A New Computer-aided Technique for Planning the Aesthetic Outcome of Plastic Surgery

Plastic surgery plays a major role in today health care. Planning plastic face surgery requires dealing with the elusive concept of attractiveness for evaluating feasible beautification of a particular face. The existing computer tools essentially allow to manually warp 2D images or 3D face scans, in order to produce images simulating possible surgery outcomes. How to manipulate faces, as well as the evaluation of the results, are left to the surgeon's judgement. We propose a new quantitative approach able to automatically suggest effective patient-specific improvements of facial attractiveness. The general idea is to compare the face of the patient with a large database of attractive faces, excluding the facial feature to be improved. Then, the feature of the faces more similar is applied, with a suitable morphing, to the face of the patient. In this paper we present a first application of the general idea in the field of nose surgery. Aesthetically effective rhinoplasty is suggested on the base of the entire face profile, a very important 2D feature for rating face attractivenes

Computer analysis of face beauty: a survey

The human face conveys to other human beings, and potentially to computer systems, information such as identity, intentions, emotional and health states, attractiveness, age, gender and ethnicity. In most cases analyzing this information involves the computer science as well as the human and medical sciences. The most studied multidisciplinary problems are analyzing emotions, estimating age and modeling aging effects. An emerging area is the analysis of human attractiveness. The purpose of this paper is to survey recent research on the computer analysis of human beauty. First we present results in human sciences and medicine pointing to a largely shared and data-driven perception of attractiveness, which is a rationale of computer beauty analysis. After discussing practical application areas, we survey current studies on the automatic analysis of facial attractiveness aimed at: i) relating attractiveness to particular facial features; ii) assessing attractiveness automatically; iii) improving the attractiveness of 2D or 3D face images. Finally we discuss open problems and possible lines of research

A New 3D Tool for Planning Plastic Surgery

Face plastic surgery (PS) plays a major role in today medicine. Both for reconstructive and cosmetic surgery, achieving harmony of facial features is an important, if not the major goal. Several systems have been proposed for presenting to patient and surgeon possible outcomes of the surgical procedure. In this paper, we present a new 3D system able to automatically suggest, for selected facial features as nose, chin, etc, shapes that aesthetically match the patient's face. The basic idea is suggesting shape changes aimed to approach similar but more harmonious faces. To this goal, our system compares the 3D scan of the patient with a database of scans of harmonious faces, excluding the feature to be corrected. Then, the corresponding features of the k most similar harmonious faces, as well as their average, are suitably pasted onto the patient's face, producing k+1 aesthetically effective surgery simulations. The system has been fully implemented and tested. To demonstrate the system, a 3D database of harmonious faces has been collected and a number of PS treatments have been simulated. The ratings of the outcomes of the simulations, provided by panels of human judges, show that the system and the underlying idea are effectiv

Recognizing human motion using eigensequences

This paper presents a novel method for motion recognition. The approach is based on 3D motion data. The captured motion is divided into sequences, which are sets of contiguous postures over time. Each sequence is then classified into one of the recognizable action classes by means of a PCA based method. The proposed approach is able to perform automatic recognition of movements containing more than one class of action. The advantages of this technique are that it can be easily extended to recognize many action classes and, most of all, that the recognition process is real-time. In order to fully understand the capabilities of the proposed method, the approach has been implemented and tested in a virtual environment. Several experimental results are also provided and discussed

A Nearly Optimal Algorithm for covering the interior of an Art Gallery

The problem of locating visual sensors can be often modeled as 2D Art Gallery problems. In particular, tasks such as surveillance require observing the interior of a polygonal environment (interior covering, IC), while for inspection or image based rendering observing the boundary (edge covering, EC) is sufficient. Both problems are NP-hard, and no technique is known for transforming one problem into the other. Recently, an incremental algorithm for EC has been proposed, and its near-optimality has been demonstrated experimentally. In this paper we show that, with some modification, the algorithm is nearly optimal also for IC. The algorithm has been implemented and tested over several hundreds of random polygons with and without holes. The cardinality of the solutions provided is very near to, or coincident with, a polygon-specific lower bound, and then suboptimal or optimal. In addition, our algorithm has been compared, for all the test polygons, with recent heuristic sensor location algorithms. In all cases, the cardinality of the set of guards provided by our algorithm was less than or equal to that of the set computed by the other algorithms. An enhanced version of the algorithm, also taking into account range and incidence constraints, has also been implemente