The  Weizmann  Institute  of  Science
                 Faculty of Mathematics and Computer Science


                         Vision and Robotics Seminar

                                Michael Black
                               Brown University


                                will speak on


      Recovering detailed 3D models of human shape and pose from images

Abstract:
Algorithms for video-based human motion capture typically assume the body shape
is known a priori and is represented coarsely (e.g. using cylinders to model
body parts). These body models stand in sharp contrast to the richly detailed
3D body models used by by animators.  In this talk we describe a method for
recovering detailed body shape models directly from images. Specifically, we
represent the body using a recently proposed triangulated mesh model called
SCAPE which employs a low-dimensional, but realistic, parametric model of human
shape and pose-dependent deformations. Shape variations of the human body were
learned from a database of 2400 ranges scans of people. We show how the
parameters of the SCAPE model can be estimated directly from image data. In
particular, the talk will look at the image cues available from strong lighting
including cast shadows and shading.  Rather than causing problems, we found
that strong lighting improves 3D human pose and shape estimation making it
practical even in monocular images.

Joint work with Alexandru Balan (Brown), Horst Haussecker (Intel) and James
Davis (UCSC).




                     The lecture will take place in the
                    Lecture Hall, Room 1, Ziskind Building
                         on Thursday, January 3, 2008
                                12:00 - 13:00