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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| ITS, IPSJ-ITS, IEE-ITS | 2023-08-29 16:45 |
Kanagawa | Kanto Gakuin Univ. (Kanazawa-Hakkei Campus) (Primary: On-site, Secondary: Online) |
A Study on evaluation index for step counting of PDR Hana Osawa, Masahiro Fujii (Utsunomiya Univ.)  ITS2023-10 |
Pedestrian Dead Reckoning (PDR) is an alternative pedestrian location estimation method for indoor when GNSS (Global Nav... [more] | ITS2023-10 pp.16-21 |
| MI, IE, SIP, BioX, ITE-IST, ITE-ME [detail] | 2020-05-29 15:10 |
Online | Online | Distant pedestrian detection from nighttime NIR video by moving-region zooming Atsuki Hiramatsu, Yusuke Kameda (TUS), Hiroshi Ikeoka (Fukuyama Univ.), Takayuki Hamamoto (TUS) SIP2020-16 BioX2020-16 IE2020-16 MI2020-16 |
Highly accurate pedestrian detection technology is required for functions such as automatic emergency braking, which are... [more] | SIP2020-16 BioX2020-16 IE2020-16 MI2020-16 pp.79-83 |
| MWP | 2019-05-22 16:30 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Preliminary Experimental Study on a Two-Frequency Secondary-Radar System to Detect Pedestrians beyond Blind Corners Keizo Inagaki (NICT), Motoki Shirai, Tetsuya Miura, Kunihisa Jitsuno, Tetsuya Kawanishi (Waseda Univ.) MWP2019-5 |
Authors are studying on a two-frequency secondary radar system to prevent traffic accidents between pedestrians and vehi... [more] | MWP2019-5 pp.19-22 |
| PRMU, BioX | 2018-03-18 16:10 |
Tokyo | Pedestrian Detection with Multi-level Deep Features Misaki Kodaira, Yu Wang, Jien Kato (Nagoya Univ.) BioX2017-52 PRMU2017-188 |
In this research, we aim to clarify effective application of CNN features in pedestrian detection. In the experiment, fe... [more] | BioX2017-52 PRMU2017-188 pp.97-102 |
|
| PRMU, BioX | 2015-03-19 11:00 |
Kanagawa | A Study on Efficient Pedestrian Detection by Combining CNN and SVM. Takuma Saito, Yuji Waizumi, Kazuyuki Tanaka (Tohoku Univ.) BioX2014-46 PRMU2014-166 |
Detecting pedestrian in real time is challenging problem for application to road safety. For high-accuracy and high-spee... [more] | BioX2014-46 PRMU2014-166 pp.41-46 |
|
| PRMU, BioX | 2015-03-20 11:00 |
Kanagawa | A study on construction of pedestrian detectors adaptive to driving environment referring to false positive tendency Yuki Suzuki, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.) BioX2014-67 PRMU2014-187 |
Recently, safety driving assistance systems using an in-vehicle camera have been studied actively. In particular, since ... [more] | BioX2014-67 PRMU2014-187 pp.171-176 |
|
| PRMU | 2014-10-09 14:30 |
Chiba | A study on features for pedestrian detection using a low resolution LIDAR Yoshinori Ichikawa, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.), Hideaki Misawa, Utsushi Sakai (DENSO) PRMU2014-55 |
In recent years, LIDAR (LIght Detection And Ranging) is focused as a sensor for recognizing surrounding environment arou... [more] | PRMU2014-55 pp.7-12 |
|
| ITS, IE, ITE-AIT, ITE-HI, ITE-ME [detail] | 2014-02-18 13:35 |
Hokkaido | Hokkaido Univ. | HOG Feature based Polar Coordinates for Pedestrian Detection Yuta Horikawa, Kousuke Matsushima (KurumeNCT) ITS2013-65 IE2013-130 |
Recently, the number of traffic accidents and injured people has been decreasing. However, the traffic-related pedestria... [more] | ITS2013-65 IE2013-130 pp.357-362 |
| PRMU, MVE, CQ, IPSJ-CVIM [detail] | 2012-01-20 11:10 |
Osaka | Detecting Pedestrians in Night View using HOG and NFTG with Geometric Constraints Hiroki Maebuchi, Haiyuan Wu, Toshikazu Wada (Wakayama Univ) PRMU2011-175 MVE2011-84 |
This paper proposes a method for detecting pedestrians on the road in night view using HOG, NFTG and the geometric const... [more] | PRMU2011-175 MVE2011-84 pp.291-296 |
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| PRMU | 2009-12-18 14:30 |
Tochigi | Fujihara Cultural Center | A Hardware-Friendly Object Detection Algorithm Based on Variable-Block-Size Edge Histograms Takashi Miyoshi, Tadashi Shibata (Univ. of Tokyo.) PRMU2009-151 |
The paper presents an object localization algorithm based on the directional-edge information and discusses its hardware... [more] | PRMU2009-151 pp.71-76 |
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