Name
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ITSC.2014.6958041 | ITSC |
Keywords | Field | DocType |
estimation theory,feature extraction,object detection,road traffic,road vehicles,support vector machines,traffic engineering computing,hog feature,pittsburgh dataset,roi estimation,suv,svm,bus,histogram of oriented histogram,onroad precise vehicle detection system,sedan,support vector machine,truck,ratios,real time information,histograms,estimating | Truck,Histogram,Computer vision,Real-time data,Simulation,Support vector machine,Vehicle detection,Artificial intelligence,Feature based,Engineering | Conference |
Citations | PageRank | References |
1 | 0.36 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jisu Kim | 1 | 211 | 28.11 |
| Jeonghyun Baek | 2 | 26 | 5.31 |
| Euntai Kim | 3 | 1472 | 109.36 |