Title :
Efficient pedestrian detection by Bin-interleaved Histogram of Oriented Gradients
Author :
Son, Haengseon ; Lee, Seonyoung ; Choi, Jongchan ; Min, Kyungwon
Author_Institution :
Convergent SoC Res. Center, Korea Electron. Technol. Inst., Seongnam, South Korea
Abstract :
This paper presents an efficient pedestrian detection by Bin-interleaved Histogram of Oriented Gradients (Bi-HOG) for automotive applications. The state-of-art feature named HOG [5] is adopted as the basic feature. We arrange alternately even-bin cells and odd-bin cells in one block and then extract the only even-bin feature elements for even-bin cells and the only odd-bin feature elements for odd-bin cells. So the feature dimension of our Bi-HOG is a half size of HOG by bin-interleaved method like this. We experimentally demonstrate that SVM classifiers trained by Bi-HOG have the same detection performance on the DaimlerChrysler data set as one by the original HOG in our two-staged pedestrian detection system and considerably reduce storage requirement and simplify the computational complexity.
Keywords :
image recognition; pattern classification; support vector machines; Bi-HOG; DaimlerChrysler data set; SVM classifiers; automotive application; bin-interleaved histogram of oriented gradients; computational complexity; pedestrian detection; storage requirement; Bin-interleaved HoG (Bi-HOG); Histogram of Oriented Gradient (HOG); Support Vector Machine (SVM); object detection; pedestrian detection;
Conference_Titel :
TENCON 2010 - 2010 IEEE Region 10 Conference
Conference_Location :
Fukuoka
Print_ISBN :
978-1-4244-6889-8
DOI :
10.1109/TENCON.2010.5685979