DocumentCode :
3586305
Title :
Implementation of pedestrian detection using a CENTRIST-ROI in embedded environment
Author :
Yun-seop Hwang ; Chang-min Jung ; Tae-ryong Park ; Kwang-yeob Lee
Author_Institution :
Dept. of Comput. Eng., SeoKyeong Univ., Seoul, South Korea
fYear :
2014
Firstpage :
50
Lastpage :
51
Abstract :
This paper proposes a pedestrian detection algorithm to which ROI was applied to implement pedestrian detection that is suitable for the embedded environment. Pedestrian detection has computations for unnecessary areas because the entire input images are computed to find pedestrians in the given images. In this paper, a pedestrian detection algorithm that is ideal for the embedded environment is proposed which reduced computations for unnecessary areas by applying ROI. The CENTIRST descriptor method was used for the pedestrian detection algorithm, which was implemented using 512×360 pixel images on an ALDEBARAN board. The proposed pedestrian detection with ROI showed a 16% improved performance of 3.6 frames per second compared to the conventional method.
Keywords :
object detection; pedestrians; ALDEBARAN board; CENTIRST descriptor method; CENTRIST-ROI; embedded environment; pedestrian detection; Computational modeling; census transform histogram; embedded; feature; pedestrian detection; region of interest;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SoC Design Conference (ISOCC), 2014 International
Type :
conf
DOI :
10.1109/ISOCC.2014.7087589
Filename :
7087589
Link To Document :
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