Video normals from colored lights

Gabe Brostow, Carlos Hernández, George Vogiatzis, Björn Stenger, Roberto Cipolla

Research output: Contribution to journalArticlepeer-review


We present an algorithm and the associated single-view capture methodology to acquire the detailed 3D shape, bends, and wrinkles of deforming surfaces. Moving 3D data has been difficult to obtain by methods that rely on known surface features, structured light, or silhouettes. Multispectral photometric stereo is an attractive alternative because it can recover a dense normal field from an untextured surface. We show how to capture such data, which in turn allows us to demonstrate the strengths and limitations of our simple frame-to-frame registration over time. Experiments were performed on monocular video sequences of untextured cloth and faces with and without white makeup. Subjects were filmed under spatially separated red, green, and blue lights. Our first finding is that the color photometric stereo setup is able to produce smoothly varying per-frame reconstructions with high detail. Second, when these 3D reconstructions are augmented with 2D tracking results, one can register both the surfaces and relax the homogenous-color restriction of the single-hue subject. Quantitative and qualitative experiments explore both the practicality and limitations of this simple multispectral capture system.
Original languageEnglish
Pages (from-to)2104-2114
Number of pages11
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number10
Publication statusPublished - Oct 2011

Bibliographical note

© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.


  • photometric stereo
  • multispectral
  • single view
  • video normals


Dive into the research topics of 'Video normals from colored lights'. Together they form a unique fingerprint.

Cite this