March 14, Wednesday 14:15, Room 303, Jacobs Building
Title: Pose Estimation and Recognition using Specular Highlights
Lecturer:
Margarita Osadchy
Lecturer homepage
: http://rita.osadchy.net/
Affiliation : University of Haifa
We presents a novel approach to pose estimation and model-based recognition of
specular objects in difficult viewing conditions, such as low illumination,
cluttered background, and large highlights and shadows that appear on the
object of interest. In such challenging conditions conventional features are
unreliable. We show that under the assumption of a dominant light source,
specular highlights produced by a known object can be used to establish
correspondence between its image and the 3D model, and to verify the
hypothesized pose and the identity of the object.
Previous methods that use highlights for recognition make limiting assumptions
such as known pose, scene-dependent calibration, simple shape, etc. The
proposed method can efficiently recognize free form specular objects in
arbitrary pose and under unknown lighting direction. It uses only a single
image of the object as its input and outputs object identity, full pose, and
the lighting direction in the scene.
This is a joint work with Aaron Netz