Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
PRMU, BioX |
2018-03-18 10:15 |
Tokyo |
|
[Invited Talk]
Why signature now Takashi Matsumoto (Cool Design/Waseda University) |
Even with a good idea, technology does not see the light of day unless there is a request from society. As of 2018, requ... [more] |
|
PRMU, BioX |
2018-03-18 11:10 |
Tokyo |
|
Learning Convolutional Autoencoders Using a Loss Function Based on Spatial Frequencies and Colors Naoyuki Ichimura (AIST) BioX2017-36 PRMU2017-172 |
This paper presents a learning method for convolutional autoencoders (CAEs) for extracting features from images. CAEs ca... [more] |
BioX2017-36 PRMU2017-172 pp.1-6 |
PRMU, BioX |
2018-03-18 11:35 |
Tokyo |
|
Pyramid Transform Revised Kento Hosoya, Atsushi Imiya (Chiba Univ.) BioX2017-37 PRMU2017-173 |
[more] |
BioX2017-37 PRMU2017-173 pp.7-12 |
PRMU, BioX |
2018-03-18 11:10 |
Tokyo |
|
Simultaneous Learning Model of Food Image Recognition and Ingrediensts Estimation Koyo Ito, Takao Yamanaka (Sophia Univ.) BioX2017-38 PRMU2017-174 |
In recent years, many health-care applications such as food diary have been developed for smart devices. It is important... [more] |
BioX2017-38 PRMU2017-174 pp.13-18 |
PRMU, BioX |
2018-03-18 11:35 |
Tokyo |
|
Estimating 2D Gaze Coordinates from Efficiently Compressed Face Images Reo Ogusu, Takao Yamanaka (Sophia Univ.) BioX2017-39 PRMU2017-175 |
[more] |
BioX2017-39 PRMU2017-175 pp.19-24 |
PRMU, BioX |
2018-03-18 13:30 |
Tokyo |
|
Multi-Element Deep Learning Using False Detection Images for Training Set
-- Effective For License Plate Detection -- Kazuo Ohzeki, Yoshikazu Kido, Yutaka Hirakawa (Shibaura Inst. of Tech.), Stefan Schneider (UAS Kempten) BioX2017-40 PRMU2017-176 |
In deep learning, in order to improve learning performance, preprocessing and ingenuity to combine a plurality of discri... [more] |
BioX2017-40 PRMU2017-176 pp.25-30 |
PRMU, BioX |
2018-03-18 13:55 |
Tokyo |
|
Feature extraction of object shape from motion parallax using convolutional neural network ChengJun Shao, Makoto Murakami (Toyo Univ.) BioX2017-41 PRMU2017-177 |
The convolution neural networks (CNN) have good feature extraction capability. In this paper, we propose a method which ... [more] |
BioX2017-41 PRMU2017-177 pp.31-36 |
PRMU, BioX |
2018-03-18 14:20 |
Tokyo |
|
A Study of Fast Image Matching Method Under Translation, Scale and Rotation Toru Takahashi, Kengo Makino, Yuta Kudo, Rui Ishiyama (NEC) BioX2017-42 PRMU2017-178 |
This paper presents a fast pattern matching method which covers image translation, rotation and scaling. Pattern matchin... [more] |
BioX2017-42 PRMU2017-178 pp.37-42 |
PRMU, BioX |
2018-03-18 13:30 |
Tokyo |
|
Investigation of Speaker Verification Performance Using Air and Ear Microphones in Various Acoustic Conditions Qiongqiong Wang, Koji Okabe, Shivangi Mahto, Takafumi Koshinaka (NEC) BioX2017-43 PRMU2017-179 |
This paper presents an experimental study on speaker verification performances using air and ear microphones in various ... [more] |
BioX2017-43 PRMU2017-179 pp.43-48 |
PRMU, BioX |
2018-03-18 13:55 |
Tokyo |
|
