Motion retrieval with ensemble multiple instance learning based on mocap database

被引：0
|
作者：
Zhu, Hongli [1 ]
Xiang, Jian [2 ]
Yu, Fei [3 ]
机构：
[1] ZheJiang Univ City Coll, Hangzhou 310015, Zhejiang, Peoples R China
[2] ZheJiang Univ Sci & Technol, Hangzhou 310023, Zhejiang, Peoples R China
[3] Guangdong Univ Business Studies, Guangdong Prov Key Lab Elect Commerce Market Appl, Guangzhou 510320, Guangdong, Peoples R China
来源：
IMECS 2007: INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, VOLS I AND II | 2007年
关键词：
3D temporal-spatial; data driven; decision tree; multiple instance; ensemble; motion retrieval;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In order to retrieve similar motion data from Mocap database, each human joint's motion clip is regarded as a bag, while each of its segments is regarded as an instance. 3D temporal-spatial features are extracted and data driven decision trees based on ensemble multiple instance are automatically constructed to reflect the influence of each point during the comparison of motion similarity. At last we use the method of multiple instance retrieval to complete motion retrieval. Experiment results show that our approaches are effective for motion data retrieval.
引用
收藏
页码：1445 / +
页数：3
相关论文
共 50 条
  • [41] An Iterative Instance Selection Based Framework for Multiple-Instance Learning
    Yuan, Liming
    Wen, Xianbin
    Zhao, Lu
    Xu, Haixia
    [J]. 2018 IEEE 30TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI), 2018, : 772 - 779
  • [42] A new multiple instance learning algorithm based on instance-consistency
    Wu Z.
    Zhang M.
    Wan S.
    Yue L.
    [J]. Wu, Zhize (wuzhize.ustc@gmail.com), 1600, Totem Publishers Ltd (13): : 519 - 529
  • [43] Multiple instance learning for medical image classification based on instance importance
    Struski, Lukasz
    Janusz, Szymon
    Tabor, Jacek
    Markiewicz, Michal
    Lewicki, Arkadiusz
    [J]. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2024, 91
  • [44] DICTIONARY-BASED MULTIPLE INSTANCE LEARNING
    Shrivastava, Ashish
    Pillai, Jaishanker K.
    Patel, Vishal M.
    Chellappa, Rama
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2014, : 160 - 164
  • [45] A Comparison of Multiple Instance and Group Based Learning
    Brossi, Steven D.
    Bradley, Andrew P.
    [J]. 2012 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING TECHNIQUES AND APPLICATIONS (DICTA), 2012,
  • [46] Ensemble learning HMM for motion recognition and retrieval by Isomap dimension reduction
    Xiang J.
    Weng J.-G.
    Zhuang Y.-T.
    Wu F.
    [J]. Journal of Zhejiang University-SCIENCE A, 2006, 7 (12): : 2063 - 2072
  • [47] Ensemble learning HMM for motion recognition and retrieval by Isomap dimension reduction
    XIANG Jian
    [J]. Journal of Zhejiang University-Science A(Applied Physics & Engineering), 2006, (12) : 2063 - 2072
  • [48] A multi-instance learning based approach to image retrieval
    Dai, Hong-Bin
    Zhang, Min-Ling
    Zhou, Zhi-Hua
    [J]. Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence, 2006, 19 (02): : 179 - 185
  • [49] Localized content-based image retrieval using semi-supervised multiple instance learning
    Zhang, Dan
    Shi, Zhenwei
    Song, Yangqiu
    Zhang, Changshui
    [J]. COMPUTER VISION - ACCV 2007, PT I, PROCEEDINGS, 2007, 4843 : 180 - +
  • [50] Deep Learning for Instance Retrieval: A Survey
    Chen, Wei
    Liu, Yu
    Wang, Weiping
    Bakker, Erwin M.
    Georgiou, Theodoros
    Fieguth, Paul
    Liu, Li
    Lew, Michael S.
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 45 (06) : 7270 - 7292
12345