Michael J. Brooks
Papers
2
Total Citations
657
H-Index
2
About
Michael J. Brooks is a pioneering figure in computer vision, best known for his foundational work on shape from shading—a classic and still largely unresolved problem in machine vision. His 1989 book on the subject, which has amassed over 620 citations, remains a seminal resource for understanding how three-dimensional shape can be inferred from two-dimensional image shading. Brooks’ contributions have shaped the theoretical and practical underpinnings of 3D reconstruction from single images. He has also made significant advances in camera self-calibration, notably through an essentially linear algorithm for recovering unknown focal lengths from stereo image pairs, published in 1996. This work addressed degenerate configurations and provided a more accessible route to calibration from fundamental matrices. Brooks’ research bridges geometry, optics, and computational modeling, influencing both academic inquiry and applied vision systems. His lasting impact is reflected in the continued relevance of his early work, which has guided generations of researchers tackling the enduring challenge of inferring shape from shading.
Research Focus
Key Achievements
Top Papers
- 1Shape from shading620 citations · 1989
- 2