers Inc., pp. 2251-2252, 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014, Qingdao, China, 14/10/8. https://doi.org/10.1109/ITSC.2014.6958041

On-road precise vehicle detection system using ROI estimation. / Kim, Jisu; Baek, Jeonghyun; Kim, Euntai.

2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 2251-2252 6958041.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - 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.

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Kim J, Baek J, Kim E. On-road precise vehicle detection system using ROI estimation. In 2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 2251-2252. 6958041 https://doi.org/10.1109/ITSC.2014.6958041