Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
PRMU, IBISML, IPSJ-CVIM [detail] |
2023-03-03 09:10 |
Hokkaido |
Future University Hakodate (Primary: On-site, Secondary: Online) |
Unknown Object Segmentation by View Independent Scene Change Detection Li Jiaxin (Nagoya Univ.), Yasutomo Kawanishi (RIKEN), Daisuke Deguchi, Hiroshi Murase (Nagoya Univ.) PRMU2022-99 IBISML2022-106 |
Exploring the indoor environment and finding unknown objects that appeared in a scene is important for scene understandi... [more] |
PRMU2022-99 IBISML2022-106 pp.211-216 |
EA, SIP, SP |
2019-03-15 13:30 |
Nagasaki |
i+Land nagasaki (Nagasaki-shi) |
[Poster Presentation]
Robustness of statistical voice conversion based on waveform modification against external noise Yusuke Kurita, Kazuhiro Kobayashi, Kazuya Takeda (Nagoya Univ.), Tomoki Toda (Nagoya Univ./JST PRESTO) EA2018-153 SIP2018-159 SP2018-115 |
In this report, we investigate the statistical voice conversion (VC) under noisy environments.
VC achieves conversion f... [more] |
EA2018-153 SIP2018-159 SP2018-115 pp.317-322 |
PRMU |
2017-12-17 17:00 |
Kanagawa |
|
A Background Subtraction Method with an Image Set as a Background Model Yuya Kasahara, Toru Abe, Takuo Suganuma (Tohoku Univ.) PRMU2017-111 |
Background subtraction method is one of the approaches for extractingthe regions of moving objects such as people and ve... [more] |
PRMU2017-111 pp.65-70 |
PRMU, IE, MI, SIP |
2017-05-26 12:00 |
Aichi |
|
Background Modeling based on Gaussian Mixture Model using Spatial Features Kan Zheng, Toshio Kondo, Yuki Fukazawa, Takahiro Sasaki (Mie Univ.) SIP2017-24 IE2017-24 PRMU2017-24 MI2017-24 |
Many methods for detecting a moving object from surveillance video using a background model have been proposed. Mixed Ga... [more] |
SIP2017-24 IE2017-24 PRMU2017-24 MI2017-24 pp.125-130 |
MI |
2015-03-03 13:40 |
Okinawa |
Hotel Miyahira |
Target Extraction from X-ray Image Sequence by using Gaussian Mixture Model for Lung Tumor Tracking Naoki Shibusawa, Kei Ichiji, Yusuke Yoshida, Xiaoyang Zhang, Noriyasu Homma (Tohoku Univ.), Yoshihiro Takai (Hirosaki Univ.), Makoto Yoshizawa (Tohoku Univ.) MI2014-110 |
During treatment fraction, accurate tracking of moving tumor by using X-ray imaging is important for radiation therapy.
... [more] |
MI2014-110 pp.277-282 |
IA, IN (Joint) |
2014-12-19 14:20 |
Hiroshima |
Hiroshima City University |
Traffic Classification on Mobile Network Considering Various Types of Network Traffic Flow Masaki Suzuki, Masafumi Watari, Shigehiro Ano (KDDI Labs.), Masato Tsuru (Kyutech) IN2014-96 |
The amount of mobile traffic data has been increasing in the recent years since the smartphones have become widely used ... [more] |
IN2014-96 pp.29-34 |
MICT, WBS |
2014-07-29 12:30 |
Osaka |
Osaka City Univ. (Umeda Satellite) |
[Poster Presentation]
On BER Performance of Optical Wireless Turbo Codes with UTPA Rai Sachin, Hiromasa Habuchi (Ibaraki Univ.) WBS2014-20 MICT2014-34 |
In this paper, Bit Error Ratio (BER) performance of standard and punctured turbo code with Unequal Transmission Power Al... [more] |
WBS2014-20 MICT2014-34 pp.63-66 |
PRMU, CNR |
2014-02-13 16:10 |
Fukuoka |
|
[Poster Presentation]
Background Modeling using Exponentially Weighted Histogram Tsubasa Minematsu, Masaki Igarashi, Atsushi Shimada, Hajime Nagahara, Rin-ichiro Taniguchi (Kyushu Univ.) PRMU2013-142 CNR2013-50 |
In this paper, we propose a nonparametric background modeling for background subtraction using exponentially weighted hi... [more] |
PRMU2013-142 CNR2013-50 pp.99-100 |
PRMU |
2013-02-22 16:40 |
Osaka |
|
An Embedded Background Modeling Method for Detecting Object Left Behind and Very Still Person Thi Thi Zin, Hiromitsu Hama, Takashi Toriu, Pyke Tin (Osaka City Univ.) PRMU2012-179 |
This paper proposes an embedded background modeling method for detecting object left behind and very still person in pub... [more] |
PRMU2012-179 pp.239-244 |
PRMU, MVE, IPSJ-CVIM (Joint) [detail] |
2013-01-24 09:30 |
Kyoto |
|
Object Detection based on Light Field Sensing Atsushi Shimada, Hajime Nagahara, Rin-ichiro Taniguchi (Kyushu Univ.) PRMU2012-106 MVE2012-71 |
