Towards Universal Haptic Library: Library-Based Haptic Texture Assignment Using Image Texture and Perceptual Space

被引:0
|
作者
Hassan, Waseem [1 ]
Abdulali, Arsen [1 ]
Jeon, Seokhee [1 ]
机构
[1] Kyung Hee Univ, Dept Comp Sci & Engn, 1732 Deogyeong Daero, Yongin 17104, Gyeonggi Do, South Korea
关键词
Perceptual space; Image feature; Multidimensional scaling; Haptic texture; Image texture;
D O I
10.1007/978-981-10-4157-0_69
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this study we focused on building a universal haptic texture models library. This library is used to automatically assign haptic texture models to any given surface based on image features. The library is built from one time data-driven modeling of a large number (84) of textured surfaces, which cover most of the daily life haptic interactions. In this demonstration, we will show automatic assignment of haptic texture models to new arbitrary textured surfaces based on their image features, from the universal haptic library of haptic texture models. Afterwards, the automatically assigned haptic model will be rendered.
引用
收藏
页码:415 / 417
页数:3
相关论文
共 24 条
  • [21] Efficient image-based projective mapping using the master texture space encoding
    Guinnip, D
    Rice, D
    Jaynes, C
    Stevens, R
    WSCG 2003 SHORT PAPERS, PROCEEDINGS, 2003, : 49 - 56
  • [22] Image retrieval based on texture using latent space representation of discrete Fourier transformed maps
    Surajit Saikia
    Laura Fernández-Robles
    Enrique Alegre
    Eduardo Fidalgo
    Neural Computing and Applications, 2021, 33 : 13301 - 13316
  • [23] Image retrieval based on texture using latent space representation of discrete Fourier transformed maps
    Saikia, Surajit
    Fernandez-Robles, Laura
    Alegre, Enrique
    Fidalgo, Eduardo
    NEURAL COMPUTING & APPLICATIONS, 2021, 33 (20): : 13301 - 13316
  • [24] 3D skin surface reconstruction from a single image by merging global curvature and local texture using the guided filtering for 3D haptic palpation
    Lee, K.
    Kim, M.
    Kim, K.
    SKIN RESEARCH AND TECHNOLOGY, 2018, 24 (04) : 672 - 685