AN IDEAL OBSERVER MODEL FOR SHAPE FROM TEXTURE

被引：0
|
作者：
ROSENHOLTZ, R [1 ]
MALIK, J [1 ]
机构：
[1] UNIV CALIF BERKELEY,DEPT ELECT ENGN & COMP SCI,BERKELEY,CA 94720
来源：
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE | 1994年 / 35卷 / 04期
关键词：
D O I：
暂无
中图分类号：
R77 [眼科学];
学科分类号：
100212 ;
摘要：
引用
收藏
页码：1668 / 1668
页数：1
相关论文
共 50 条
  • [1] A new observer model of 3-D shape from texture cues
    Li, A.
    Zaidi, Q.
    PERCEPTION, 2001, 30 : 9 - 9
  • [2] SHAPE FROM TEXTURE - IDEAL OBSERVERS AND HUMAN PSYCHOPHYSICS
    BLAKE, A
    BULTHOFF, HH
    SHEINBERG, D
    VISION RESEARCH, 1993, 33 (12) : 1723 - 1737
  • [3] A COMPUTATIONAL MODEL FOR SHAPE FROM TEXTURE
    MALIK, J
    ROSENHOLTZ, R
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 1993, 34 (04) : 1290 - 1290
  • [4] A COMPUTATIONAL MODEL FOR SHAPE FROM TEXTURE
    MALIK, J
    ROSENHOLTZ, R
    HIGHER-ORDER PROCESSING IN THE VISUAL SYSTEM, 1994, 184 : 272 - 283
  • [5] Beliefs About Perception Shape Perceptual Inference: An Ideal Observer Model of Detection
    Mazor, Matan
    Moran, Rani
    Press, Clare
    PSYCHOLOGICAL REVIEW, 2025,
  • [6] AN IDEAL OBSERVER MODEL OF READING
    LEGGE, GE
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 1992, 33 (04) : 1414 - 1414
  • [7] Haptic SLAM: An Ideal Observer Model for Bayesian Inference of Object Shape and Hand Pose from Contact Dynamics
    Behbahani, Feryal M. P.
    Singla-Buxarrais, Guillem
    Faisal, A. Aldo
    HAPTICS: PERCEPTION, DEVICES, CONTROL, AND APPLICATIONS, EUROHAPTICS 2016, PT I, 2016, 9774 : 146 - 157
  • [8] Perception of surface orientation from texture: Perceptual strategies revealed by ideal observer analysis
    Knill, DC
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 1997, 38 (04) : 8 - 8
  • [9] Does the human visual system implement an ideal observer theory of slant from texture?
    Buckley, D
    Frisby, JP
    Blake, A
    VISION RESEARCH, 1996, 36 (08) : 1163 - 1176
  • [10] Toward a Universal Model for Shape from Texture
    Verbin, Dor
    Zickler, Todd
    2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2020, : 419 - 427
12345