Current Position: I work at Riya Inc. in San Mateo, CA
Resume (somewhat outdated): Download the PDF of my resume
Ph.D. Thesis (September 2004): Abstract
Variational Image Segmentation and Curve Evolution on Natural Images.
Travel and Vacation
Are you making travel plans. Istanbul, Turkey is a good choice.
I suggest staying at Ada Hotel Istanbul (Sultanahmet area) for a smooth experience.
Image
segmentation software that uses Edgeflow-based Anisotropic diffusion (C++)
Both windows binary and source code are available. Based on the ideas presented on this
Technical Report and some more recent stuff.
Matlab toolbox for Level Set
Methods (Matlab)
This set of Matlab files implements Level Set Methods and follows
Osher and
Fedkiw's book. A combination of curvature-based forces, vector field-based
forces and forces in the normal direction can be used.
CIMPL Matrix Performance Library (C++)
Robust and simple (to use and understand) multi-dimensional C++ library for
Matrices and Vectors. Linear algebra operations are supported mainly through
BLAS and LAPACK. Useful for
researchers in image processing and many other fields.
Graph Partitioning Active Contours (GPAC) for Image Segmentation
In this paper we introduce new variational segmentation cost functions that are
based on pair wise similarities or dissimilarities of the pixels...
Edgeflow-driven Variational Image Segmentation: Theory and Performance
Evaluation
We introduce robust variational segmentation techniques that are driven by an Edgeflow vector field...
»
Berkeley Segmentation Data Set
Includes a set of natural images with manual ground truth segmentations
associated with them. The package include many useful Matlab source code.
» Segmentation Research at UC Berkeley
» Segmentation Research of Dr. Song-Chun Zhu at UCLA
» Netlab Library for Pattern
Recognition (for Matlab)
Useful and complete toolbox. An accompanying book can also be bought.
In this project, we propose a new class of variational segmentation cost functions. Our cost functions are based on pair-wise dissimilarities between individual pixels and have been successfully applied to natural images by graph partitioning techniques. These cost functions are minimized within a variational framework. We refer to our work as graph partitioning active contours (GPAC).
Starting with the Edgeflow technique, which has been shown to be highly successful on natural images, a curve evolution method is proposed. To verify the effectiveness of this technique, extensive tests are conducted on the Berkeley segmentation data set and associated ground truth. Our method is compared to Geodesic Active Contours and Gradient Vector Flow (GVF) The results show that our methods outperform the current state of the art.
Starting with the Edgeflow technique, which has been shown to be highly successful on natural images, an anisotropic diffusion method is proposed. Our method is compared to Perona and Malik's anisotropic diffusion and Self Snakes by conducting extensive tests on the Berkeley segmentation data set and associated ground truth. The results show that our methods significantly outperform the current state of the art.
In this project, we introduce new multi-scale techniques for edge detection and image segmentation. The idea is to favor edges that exist across multiple scales and localize them at the smallest scale they exist.
This project introduces a simple method for automatically collecting and categorizing images from the world wide web. Using the category structure, a search and retrieval strategy is proposed for a large database of images (around a million)
Most large image databases can be divided into categories implicitly or explicitly. If this categorization is achieved by using automated techniques it is possible that there are a number of outliers in these categories. Our purpose in this project is to prune these categories using image segmentation techniques so that the precision of the category is improved with little effect to recall.
© 2004 Baris Sumengen
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