Segmenting images with occluded and missing intensity information is still a difficult task. Intensity based segmentation approaches often lead to wrong results. High vision prior information such as prior shape has been proven to be effective in solving this problem. Most existing shape prior approaches assume known prior shape and segmentation results rely on the selection of prior shape. In this paper, we study how to do simultaneous automatic prior shape selection and segmentation in a variational scheme
Graph cut image segmentation with intensity information alone is prone to fail for objects with weak...
International audienceActive contours are adapted to image segmentation by energy minimization. The ...
We propose a new algorithm for simultaneous localization and figure-ground segmentation where couple...
The problem of image segmentation is known to become particularly challenging in the case of partial...
This book proposes a new approach to handle the problem of limited training data. Common approaches ...
In many image segmentation problems involving limited and low-quality data, employing statistical pr...
International audienceThis work proposes an image segmentation model based on active contours. For a...
Color and texture have been widely used in image segmentation; however, their performance is often h...
Abstract. This paper exposes a novel formulation of prior shape con-straint incorporation for the le...
SUMMARY We proposed a new level set segmentation model with statistical shape prior using a variatio...
Abstract. We propose a novel variational approach based on a level set formulation of the Mumford-Sh...
In this thesis we propose a stable method for image segmentation with shape priors. The original Cha...
In recent years, graph cut has been regarded as an effective discrete optimization method and receiv...
In this paper we propose a novel prior-based variational object segmentation method in a global mini...
International audienceIn this paper, we propose two solutions to integrate shape prior in a segmenta...
Graph cut image segmentation with intensity information alone is prone to fail for objects with weak...
International audienceActive contours are adapted to image segmentation by energy minimization. The ...
We propose a new algorithm for simultaneous localization and figure-ground segmentation where couple...
The problem of image segmentation is known to become particularly challenging in the case of partial...
This book proposes a new approach to handle the problem of limited training data. Common approaches ...
In many image segmentation problems involving limited and low-quality data, employing statistical pr...
International audienceThis work proposes an image segmentation model based on active contours. For a...
Color and texture have been widely used in image segmentation; however, their performance is often h...
Abstract. This paper exposes a novel formulation of prior shape con-straint incorporation for the le...
SUMMARY We proposed a new level set segmentation model with statistical shape prior using a variatio...
Abstract. We propose a novel variational approach based on a level set formulation of the Mumford-Sh...
In this thesis we propose a stable method for image segmentation with shape priors. The original Cha...
In recent years, graph cut has been regarded as an effective discrete optimization method and receiv...
In this paper we propose a novel prior-based variational object segmentation method in a global mini...
International audienceIn this paper, we propose two solutions to integrate shape prior in a segmenta...
Graph cut image segmentation with intensity information alone is prone to fail for objects with weak...
International audienceActive contours are adapted to image segmentation by energy minimization. The ...
We propose a new algorithm for simultaneous localization and figure-ground segmentation where couple...