Faculty: Linda G. Shapiro and Robert M. Haralick
Current Students: Mauro Costa, Bharath Modayur, Kari Pulli, and
Adnan Mustafa
The goal of this project is to develop an
automated vision system for inspection and robot guidance that bridges
the gap from CAD models to machine vision algorithms. The PREMIO
system converts a CAD model to a model that is appropriate for machine
vision, uses the vision model to predict features that will appear in
images under various lighting and other environmental conditions, and
uses the predictions to guide a matching procedure that finds
correspondences between image features and model features for
estimation of position and orientation. The ICE system
determines the best positions for sensor and light source for a
given inspection task.
The Automated Inspection System allows the user to
select an object and its features to be inspected and
an inspection task. It then performs
the specified dimensional inspection on a given image of the selected
object.
The Shape from Color Photometric Stereo System determines
3D shape of objects in a scene from two color images of the scene
taken from the same viewpoint with two different lightings. The system
is being used as part of a color object recognition procedure .
The Parallel Object Recognition System matches point or
line-segment models of 2D and 3D objects to features extracted
from images, using a new matching procedure implemented as
a parallel algorithm on both SIMD and MIMD machines as well
as on UNIX workstations.
A new system for active analysis of multi-object scenes
is under development.
The system uses a single, movable camera and
several light sources. It generates hypotheses about the scene
from several images taken from a single viewpoint with different light
sources. The hypotheses will then be used to determine an action such
as moving the camera or light sources and taking more images with
which to verify or disprove the hypotheses. After several iterations
of image acquisition, image processing, analysis, actions, the system
will produce an explanation of the scene in terms of the models that
g, analysis, actions, the system
will produce an explanation of the scene in terms of the models that
it finds present and their positions in the scene.