VASC Seminar
Image Segmentation Using Meta-Texture Saliency
Yaser Yacoob
University of Maryland
3:30pm, Monday, April 14
NSH 1507
Appointments: Peggy Martin
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.
Biography:
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.
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