A Study on Human Reflex Based Biometric Authentication Using Eye-Head Coordination (part 2) Yosuke Takahashi, Masashi Endo, Hiroaki Matsuno, Hiroaki Muramatsu, Tetsushi Ohki, Masakatsu Nishigaki (Shizuoka Univ.) BioX2017-44 PRMU2017-180 |
Biometric information could be easily leaked and/or copied. Therefore, biometric authentication in which biometric infor... [more] |
BioX2017-44 PRMU2017-180 pp.49-54 |
PRMU, BioX |
2018-03-18 14:20 |
Tokyo |
|
A study on multi-factor authentication with usage environment recognition function Tomoaki Higashi, Yasushi Yamazaki (Univ. of Kitakyushu), Tetsushi Ohki (Shizuoka Univ.) BioX2017-45 PRMU2017-181 |
In recent years, with the rapid spread of smart devices, such as smart-phones and tablet PCs, biometric authentication u... [more] |
BioX2017-45 PRMU2017-181 pp.55-60 |
PRMU, BioX |
2018-03-18 14:45 |
Tokyo |
|
A Kinect-based Multimodal Person Authentication System with User Existence Confirmation Lin Zhou, Koji Iwano (Tokyo City Univ.) BioX2017-46 PRMU2017-182 |
Person identification systems used for receiving pension need to have countermeasures against fraud by "spoofing" as ann... [more] |
BioX2017-46 PRMU2017-182 pp.61-66 |
PRMU, BioX |
2018-03-18 15:20 |
Tokyo |
|
Person Image Retrieval Considering People Co-occurrence Relations in Group Photos Yukiya Fujita, Naoko Nitta, Kazuaki Nakamura, Noboru Babaguchi (Osaka Univ.) BioX2017-47 PRMU2017-183 |
(To be available after the conference date) [more] |
BioX2017-47 PRMU2017-183 pp.67-71 |
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 |
|
Toward image inbetweening using Latent Model Paulino Cristovao (Univ. of Tsukuba), Yusuke Tanimura, Hidemoto Nakada, Hideki Asoh (AIST) BioX2017-49 PRMU2017-185 |
Image interpolation is a well known problem in computer vision. Many approaches are restricted to optical flow and convo... [more] |
BioX2017-49 PRMU2017-185 pp.79-84 |
PRMU, BioX |
2018-03-18 15:20 |
Tokyo |
|
Saliency Map Estimation for Omni-Directional Image Considering Prior Distribution Tatsuya Suzuki, Takao Yamanaka (Sophia Univ.) BioX2017-50 PRMU2017-186 |
In recent years, the Deep Learning techniques have been applied to the estimation of saliency maps, which represent prob... [more] |
BioX2017-50 PRMU2017-186 pp.85-90 |
PRMU, BioX |
2018-03-18 15:45 |
Tokyo |
|
Drowsiness estimation using eye opening degree histograms Takahiro Matsuda, Atsushi Nakazawa (Kyoto Univ.), Masanori Hashizaki, Koichi Kinoshita (OMRON Co.), Toyoaki Nishida (Kyoto Univ.) BioX2017-51 PRMU2017-187 |
(To be available after the conference date) [more] |
BioX2017-51 PRMU2017-187 pp.91-96 |
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 |
2018-03-18 16:45 |
Tokyo |
|
Evaluation of the Shot Boundary Detection Method based on Unsupervised Learning from Video Big Data Norio Katayama, Hiroshi Mo, Shin'ichi Satoh (NII) BioX2017-53 PRMU2017-189 |
Video data is a sequence of video frames and their temporal continuity
is an essential property of video stream. In th... [more] |
BioX2017-53 PRMU2017-189 pp.103-108 |
PRMU, BioX |
2018-03-18 17:10 |
Tokyo |
|
BioX2017-54 PRMU2017-190 |
(To be available after the conference date) [more] |
BioX2017-54 PRMU2017-190 pp.109-114 |