A Hybrid Approach to Keyframe Extraction from Motion Capture Data Using Curve Simplification and Principal Component Analysis

被引：7

作者：

Miura, Takeshi ^{[1
]}

Kaiga, Takaaki ^{[1
,2
]}

Shibata, Takeshi ^{[1
]}

Katsura, Hiroaki ^{[1
]}

Tajima, Katsubumi ^{[1
]}

Tamamoto, Hideo ^{[1
]}

机构：

[1] Akita Univ, Akita 0108502, Japan

[2] Warabi Za Co Ltd, Semboku City, Akita 0141192, Japan

来源：

IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING | 2014年 / 9卷 / 06期

关键词：

motion capture; keyframe; curve simplification; principal component analysis;

D O I：

10.1002/tee.22029

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we propose a novel method to extract keyframes from motion capture data. A hybrid approach, which combines a curve-simplification algorithm with an initialization procedure including principal component analysis, is adopted. The developed method automatically extracts an appropriate number of keyframes at high speed without performance degradation. Experimental results prove the effectiveness of the present method. (c) 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

引用

页码：697 / 699

页数：3

共 50 条

[21] Extraction of a deterministic component from ROSAT X-ray data using a wavelet transform and the principal component analysis II. The data analysis
Liszka, L
Pacholczyk, AG
Stoeger, WR
[J]. ASTRONOMY & ASTROPHYSICS, 2000, 354 (03): : 847 - 852
[22] Analysis of lip motion using principal component analyses
Mishima, Katsuaki
Yamada, Tomohiro
Matsumura, Tatsushi
Moritani, Norifumi
[J]. JOURNAL OF CRANIO-MAXILLOFACIAL SURGERY, 2011, 39 (04) : 232 - 236
[23] Principal component analysis of interval data: a symbolic data analysis approach
Carlo N. Lauro
Francesco Palumbo
[J]. Computational Statistics, 2000, 15 : 73 - 87
[24] Principal component analysis of interval data: a symbolic data analysis approach
Lauro, CN
Palumbo, F
[J]. COMPUTATIONAL STATISTICS, 2000, 15 (01) : 73 - 87
[25] Feature Extraction of Hyperspectral Image Using Principal Component Analysis and Folded-Principal Component Analysis
Deepa, P.
Thilagavathi, K.
[J]. 2015 2ND INTERNATIONAL CONFERENCE ON ELECTRONICS AND COMMUNICATION SYSTEMS (ICECS), 2015, : 656 - 660
[26] Feature Extraction of Autism Gait Data Using Principal Component Analysis and Linear Discriminant Analysis
Ilias, Suryani
Tahir, Nooritawati Md
Jailani, Rozita
[J]. 2016 IEEE INDUSTRIAL ELECTRONICS AND APPLICATIONS CONFERENCE (IEACON), 2016, : 275 - 279
[27] Analysis of EEG using principal component approach
Padmasai, Y.
SubbaRao, K.
Rao, C. Raghavendra
Jayalakshmi, S. Sita
[J]. 2007 14TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS AND SYSTEMS, VOLS 1-4, 2007, : 134 - +
[28] Principal Component Analysis: A Natural Approach to Data Exploration
Gewers, Felipe L.
Ferreira, Gustavo R.
De Arruda, Henrique F.
Silva, Filipi N.
Comin, Cesar H.
Amancio, Diego R.
Costa, Luciano Da F.
[J]. ACM COMPUTING SURVEYS, 2021, 54 (04)
[29] Principal-component analysis of sea-ice motion from satellite data
Zhao, YH
Liu, AK
[J]. ANNALS OF GLACIOLOGY, VOL 33, 2001, 33 : 133 - 138
[30] Quantitative information extraction from gas sensor data using principal component regression
Ozmen, Ahmet
Mumyakmaz, Bekir
Ebeoglu, Mehmet Ali
Tasaltin, Cihat
Gurol, Ilke
Ozturk, Zafer Ziya
Dural, Deniz
[J]. TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2016, 24 (03) : 946 - 960

← 1 2 3 4 5 →