Facial Image Analysis using Directional Statistics and Shape-from Shading
published: Sept. 20, 2010, recorded: September 2010, views: 3783
Slides
Related content
Report a problem or upload files
If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Description
Although the recovery of facial shape using shape-from-shading is an appealing idea, it is frustrated by problems such as concave-convex ambiguities, variable albedo, self shadowing and non-Lambertian reflectance. As such the devil resides in the detail. In this talk I will show how these problems can be overcome by incorporating a statistical model for surface normal direction within the shape-from-shading process. The main contribution of the talk is to develop a representation of the distribution of surface normals using the equidistant azimuthal projection from cartography, which transforms a distribution of surface normal direction on a unit sphere to a distribution of points on a tangent plane. I will show how this model can be adapted to deal with shadowing by fitting the statistical model to image brightness data using robust statistics. I will also show to to adapt the process to deal with non-Lambertian reflectance, through fitting a reflectance model that can capture the behavour of both shiny and rough surfaces. Finally, I will show how the shape information delivered by the process can be used to perform face recognition and gender determination. This talk will provide a synopsis of recent work by Smith and Hancock (PAMI 07, IJCV09, IJCV 2010) and Wu, Smith and Hancock (IVC 2010)
Link this page
Would you like to put a link to this lecture on your homepage?Go ahead! Copy the HTML snippet !
Write your own review or comment: