Study on Pedestrian Detection Method Based on HOG Features and SVM
Study on Pedestrian Detection Method Based on HOG Features and SVM
The research of pedestrian detection ahead of vehicle is the front direction in the field of vehicle safety assistant driving at present. The method of SVM pedestrian detection based on HOG features is studied in this paper. Firstly, the histograms of oriented gradient features between pedestrian and non-pedestrian samples are extracted. Then the features are used as an input vector of SVM algorithm, getting pedestrian classifier with a higher recognition by training. Finally the trained classifier is loaded into the online pedestrian detection system to detect the transport road image. The experimental results show that the algorithm can effectively identify the different scales and attitude pedestrian in complex background.
Dokumentinformationen
Study on Pedestrian Detection Method Based on HOG Features and SVM
Advanced Materials Research ; 268-270 ; 1786-1791
2011-07-04
6 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Ähnliche Titel
Body Parts Features-Based Pedestrian Detection for Active Pedestrian Protection System
| DOAJ | 2016
Pedestrian Detection Using Boosted HOG Features
| IEEE | 2008
Pedestrian detection device and pedestrian detection method
| Europäisches Patentamt | 2019
PEDESTRIAN DETECTION DEVICE AND PEDESTRIAN DETECTION METHOD
| Europäisches Patentamt | 2018
Comparison of granules features for pedestrian detection
| IEEE | 2012