We address the problem of segmenting multiple similar objects by optimizing a Chan-Vese-like [1] functional with respect to a mixture of level set functions. We solve the variatio...
In this paper we present a general framework for object detection and segmentation. Using a bottom-up unsupervised merging algorithm, a region-based hierarchy that represents the ...
We present a method for the simultaneous detection and segmentation of objects from static images. We employ lowlevel contour features that enable us to learn the coarse object sh...
In the application of curve evolution and level set methods to biomedical image analysis, the incorporation of geometric priors for isolated shapes has been proved useful. On the ...
Drawing a box around an intended segmentation target has become both a popular user interface and a common output for learning-driven detection algorithms. Despite the ubiquity of...