Radiance interpolants for accelerated bounded-error ray tracing

被引:34
|
作者
Bala, K [1 ]
Dorsey, J [1 ]
Teller, S [1 ]
机构
[1] MIT, Comp Sci Lab, Cambridge, MA 02139 USA
来源
ACM TRANSACTIONS ON GRAPHICS | 1999年 / 18卷 / 03期
关键词
data structures; error bounds; interactive; 4D interpolation; interval arithmetic; radiance approximation; rendering; rendering systems; visibility;
D O I
10.1145/336414.336417
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Ray tracers, which sample radiance, are usually regarded as offline rendering algorithms that are too slow for interactive use. In this article we present a system that exploits object-space, ray-space, image-space, and temporal coherence to accelerate ray tracing. Our system uses per-surface interpolants to approximate radiance while conservatively bounding error. The techniques introduced in this article should enhance both interactive and batch ray tracers. Our approach explicitly decouples the two primary operations of a ray tracer-shading and visibility determination-and accelerates each of them independently. Shading is accelerated by quadrilinearly interpolating lazily acquired radiance samples. Interpolation error does not exceed a user-specified bound, allowing the user to control performance/quality tradeoffs. Error is bounded by adaptive sampling at discontinuities and radiance nonlinearities. Visibility determination at pixels is accelerated by reprojecting interpolants as the user's viewpoint changes. A fast scan-line algorithm then achieves high performance without sacrificing image quality. For a smoothly varying viewpoint, the combination of lazy interpolants and reprojection substantially accelerates the ray tracer. Additionally, an efficient cache management algorithm keeps the memory footprint of the system small with negligible overhead.
引用
收藏
页码:213 / 256
页数:44
相关论文
共 50 条
  • [2] Bounded-Error LQR-Trees
    Ames, Barrett
    Konidaris, George
    2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2019, : 144 - 150
  • [3] PARAMETER SETS FOR BOUNDED-ERROR DATA
    MOORE, R
    MATHEMATICS AND COMPUTERS IN SIMULATION, 1992, 34 (02) : 113 - 119
  • [4] Quantum search on bounded-error inputs
    Hoyer, P
    Mosca, M
    de Wolf, R
    AUTOMATA, LANGUAGES AND PROGRAMMING, PROCEEDINGS, 2003, 2719 : 291 - 299
  • [5] Robust Bounded-Error Subset Selection
    Alghoniemy, Masoud
    2018 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE), 2018,
  • [6] EXPERIMENT DESIGN FOR BOUNDED-ERROR MODELS
    PRONZATO, L
    WALTER, E
    MATHEMATICS AND COMPUTERS IN SIMULATION, 1990, 32 (5-6) : 571 - 584
  • [7] L(2) PROJECTION IN BOUNDED-ERROR ESTIMATION
    KEESMAN, KJ
    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 1995, 9 (01) : 71 - 85
  • [8] Hardware-Accelerated Collision Detection using Bounded-Error Fixed-Point Arithmetic
    Raabe, Andreas
    Hochguertel, Stefan
    Anlauf, Joachim K.
    Zachmann, Gabriel
    JOURNAL OF WSCG, 2006, 2006, 14 (1-3): : 17 - +
  • [9] ON BOUNDED-ERROR IDENTIFICATION OF FEEDBACK-SYSTEMS
    MAKILA, PM
    PARTINGTON, JR
    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 1995, 9 (01) : 47 - 61
  • [10] Adaptive blind equalization with bounded-error specification
    Gollamudi, S
    Huang, YF
    2003 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY - PROCEEDINGS, 2003, : 197 - 197