Event Location: NSH 1507
Bio: Yaser Yacoob is a Research Faculty at the Computer Vision laboratory at
the University of Maryland, College Park. His research is on image and
video analysis with focus on topics that are relevant to interpretation
of human appearance and motion.

Abstract: The rapid increase in megapixel resolution of digital images provides a
novel opportunity to capture and analyze information about scene
surfaces and expand beyond the commonly used edge/color/texture
attributes. The talk will address segmentation of an image into patches
that have common underlying salient surface-roughness. Three intrinsic
images are derived: reflectance, shading and meta-texture images. A
constructive approach is proposed for computing a meta-texture image by
preserving, equalizing and enhancing the underlying surface-roughness
across color, brightness and illumination variations. We evaluate the
performance on sample images and illustrate quantitatively that
different patches of the same material, in an image, are normalized in
their statistics despite variations in color, brightness and
illumination. Image segmentation by line-based boundary-detection is
proposed and results are provided and compared to known algorithms.