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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 28  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
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
PRMU, IPSJ-CVIM 2019-05-30
11:20
Tokyo   A Preliminary Study on Integrating Camera and LiDAR Pedestrian Detections Adaptive to Surrounding Environmental Conditions
Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide (Nagoya Univ.), Kazuki Kato (DENSO CORPORATION), Hiroshi Murase (Nagoya Univ.) PRMU2019-6
Results of pedestrian detectors from in-vehicle sensors still have room for improvement in real environments.
Therefore... [more]
PRMU2019-6
pp.31-36
PRMU, BioX 2018-03-18
15:45
Tokyo   A Preliminary Study on Estimating the Difficulty of Pedestrian Detection Adaptive to Vehicle Surrounding Environments Measured by LiDAR
Haruya Kyutoku, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide (Nagoya Univ.), Kazuki Kato (DENSO CORPORATION), Hiroshi Murase (Nagoya Univ.) BioX2017-48 PRMU2017-184
Results of pedestrian detectors from in-vehicle sensors still have room for improvement in real environments.
Therefore... [more]
BioX2017-48 PRMU2017-184
pp.73-78
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
MSS, NLP
(Joint)
2018-03-13
11:10
Osaka   Accelerating Pedestrian Detection Using Convolutional Neural Network
Naoya Koyama, Masaharu Adachi (Tokyo Denki Univ.) NLP2017-103
In recent years, pedestrian detection technologies become important in driving assistant systems. Pedestrian detection i... [more] NLP2017-103
pp.9-12
SANE 2017-08-25
13:30
Osaka OIT UMEDA Campus Discrimination Method of Pedestrians and Cars by Broadband Radar with Narrow Receiver Bandwidth
Kazuhiro Watanabe, Kenta Ishizaki, Manabu Akita, Takayuki Inaba (UEC) SANE2017-39
The authors have proposed a broadband radar system (stepped multiple frequency CPC radar) capable of multi-target separa... [more] SANE2017-39
pp.59-64
PRMU, CNR 2017-02-19
11:20
Hokkaido   [Poster Presentation] Study on Performance Improvement of Pedestrian Detection using Vehicular-to-Vehicular Communications
Ryosuke Kobayashi, Naoko Enami, Yumi Takaki, Tomio Kamada, Chikara Ohta (Kobe Univ.) PRMU2016-185 CNR2016-52
(To be available after the conference date) [more] PRMU2016-185 CNR2016-52
pp.167-168
PRMU, IPSJ-CVIM, IBISML [detail] 2016-09-05
09:00
Toyama   A Preliminarily Study on Multi-Frames Features for LIDAR-Based Pedestrian Detection
Yoshiki Tatebe, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.), Utsushi Sakai (DENSO) PRMU2016-57 IBISML2016-12
In this report, we study multi-frames features extracted by integrating point-clouds of LIDAR over multiple frames. We s... [more] PRMU2016-57 IBISML2016-12
pp.19-24
PRMU, IPSJ-CVIM, MVE [detail] 2016-01-22
09:30
Osaka   A study on the detection of a pedestrian holding an umbrella with a Selective DPM
Yuto Shimbo, Yasutomo Kawanishi, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.) PRMU2015-123 MVE2015-45
In recent years, pedestrian detection from an in-vehicle camera has been attracting interest.
However, in the case of a... [more]
PRMU2015-123 MVE2015-45
pp.163-168
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
IE, ITS, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] 2015-02-23
13:30
Hokkaido Hokkaido Univ. Image Feature Descriptor of Rotation-Invariant Gradient Orientation for Pedestrian Detection under Changes of Posture
Yuta Horikawa, Kousuke Matsushima (Kurume NCT) ITS2014-42 IE2014-69
Pedestrian recognition is an important subject of research in automotive safe driving support technology. Combining imag... [more] ITS2014-42 IE2014-69
pp.53-58
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
PRMU 2014-03-13
15:30
Tokyo   Accuracy improvement of pedestrian detection from in-vehicle camera images based on environment adaptation using location information
Daichi Suzuo, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.), Hiroyuki Ishida, Yoshiko Kojima (Toyota Central R&D Labs) PRMU2013-187
Recently, pedestrian detection techniques from in-vehicle camera images is being focused. However, since the environment... [more] PRMU2013-187
pp.115-120
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, CNR 2014-02-13
16:10
Fukuoka   [Poster Presentation] Pedestrian Detection by Channel Features based on Context
Yohei Takayanagi, Naoko Enami, Yasuo Ariki (Kobe Univ.) PRMU2013-144 CNR2013-52
In this paper, we propose the method of pedestrian detection based on context model between pedestrians and background.
... [more]
PRMU2013-144 CNR2013-52
pp.103-104
NC, MBE
(Joint)
2013-11-23
10:00
Miyagi Tohoku University Brain-style image recognition algorithm constructed from the human brain activity at higher visual cortices -- Application to the recognition of occluded pedestrian images --
Hiroyuki Hoshino, Takashi Owaki (TCRDL), Hiroki Kurashige, Kenichi Ueno, Topi Tanskanen, Kang Cheng, Hideyuki Cateau (RIKEN) NC2013-52
The purpose of our study is to improve the robustness of image recognition for pedestrians or vehicles occluded by other... [more] NC2013-52
pp.31-36
PRMU 2013-03-14
11:15
Tokyo   A study on a pedestrian detector adaptive to driving environment using in-vehicle camera and GPS
Daichi Suzuo, Hidefumi Yoshida, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.), Takashi Machida, Yoshiko Kojima (Toyota Central R&D Labs.) PRMU2012-190
Recently, pedestrian detection from in-vehicle camera images is being focused. However, it is difficult to detect pedest... [more] PRMU2012-190
pp.61-66
PRMU 2013-02-22
15:40
Osaka   GPU based implementation of the Human Detection and Tracking by Using Fish-eye Camera
Katsuhisa Kitaguchi, Mamoru Saito (OMTRI) PRMU2012-177
This paper presents a method for Graphic Processing Unit (GPU) based human detection and tracking by using fisheye camer... [more] PRMU2012-177
pp.227-231
PRMU, IBISML, IPSJ-CVIM
(Joint) [detail]
2012-09-03
11:00
Tokyo   A preliminary study on a pedestrian detector adaptive to the driving environment using an in-vehicle camera
Daichi Suzuo, Hidefumi Yoshida, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.), Takashi Machida, Yoshiko Kojima (Toyota Central R&D Labs., Inc.) PRMU2012-41 IBISML2012-24
Recently, pedestrian detection from in-vehicle camera images is being focused. However, it is difficult to detect pedest... [more] PRMU2012-41 IBISML2012-24
pp.99-104
PRMU, IBISML, IPSJ-CVIM
(Joint) [detail]
2012-09-03
16:00
Tokyo   A study on a method for high-accuracy detection of a pedestrian holding an umbrella with generative learning
Hidefumi Yoshida, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase (Nagoya Univ.), Takashi Machida, Yoshiko Kojima (Toyota Central R&D Labs., Inc.) PRMU2012-50 IBISML2012-33
Recently, pedestrian detection from in-vehicle camera images has become an interesting topic for researchers. Especially... [more] PRMU2012-50 IBISML2012-33
pp.191-196
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