An Efficient Hardware Implementation of HOG Feature Extraction for Human Detection

Author

Pei-Yin Chen ; Chien-Chuan Huang ; Chih-Yuan Lien ; Yu-Hsien Tsai

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan

Volume

15

Issue

2

fYear

2014

fDate

Apr-14

Firstpage

656

Lastpage

662

Abstract

In intelligent transportation systems, human detection is an important issue and has been widely used in many applications. Histograms of oriented gradients (HOG) are proven to be able to significantly outperform existing feature sets for human detection. In this paper, we present a low-cost high-speed hardware implementation for HOG feature extraction. The simulation shows that the proposed circuit can achieve 167 MHz with 153-K gate counts by using Taiwan Semiconductor Manufacturing Company 0.13-μm technology. Compared with the previous hardware architectures for HOG feature extraction, our circuit requires fewer hardware costs and achieves faster working speed.

Keywords

feature extraction; intelligent transportation systems; object detection; HOG feature extraction; Taiwan Semiconductor Manufacturing Company; frequency 167 MHz; hardware implementation; histograms of oriented gradients; human detection; intelligent transportation systems; Approximation methods; Computer architecture; Feature extraction; Hardware; Histograms; Intelligent transportation systems; Real-time systems; Hardware implementation; histograms of oriented gradients (HOG); object detection;

fLanguage

English

Journal_Title

Intelligent Transportation Systems, IEEE Transactions on

Publisher

ieee

ISSN

1524-9050

Type

jour

DOI

10.1109/TITS.2013.2284666

Filename

6648678