Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Centroid for the Paraboloid of Revolution

Centroid for the Paraboloid of Revolution

The paraboloid of revolution is an axially symmetric surface generated by rotating a parabola around its axis. This shape has several applications in mechanical engineering due to its advantageous structural properties, such as strength against stress concentration points and rotational symmetry.
The centroid for the paraboloid of revolution is the point where all the mass of the paraboloid is concentrated. This centroid is important for engineering applications, as it determines how forces are...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Phase transitions and self-organized criticality in networks of stochastic spiking neurons.

Scientific reports·2016

Same author

Mutual information content of homologous DNA sequences.

Genetics and molecular research : GMR·2005

Same author

The image foresting transform: theory, algorithms, and applications.

IEEE transactions on pattern analysis and machine intelligence·2004

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 1, 2026

Reefshape: A System for the Efficient Collection and Automated Processing of Time-Series Underwater Photogrammetry Data for Benthic Habitat Monitoring

Reefshape: A System for the Efficient Collection and Automated Processing of Time-Series Underwater Photogrammetry Data for Benthic Habitat Monitoring

Published on: June 13, 2025

A uniform grid structure to speed up example-based photometric stereo.

Rafael F V Saracchini¹, Jorge Stolfi, Helena Cristina da Gama Leitao

¹Institute of Computing, State University of Campinas, 13984-971 Campinas, Brazil. ra069320@ic.unicamp.br

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|June 16, 2011

Summary

This summary is machine-generated.

This study introduces a faster, exact algorithm for photometric stereo, accelerating table lookups. It efficiently finds matching pixels using a 2-D grid structure on a manifold, improving multi-image analysis.

More Related Videos

Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales

Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales

Published on: August 21, 2019

Related Experiment Videos

Last Updated: Jun 1, 2026

Reefshape: A System for the Efficient Collection and Automated Processing of Time-Series Underwater Photogrammetry Data for Benthic Habitat Monitoring

Reefshape: A System for the Efficient Collection and Automated Processing of Time-Series Underwater Photogrammetry Data for Benthic Habitat Monitoring

Published on: June 13, 2025

Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales

Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales

Published on: August 21, 2019

Area of Science:

Computer Vision
Computer Graphics
Image Processing

Background:

Photometric stereo reconstructs 3D shape from images under varying illumination.
Example-based photometric stereo relies on efficient table lookup for matching pixels.
Existing methods face speed or accuracy limitations, especially without point-like light sources.

Purpose of the Study:

To develop a novel data structure and algorithm for accelerating the table lookup in example-based multi-image photometric stereo.
To provide an exact solution that guarantees finding the best matching entry.
To overcome limitations of previous methods, including the assumption of point-like light sources.

Main Methods:

A new data structure and algorithm are proposed to speed up the table lookup process.
The method leverages the 2-D manifold structure of the data in m-dimensional space.
A uniform 2-D grid structure is employed for efficient searching.

Main Results:

The proposed method significantly accelerates the table lookup step compared to prior solutions.
The algorithm provides an exact solution, ensuring the optimal match is always found.
The method is effective without requiring point-like illumination sources.

Conclusions:

The developed data structure and algorithm offer a more efficient and exact approach to photometric stereo.
This advancement improves the analysis of multi-image data in computer vision and graphics.
The technique provides a robust solution applicable to various illumination conditions.