The UCSB Bio-Segmentation Benchmark dataset consists of 2D/3D images and time-lapse sequences that can be used for evaluating the performance of novel state of the art computer vision algorithms. Tasks include segmentation, classification and tracking. For each class of problem, at least one ground truth dataset is available. We also provide performance metrics for comparing the results of the algorithms with the ground truth. Additional ground truth data will be posted as they become available.
We have started beta-testing for a first set of web applications. These applications do not require local install and use the CPU time of our servers. The web application incapsulates the entire analysis module workflow with specifically designed user interface. Currently we provide 
The Center for Bio-Image Informatics faculty have been awarded a new 5 year NSF project that would explore new, fundamental problems in uncertainty analysis while working with image data. The principal investigators on the project include Professors Hollerer, Manjunath, Rose and Singh on the Engineering side and Professors Feinstein, Fisher and Wilson from the biology division.
