HOG feature extractor circuit for real-time human and vehicle detection

Smart vehicle technologies such as ADAS are growing concern about. Especially, pedestrian and vehicle recognition system based on machine vision is a big issue. In this paper, we propose the hardwired HOG feature extractor circuit for real-time human and vehicle detection, and describe the hardware...

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Bibliographic Details
Main Authors: Seonyoung Lee, Haengseon Son, Jong Chan Choi, Kyoungwon Min
Format: Conference Proceeding
Language:English
Subjects:
Calculators
Conferences
Feature extraction
Hardware
hardware circuit
Histograms
HOG
human detection
Humans
real-time
Real-time systems
vehicle detection
Online Access:Request full text
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Description
Summary:Smart vehicle technologies such as ADAS are growing concern about. Especially, pedestrian and vehicle recognition system based on machine vision is a big issue. In this paper, we propose the hardwired HOG feature extractor circuit for real-time human and vehicle detection, and describe the hardware implementation results. Our HOG feature extractor supports weighted gradient value, 2D histogram interpolation and block normalization. We have used the simplified methods of the square root and division operation for the hardware implementation. Our HOG feature extractor circuit was verified on FPGA environment and can be processed 33 frames per seconds for 640×480 VGA images in real-time.
ISSN:2159-3442
2159-3450
DOI:10.1109/TENCON.2012.6412287