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Paper Abstract and Keywords
Presentation 2012-01-20 11:10
Detecting Pedestrians in Night View using HOG and NFTG with Geometric Constraints
Hiroki Maebuchi, Haiyuan Wu, Toshikazu Wada (Wakayama Univ) PRMU2011-175 MVE2011-84
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a method for detecting pedestrians on the road in night view using HOG, NFTG and the geometric constraints that pedestrians stand or walk on the road. The vanishing point of the road is estimated from the white lines on the road using particle filter and Hough transform. The vanishing point is used to predict the size of the pedestrian when whose position is given, thus brings the effect of reducing the processing time and the false detection. A new method called “Integral-Ni-HOG” (or INi-HOG) for calculating HOG for near-infrared images fast is proposed. The Hausdorff distance between the pedestrian candidate regions and the pedestrian model is used for the verification of each pedestrian candidate region in the image. NFTG is used to describe the relations between each pedestrian model in order to reduce the number of times of pedestrian models being used for verifying each pedestrian candidate region. The experiments using real images show that this method is 15 times faster and the false detection rate is lowered by about 50% compared the conventional method based on HOG.
Keyword (in Japanese) (See Japanese page) 
(in English) Detecting Pedestrians in Night View / Near-infrared / INi-HOG / NFTG / geometric constraints / Hausdorff Distance / /  
Reference Info. IEICE Tech. Rep., vol. 111, no. 379, PRMU2011-175, pp. 291-296, Jan. 2012.
Paper # PRMU2011-175 
Date of Issue 2012-01-12 (PRMU, MVE) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF PRMU2011-175 MVE2011-84

Conference Information
Committee PRMU MVE CQ IPSJ-CVIM  
Conference Date 2012-01-19 - 2012-01-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2012-01-PRMU-MVE-CQ-CVIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Detecting Pedestrians in Night View using HOG and NFTG with Geometric Constraints 
Sub Title (in English)  
Keyword(1) Detecting Pedestrians in Night View  
Keyword(2) Near-infrared  
Keyword(3) INi-HOG  
Keyword(4) NFTG  
Keyword(5) geometric constraints  
Keyword(6) Hausdorff Distance  
Keyword(7)  
Keyword(8)  
1st Author's Name Hiroki Maebuchi  
1st Author's Affiliation Wakayama University (Wakayama Univ)
2nd Author's Name Haiyuan Wu  
2nd Author's Affiliation Wakayama University (Wakayama Univ)
3rd Author's Name Toshikazu Wada  
3rd Author's Affiliation Wakayama University (Wakayama Univ)
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Speaker Author-1 
Date Time 2012-01-20 11:10:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2011-175, MVE2011-84 
Volume (vol) vol.111 
Number (no) no.379(PRMU), no.380(MVE) 
Page pp.291-296 
#Pages 6 
Date of Issue 2012-01-12 (PRMU, MVE) 

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