Title :
Applying MSC-HOG feature to the detection of a human on a bicycle
Author :
Heewook Jung ; Ehara, Yoshiyasu ; Joo Kooi Tan ; Hyoungseop Kim ; Ishikawa, Seiichiro
Author_Institution :
Dept. of Mech. & Control Eng., Kyushu Inst. of Technol., Kitakyushu, Japan
Abstract :
Traffic accidents are decreasing under the influence of technology advancement. But the problems still remain that accidents occur due to carelessness of drivers. Therefore many researchers have been still studying to realize an advanced safety system. The Histograms of Oriented Gradients (HOG) feature is well known as a useful method of detecting a standing human in various kinds of the background. Unlike a human, a bicycle changes its appearance variously according to viewpoints. Hence, it is more difficult than detecting a human. In this paper, we propose a method of detecting a human on a bicycle using the Multiple-size Cell HOG (MSC-HOG) feature and the RealAdaboost algorithm. Experimental results and evaluation show satisfactory performance of the proposed method.
Keywords :
computer vision; feature extraction; learning (artificial intelligence); object detection; object recognition; road accidents; road traffic; traffic engineering computing; MSC-HOG feature; advanced safety system; car vision; histograms-of-oriented gradients feature; human detection; multiple-size cell HOG feature; object recognition techniques; realAdaboost algorithm; technology advancement; traffic accidents; Accidents; Bicycles; Classification algorithms; Feature extraction; Histograms; Humans; Merging; MSC-HOG feature; advanced safety system; bicycle detection;
Conference_Titel :
Control, Automation and Systems (ICCAS), 2012 12th International Conference on
Print_ISBN :
978-1-4673-2247-8