This paper discusses about object detection based on light field sensing. Our proposed method generates an arbitrary foc... [more] |
PRMU2012-106 MVE2012-71 pp.205-210 |
PRMU, SP |
2012-02-10 10:00 |
Miyagi |
|
Evaluation of Case-Based Background Model Yosuke Nonaka, Atsushi Shimada, Hajime Nagahara, Rin-ichiro Taniguchi (Kyushu Univ.) PRMU2011-226 SP2011-141 |
Background subtraction is one of the important techniques for object detection. In general, there is a trade-off problem... [more] |
PRMU2011-226 SP2011-141 pp.179-184 |
PRMU, FM |
2011-12-16 09:30 |
Shizuoka |
Hamamatsu Campus, Shizuoka Univ. |
Condition-Driven Background Modeling Atsushi Shimada, Hajime Nagahara, Rin-ichiro Taniguchi (Kyushu Univ.) PRMU2011-136 |
Background modeling and subtraction is an essential task in video surveillance applications. Many researchers have been... [more] |
PRMU2011-136 pp.65-70 |
PRMU |
2011-02-18 14:30 |
Saitama |
|
Probabilistic Background Texture Modeling for Object Detection Satoshi Yoshinaga, Atsushi Shimada, Hajime Nagahara, Rin-ichiro Taniguchi (Kyushu Univ.) PRMU2010-232 |
We propose a new method of background modeling, which is considering the background texture, to detect objects. Many bac... [more] |
PRMU2010-232 pp.153-158 |
PRMU |
2009-11-27 10:40 |
Ishikawa |
Ishikawa Industrial Promotion Center |
Object Detection based on Mutual Modeling between Foreground and Background Atsushi Shimada, Rin-ichiro Taniguchi (Kyushu Univ.) PRMU2009-120 |
Background modeling has been widely researched to detect moving objects from image sequences including various changes o... [more] |
PRMU2009-120 pp.189-194 |
PRMU |
2009-06-18 13:55 |
Hokkaido |
Hokkaido Univ. |
Object Detection System using Region-Level Layered Background Subtraction and Feature Point Based Tracking Shigeyuki Odashima, Taketoshi Mori, Masamichi Shimosaka, Hiroshi Noguchi, Tomomasa Sato (The Univ. of Tokyo) PRMU2009-45 |
This paper proposes an object detection method in indoor environments. With object placement and removal, the input imag... [more] |
PRMU2009-45 pp.31-36 |
PRMU |
2009-03-14 15:30 |
Miyagi |
Tohoku Institute of Technology |
Object Segmentation Based on Adaptive Background Model Considering Spatio-temporal Features Tatsuya Tanaka, Atsushi Shimada (Kyushu Univ.), Daisaku Arita (ISIT), Rin-ichiro Taniguchi (Kyushu Univ.) PRMU2008-282 |
We propose a new method for background modeling considering spatio-temporal features. Our method consists of three compl... [more] |
PRMU2008-282 pp.281-286 |
SP, NLC |
2008-12-09 11:15 |
Tokyo |
Waseda Univ. |
Music suppression method for single channel speech mixed with BGM using Bayesian networks Hiroaki Itou, Takanori Nishino, Norihide Kitaoka, Kazuya Takeda (Nagoya Univ.) NLC2008-27 SP2008-82 |
A non-parametric stochastic method of the single-channel speech extraction from a mixture of speech and music is propose... [more] |
NLC2008-27 SP2008-82 pp.19-24 |
PRMU, HIP |
2008-09-06 16:30 |
Kanagawa |
Keio Univ. |
Abnormal Motion Detection at Escalator Scene based on Spatio-temporal Features Yasuhiro Murai, Hironobu Fujiyoshi (Chubu Univ.), Masato Kazui (Hitachi, Ltd.) PRMU2008-87 HIP2008-87 |
This paper presents a method for detecting abnormal motion at an escalator scene, in which the movement of the escalator... [more] |
PRMU2008-87 HIP2008-87 pp.247-254 |
PRMU, IE |
2008-03-11 16:35 |
Ishikawa |
|
Object Detection Based on Mixture of Radial Reach Filter under Varying Illumination Tatsuya Tanaka, Atsushi Shimada (Kyushu Univ.), Daisaku Arita (ISIT), Rin-ichiro Taniguchi (Kyushu Univ.) IE2007-338 PRMU2007-322 |
We propose a new method for background modeling based on Radial Reach Filter(RRF) known as robust background subtraction... [more] |
IE2007-338 PRMU2007-322 pp.501-506 |
PRMU, IE |
2008-03-11 17:05 |
Ishikawa |
|
Object Detection Based on Gaussian Mixture Predictive Background Model under Varying Illumination Atsushi Shimada, Tatsuya Tanaka (Kyushu Univ.), Daisaku Arita (ISIT), Rin-ichiro Taniguchi (Kyushu Univ.) IE2007-339 PRMU2007-323 |
We propose a new method to create adaptive background models. Traditionally, each pixel has an adaptive background mode... [more] |
IE2007-339 PRMU2007-323 pp.507-512 |