TY - JOUR
T1 - Accelerating Histograms of Oriented Gradients descriptor extraction for pedestrian recognition
AU - Lee, Seung Eun
AU - Min, Kyungwon
AU - Suh, Taeweon
N1 - Funding Information:
This study was financially supported in part by the Seoul National University of Science and Technology and the industrial core technology development program (10041656) of the Ministry of Knowledge Economy (MKE) of Korea.
Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013/5
Y1 - 2013/5
N2 - Pedestrian recognition is an emerging visual computing application for embedded systems. In one usage model, a vehicle mounted camera acquires image from road and a pedestrian recognition system automatically recognizes and alarms information on the road preventing traffic accidents. Achieving this in software on embedded systems requires significant compute processing for object recognition. In this paper, we identify the hotspot function of the workload on an embedded system that motivates acceleration and present the detailed design of a hardware accelerator for Histograms of Oriented Gradients descriptor extraction. We also quantify the performance and area efficiency of the hardware accelerator. Our analysis shows that hardware acceleration has the potential to improve the hotspot function. As a result, user response time can be reduced significantly.
AB - Pedestrian recognition is an emerging visual computing application for embedded systems. In one usage model, a vehicle mounted camera acquires image from road and a pedestrian recognition system automatically recognizes and alarms information on the road preventing traffic accidents. Achieving this in software on embedded systems requires significant compute processing for object recognition. In this paper, we identify the hotspot function of the workload on an embedded system that motivates acceleration and present the detailed design of a hardware accelerator for Histograms of Oriented Gradients descriptor extraction. We also quantify the performance and area efficiency of the hardware accelerator. Our analysis shows that hardware acceleration has the potential to improve the hotspot function. As a result, user response time can be reduced significantly.
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U2 - 10.1016/j.compeleceng.2013.04.001
DO - 10.1016/j.compeleceng.2013.04.001
M3 - Article
AN - SCOPUS:84878831088
SN - 0045-7906
VL - 39
SP - 1043
EP - 1048
JO - Computers and Electrical Engineering
JF - Computers and Electrical Engineering
IS - 4
ER -
