E. Turetken, F. Benmansour, B. Andres, H. Pfister, P. Fua (2013), Reconstructing Loopy Tubular Structures Using Integer Programming, in Conference on Computer Vision and Pattern Recognition
, Portland, OR, USA.
E. Turetken F. Benmansour and P. Fua (2012), Automated Reconstruction of Tree Structures using Path Classifiers and Mixed Integer Programming, in onference on Computer Vision and Pattern Recognition
, Providence, RI, USA.
E. Turetken G. Gonzalez C. Blum and P. Fua (2011), Automated Reconstruction of Dendritic and Axonal Trees by Global Optimization With Geomet, in Neuroinformatics
, 9(2-3), 279-302.
Tree-like structures appear at many different scales and in many different contexts. They can be micrometer scale dendrites in light microscopy image-stacks, centimeter-scale blood vessels in retinal scans, or meter-scale road networks in aerial images. Extracting them automatically and robustly is therefore of fundamental relevance to many scientific disciplines. However, even though the topic has received sustained attention ever since the inception of the field of Computer Vision, both robustness and automation remain elusive. Fully automated techniques exist but require very clean data; substantial amounts of manual intervention is required for any other kind.In this project, we will therefore develop a fully automated approach to addressing these shortcomings. We will first develop an approach to finding optimal trees that accounts both for global image and geometric properties. We will then implement a practical algorithm to build near-optimal ones in an acceptably short time, even though the underlying problem is closely related to one known to be NP-Hard.