Name
Abstract | ||
|---|---|---|
In this paper, we proposed a pedestrian detection system based on laser and image data fusion. The high speed of laser data based location and precise of image based classification are fully explored. First, laser scanner point data is clustered into segments, each of which implies a pedestrian candidate. Then, the segments are projected to the image domain to form regions of interest (ROI) on the image, given camera calibration parameters. Finally two SVM classifiers on Histogram of Oriented Gradient (HOG) features are used to precisely locate pedestrians on the ROI. Experiments report over 30 times higher speed than the state-of-the-art method and a comparable detection rate. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICIG.2011.107 | ICIG |
Keywords | DocType | ISBN |
image based classification,image segment,laser data,image fusion,times higher speed,pedestrian detection,regions of interest,image segmentation,high speed,optical scanners,fast pedestrian detection,svm classifier,image domain,image data fusion,comparable detection rate,image classification,laser scanner hog features,gradient methods,camera calibration parameter,laser scanner point data,object detection,histogram of oriented gradient,traffic information systems,pedestrian candidate,laser data based location,oriented gradient,pedestrian detection system,support vector machines,sensor fusion,hog feature,data fusion,support vector machine,laser fusion,camera calibration,laser scanner,region of interest,feature extraction | Conference | 978-0-7695-4541-7 |
Citations | PageRank | References |
4 | 0.57 | 8 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bo Wu | 1 | 4 | 0.57 |
| Jixiang Liang | 2 | 16 | 1.46 |
| Qixiang Ye | 3 | 913 | 64.51 |
| Zhenjun Han | 4 | 176 | 16.40 |
| Jianbin Jiao | 5 | 367 | 32.61 |