We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
: This paper introduces the notion of primary image segmentation which serves as a well defined link between low- and high-level image analysis. A general algorithmic framework bas...
Five image segmentation algorithms are evaluated: mean shift, normalised cuts, efficient graph-based segmentation, hierarchical watershed, and waterfall. The evaluation is done us...
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Brain MR image segmentation is an important research topic in medical image analysis area. In this paper, we propose an active contour model for brain MR image segmentation, based ...