Vector representation of user's view using self-organizing map

被引:2
作者
Ae, T [1 ]
Yamaguchi, T [1 ]
Monden, E [1 ]
Kawabata, S [1 ]
Kamitani, M [1 ]
机构
[1] Hiroshima Univ, Grad Sch Engn, Higashihiroshima 7398527, Japan
来源
IMAGE PROCESSING: ALGORITHMS AND SYSTEMS III | 2004年 / 5298卷
关键词
vector representation of user's view; self organizing map; hidden Markov model;
D O I
10.1117/12.524398
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
There exist various objects, such as pictures, music, texts, etc., around our environment. We have a view for these objects by looking, reading or listening. Our view is concerned with our behaviors deeply, and is very important to understand our behaviors. Therefore, we propose a method which acquires a view as a vector, and apply the vector to sequence generation. We focus on sequences of the data of which a user selects from a multimedia database containing pictures, music, movie, etc.. These data cannot be stereotyped because user's view for them changes by each user. Therefore, we represent the structure of the multimedia database as the vector representing user's view and the stereotyped vector, and acquire sequences containing the structure as elements. We demonstrate a city-sequence generation system which reflects user's intension as an application of sequence generation containing user's view. We apply the self-organizing map to this system to represent user's view.
引用
收藏
页码:384 / 394
页数:11
相关论文
共 16 条
  • [11] MA Q, 2001, IPSJ J, V42, P2379
  • [12] A TUTORIAL ON HIDDEN MARKOV-MODELS AND SELECTED APPLICATIONS IN SPEECH RECOGNITION
    RABINER, LR
    [J]. PROCEEDINGS OF THE IEEE, 1989, 77 (02) : 257 - 286
  • [13] TERAMOTO K, 1995, 101 IPSJ SIG
  • [14] USUI D, 1999, IPSJ J, V40, P1774
  • [15] USUKI H, 1998, 26 INF P SOC JAP, P39
  • [16] Clustering of the self-organizing map
    Vesanto, J
    Alhoniemi, E
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2000, 11 (03): : 586 - 600