In this paper we describe a new technique for general purpose interactive segmentation of N-dimensional images. The user marks certain pixels as “object” or “background” to provide hard constraints for segmentation. Additional soft constraints incorporate both boundary and region information. Graph

This paper addresses the problem of segmenting an image into regions. We define a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image. We then develop an efficient segmentation algorithm based on this predicate, and show

This paper describes a segment (e.g. phoneme) boundary estimation method based on recurrent neural networks (RNNs). The proposed method only requires acoustic observations to accurately estimate segment boundaries. Experimental results show that the proposed method can estimate segment boundaries

We present a novel statistical and variational approach to image segmentation based on a new algorithm named region competition. This algorithm is derived by minimizing a generalized Bayes/MDL criterion using the variational principle. The algorithm is guaranteed to converge to a local minimum

We propose a new multiphase level set framework for image segmentation using the Mumford and Shah model, for piecewise constant and piecewise smooth optimal approximations. The proposed method is also a generalization of an active contour model without edges based 2-phase segmentation, developed

exist to measure an algorithm’s accuracy against these rich structural annotations. In this work, we propose a method to evaluate structural boundary detec-tion with hierarchical annotations. The proposed method transforms boundary detection into a ranking problem, and facilitates the comparison of both

that corresponds well to human judgments of the subtopic boundaries of 12 texts. Multi-paragraph subtopic segmentation should be useful for many text analysis tasks, including information retrieval and summarization. 1.

Abstract. This study analyses how the reduction of the look-ahead length of a two pass phonetic decoder influences the alignment of the segment boundaries. It is shown how the optimization of some tuning parameters, such as the insertion penalty, is dependent on the look-ahead length. It is also

Abstract. The segment boundaries produced by the Synface low latency phoneme recogniser are analysed. The precision in placing the boundaries is an important factor in the Synface system as the aim is to drive the lip movements of a synthetic face for lip-reading support. The recogniser is based

segmentation allows to connect classical “snakes ” based on energy minimization and geometric active contours based on the theory of curve evolution. Previous models of geometric active contours are improved, allowing stable boundary detection when their gradients suffer from large variations, including gaps