We describe an unsupervised method to segment objects detected in images using a novel variant of an interest point template, which is very efficient to train and evaluate. Once a...
Himanshu Arora, Nicolas Loeff, David A. Forsyth, N...
Combinations of multiple classifiers have been found to be consistently more accurate than a single classifier. The construction of multiple independent classifiers, however, is t...
Torsten Rohlfing, Daniel B. Russakoff, Calvin R. M...
Abstract. Image segmentation is essential for many automated microscopy image analysis systems. Rather than treating microscopy images as general natural images and rushing into th...
We present a region-based active contour approach to segmenting masses in digital mammograms. The algorithm developed in a Maximum Likelihood approach is based on the calculation o...
We address the problem of segmenting and recognizing objects in real world images, focusing on challenging articulated categories such as humans and other animals. For this purpos...
Pablo Arbelaez, Bharath Hariharan, Chunhui Gu, Sau...