Eye movement computation model based on short-term memory optical flow image

被引:3
|
作者
Morita, S [1 ]
机构
[1] Yamaguchi Univ, Fac Engn, Ube, Yamaguchi 7558611, Japan
关键词
D O I
10.1109/MFI-2003.2003.1232569
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper we introduced a computation model of eye movement using the short-term memory optical flow image. We also applied this model into the simulation of driver's eye movements in an open road. The computation model of the eye movement is based on the parallel tasks and the short-term memory. It is especially important to realize certain driving tasks which involve tracking the moving vehicles, identifying road sign, and estimating the road shape. The short-term memories corresponding to tasks are used due to change the attention region. We show that the viewpoint moves smoothly in the wide region by using the short-term memory image generated by the low-level features of the optical flow. We simulate the driver's eye movement and show the efficiency of this model.
引用
收藏
页码:3 / 8
页数:6
相关论文
共 50 条
  • [41] Model of a neuron with afterdepolarization and short-term memory
    Klin'shov V.V.
    Nekorkin V.I.
    Radiophysics and Quantum Electronics, 2005, 48 (3) : 203 - 211
  • [42] A review on the long short-term memory model
    Van Houdt, Greg
    Mosquera, Carlos
    Napoles, Gonzalo
    ARTIFICIAL INTELLIGENCE REVIEW, 2020, 53 (08) : 5929 - 5955
  • [43] MEANINGFULNESS AND SHORT-TERM MEMORY - TEST OF A MODEL
    SALTZ, E
    MODIGLIA.V
    JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 1970, 86 (02): : 309 - &
  • [44] A new model of verbal short-term memory
    Morra, S
    JOURNAL OF EXPERIMENTAL CHILD PSYCHOLOGY, 2000, 75 (03) : 191 - 227
  • [45] MFOA-Bi-LSTM: An optimized bidirectional long short-term memory model for short-term traffic flow prediction
    Naheliya, Bharti
    Redhu, Poonam
    Kumar, Kranti
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2024, 634
  • [46] A review on the long short-term memory model
    Greg Van Houdt
    Carlos Mosquera
    Gonzalo Nápoles
    Artificial Intelligence Review, 2020, 53 : 5929 - 5955
  • [47] Predicting Short-term Traffic Flow by Long Short-Term Memory Recurrent Neural Network
    Tian, Yongxue
    Pan, Li
    2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY), 2015, : 153 - 158
  • [48] Water Flow Forecasting Based on River Tributaries Using Long Short-Term Memory Ensemble Model
    Costa Silva, Diogo F.
    Galvao Filho, Arlindo R.
    Carvalho, Rafael V.
    de Souza L. Ribeiro, Filipe
    Coelho, Clarimar J.
    ENERGIES, 2021, 14 (22)
  • [49] Short-term Elevator Traffic Flow Estimation with Hybrid Long Short-Term Memory Network
    Zheng, Qi
    Zhao, Chunhui
    2020 CHINESE AUTOMATION CONGRESS (CAC 2020), 2020, : 7141 - 7146
  • [50] Credit Risk Assessment Based on Long Short-Term Memory Model
    Zhang, Yishen
    Wang, Dong
    Chen, Yuehui
    Shang, Huijie
    Tian, Qi
    INTELLIGENT COMPUTING THEORIES AND APPLICATION, ICIC 2017, PT II, 2017, 10362 : 700 - 712