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In this paper we propose an edge-based segmentation algorithm built on a new type of active contour which is fast, has a low computational complexity and does not introduce unwanted smoothing on the retrieved contours. The contours are always returned as closed chains of points, resulting in a very useful base for subsequent shape representation techniques.

In the attempt to mitigate the effects of COVID-19 lockdown, most countries have recently authorized and promoted the adoption of e-learning and remote teaching technologies, often with the support of teleconferencing platforms. Unfortunately, not all students can benefit from the adoption of such a surrogate of their usual school. We were asked to devise a way to allow a community of children affected by the Rett genetic syndrome, and thus unable to communicate verbally, in writing or by gestures, to actively participate in remote rehabilitation and special education sessions by exploiting eye-gaze tracking. As not all subjects can access commercial eye-tracking devices, we investigated new ways to facilitate the access to eye gaze-based interaction for this specific case. The adopted communication platform is a videoconferencing software, so all we had at our disposal was a live video stream of the child. As a solution to the problem, we developed a software (named SWYG) that only runs at the “operator” side of the communication, at the side of the videoconferencing software, and does not require to install other software in the child’s computer. The preliminary results obtained are very promising and the software is ready to be deployed on a larger base. While this paper is being written, several children are finally able to communicate with their caregivers from home, without relying on expensive and cumbersome devices.