In this paper we present a new approach for automatically segmentation and tracking of faces in color images. Segmentation of faces is performed by evaluating color and shape information. First, skin-like regions are determined based on the color attributes hue and saturation. Then regions with elliptical shape are selected as face hypotheses. They are veriied by searching for facial features i...

Active contour models based on local region fitting energy can segment images with intensity inhomogeneity effectively, but their segmentation results are easy to error if the initial contour is inappropriate. In this paper, we present a simple and universal method of improving the robustness of initial contour for these local fitting-based models. The core idea of proposed method is exchanging...

This paper examines the influence of head orientation in liptracking. There are two main conclusions: First, lip gesture analysis and head movement correction should be processed independently. Second, the measurement of articulatory parameters may be corrupted by head movement if it is performed directly at the pixel level. We thus propose an innovative technique of liptracking which relies on...

This paper presents the application of active contour models (Snakes) for the segmentation of oral lesions in medical color images acquired from the visual part of the light spectrum. The aim is to assist the clinical expert in locating potentially cancerous cases for further analysis (e.g. classification of cancerous vs. non-cancerous lesions). In order to apply the conventional snake formulat...

We propose a novel active contour model by incorporating particle based electrostatic interactions into the geometric active contour framework. The proposed active contour, embedded in level sets, propagates under the joint influence of a boundary attraction force and a boundary competition force. Unlike other contour models, the proposed vector field dynamically adapts by updating itself when ...

To extract object regions from images, the methods using region-based active contour model (ACM) have been proposed. By controlling ACM with the statistical characteristics of the image properties, these methods effect robust region extraction. However, the existing methods require redundant processing and cannot adapt to complex scene images. To overcome these problems, we propose a new method...

Conventional approaches to perceptual grouping assume little specific knowledge about the object(s) of interest. However, there are many applications in which such knowledge is available and useful. Here, we address the problem of finding the bounding contour of an object in an image when some prior knowledge about the object is available. We introduce a framework for combining prior probabilis...

A highly successful active contour implementation, for the automatic segmentation of cervical cell nuclei, is shown to lend itself well to a framework that further increases its success rate. The method is based upon measuring changes in the final contour as the one parameter that governs its behaviour is varied. Only one object of interest is contained in the image, but as artefacts often appe...

In this paper, we propose two important improvements of an existing approach for automatically segmenting the walls of retinal arteries of healthy/pathological subjects in adaptive optics images. We illustrate the limits of the previous approach and propose to (i) modify the pre-segmentation step, and (ii) embed additional information through coupling energy terms in the parallel active contour...