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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 17 of 17  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU 2018-12-14
Miyagi   [Short Paper] Skeleton-based Human Action Recognition with Fine-to-Coarse Convolutional Neural Network
Thao Minh Le, Nakamasa Inoue, Koichi Shinoda (TokyoTech) PRMU2018-86
This work introduces a new framework for skeleton-based human action recognition. Existing approaches using Convolutiona... [more] PRMU2018-86
PRMU 2017-12-17
Kanagawa   Action Sequence Recognition in Videos by Combining a CTC Network with a Statistical Language Model
Mengxi Lin, Nakamasa Inoue, Koichi Shinoda (Tokyo Tech) PRMU2017-101
Action sequence recognition aims to recognize what actions occur in a video and their temporal order. In this paper, we ... [more] PRMU2017-101
PRMU, IPSJ-CVIM, MVE [detail] 2017-01-20
Kyoto   A Report on MIRU2016 Young Researchers' Program
Takuya Funatomi (NAIST), Masato Ishii (NEC), Nakamasa Inoue (Tokyo Tech), Asako Kanezaki (AIST), Kosuke Takahashi (NTT), Keisuke Doman (Chukyo Univ.), Takahiro Yoshioka (Fujitsu Labs.) PRMU2016-143 MVE2016-34
 [more] PRMU2016-143 MVE2016-34
PRMU 2015-12-22
Nagano   Video Semantic Indexing Using Vocabulary Expansion Based on Word Vectors
Nakamasa Inoue, Koichi Shinoda (TokyoTech) PRMU2015-105
(To be available after the conference date) [more] PRMU2015-105
PRMU, CNR 2015-02-20
Miyagi   Human Action Retrieval Based on Temporal Matching
Mengxi Lin, Nakamasa Inoue, Koichi Shinoda (Tokyo Tech) PRMU2014-139 CNR2014-54
 [more] PRMU2014-139 CNR2014-54
PRMU, CNR 2015-02-20
Miyagi   Spectral Graph Wavelets for Skeleton-based 3D Action Recognition
Tommi Kerola, Nakamasa Inoue, Koichi Shinoda (Tokyo Tech) PRMU2014-140 CNR2014-55
 [more] PRMU2014-140 CNR2014-55
PRMU 2014-03-13
Tokyo   Velocity Pyramid for Event Detection
Zhuolin Liang, Nakamasa Inoue, Koichi Shinoda (Tokyo Inst. of Tech.) PRMU2013-170
In this paper, we propose a new motion feature, a velocity pyramid, for multimedia event detection. In an event which is... [more] PRMU2013-170
PRMU 2014-03-13
Tokyo   Neighbor-to-Neighbor Search for Fast Image Classification
Nakamasa Inoue, Koichi Shinoda (Tokyo Inst. of Tech.) PRMU2013-184
(To be available after the conference date) [more] PRMU2013-184
PRMU 2013-02-22
Osaka   Video Semantic Indexing Using Video-Clip Scores and GMM Supervectors
Nakamasa Inoue, Koichi Shinoda (Tokyo Inst. of Tech.) PRMU2012-168
We propose a video-semantic-indexing system using video-clip scores and Gaussian-mixture-model (GMM) supervectors. The g... [more] PRMU2012-168
PRMU 2013-02-22
Osaka   Multimedia event detection using camera motion cancelled features and GMM supervectors
Yusuke Kamishima, Nakamasa Inoue, Koichi Shinoda (Tokyo Inst. of Tech.) PRMU2012-170
The number of studies for event detection from Internet videos has been increasing. Here, an event is defined as a combi... [more] PRMU2012-170
(Joint) [detail]
Tokyo   q-Gaussian Mixture Models for Video Semantic Indexing
Nakamasa Inoue, Koichi Shinoda (Tokyo Inst. of Tech.) PRMU2012-34 IBISML2012-17
Gaussian mixture models (GMMs) which extend the bag-of-visual-words (BoW) to a probabilistic framework have been proved ... [more] PRMU2012-34 IBISML2012-17
PRMU, SP 2012-02-10
Miyagi   Event detection from Video using GMM-Supervectors and SVMs
Yusuke Kamishima, Nakamasa Inoue, Koichi Shinoda (Tokyo Tech), Shunsuke Sato (Canon) PRMU2011-230 SP2011-145
In multimedia event detection, complex target events are detected from a large set of consumer domain videos taken in un... [more] PRMU2011-230 SP2011-145
PRMU, FM 2011-12-16
Shizuoka Hamamatsu Campus, Shizuoka Univ. [Special Talk] Toward High-Performance Video Semantic Indexing
Nakamasa Inoue, Koichi Shinoda (Tokyo Tech) PRMU2011-140
TokyoTech, in collaboration with Canon Inc., achieved the best performance in the Semantic Indexing task of TRECVID2011 ... [more] PRMU2011-140
PRMU, DE 2011-06-07
Kanagawa   Fast Semantic Indexing Using Tree-structured GMMs
Nakamasa Inoue, Koichi Shinoda (Tokyo Tech) DE2011-19 PRMU2011-50
We propose a fast semantic indexing method for large scale video resources using tree-structured Gaussian mixture models... [more] DE2011-19 PRMU2011-50
PRMU 2011-02-17
Saitama   A Multi-modal, Multi-frame Approach for Semantic Indexing in TRECVID
Nakamasa Inoue, Yusuke Kamishima, Koichi Shinoda (Tokyo Tech) PRMU2010-212
We propose a multi-modal, multi-frame approach for semantic indexing in the TRECVID 2010 workshop. The goal of the seman... [more] PRMU2010-212
IBISML, PRMU, IPSJ-CVIM [detail] 2010-09-05
Fukuoka Fukuoka Univ. Multiple Kernel Learning for Generic Object Recognition Using SIFT Gaussian Mixture Models
Nakamasa Inoue, Yusuke Kamishima, Koichi Shinoda, Sadaoki Furui (Tokyo Tech) PRMU2010-58 IBISML2010-30
We propose a statistical framework for generic object recognition using SIFT Gaussian mixture models (GMMs) and multiple... [more] PRMU2010-58 IBISML2010-30
PRMU 2009-11-27
Ishikawa Ishikawa Industrial Promotion Center High-level Feature Extraction from Video Using SIFT GMM and Acoustic Features
Nakamasa Inoue, Tatsuhiko Saito, Koichi Shinoda, Sadaoki Furui (Tokyo Inst. of Tech) PRMU2009-106
We propose a statistical framework for high-level feature (HLF) extraction, which employs SIFT Gaussian Mixture Models (... [more] PRMU2009-106
 Results 1 - 17 of 17  /   
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