Maria Antonietta Pascali

Thesaurus project: design of new autonomous underwater vehicles for documentation and protection of underwater archaeological sites

The Thesaurus Project, funded by the Regione Toscana, combines humanistic and technological research aiming at developing a new generation of cooperating Autonomous Underwater Vehicles and at documenting ancient and modern Tuscany shipwrecks. Technological research will allow performing an archaeological exploration mission through the use of a swarm of autonomous, smart and self-organizing underwater vehicles. Using acoustic communications, these vehicles will be able to exchange each other data related to the state of the exploration and then to adapt their behavior to improve the survey. The archival research and archaeological survey aim at collecting all reports related to the underwater evidences and the events of sinking occurred in the sea of Tuscany. The collected data will be organized in a specific database suitably modeled.

Face morphology

This paper proposes a method for an automatic extraction of geometric features, related to weight parameters, from 3D facial data acquired with low-cost depth scanners. The novelty of the method relies both on the processing of the 3D facial data and on the definition of the geometric features which are conceptually simple, robust against noise and pose estimation errors, computationally efficient, invariant with respect to rotation, translation, and scale changes. Experimental results show that these measurements are highly correlated with weight, BMI, and neck circumference, and well correlated with waist and hip circumference, which are markers of central obesity. Therefore the proposed method strongly supports the development of interactive, non obtrusive systems able to provide a support for the detection of weight-related problems.

Underwater Scene Understanding by Optical and Acoustic Data Integration

A new method is proposed to integrate 3D optical and acoustic images relative to the same underwater environment. The combination of optical and acoustic sensors in terms of uniform reference system, geo-referencing and time allows: (i) integration cascade (operational level), (ii) safety data acquisition in various domains (distance from ground, turbid water, vegetation, etc.), (iii) replanning of missions in progress. Furthermore, data fusion can be faced according to different approaches: (a) stratification of referenced data layers, (b) correlation of quantities of different nature, (c) comparison of extracted features: 2D geometries (segments, elementary curves) and 3D (planes, simple surfaces), repetitive patterns, (d) integration of semantic information, (e) template matching for recognizing known structures, (f) creation and refinement of probability maps as a measure of optical (geometry, texture) and acoustic (elevation or reflectivity maps) properties. A set of geometrical and textural feature ...

Mirror Mirror on the Wall... An Unobtrusive Intelligent Multisensory Mirror for Well-Being Status Self-Assessment and Visualization

A persons well-being status is reflected by their face through a combination of facial expressions and physical signs. The SEMEOTICONS project translates the semeiotic code of the human face into measurements and computational descriptors that are automatically extracted from images, videos, and three-dimensional scans of the face. SEMEOTICONS developed a multisensory platform in the form of a smart mirror to identify signs related to cardio-metabolic risk. The aim was to enable users to self-monitor their well-being status over time and guide them to improve their lifestyle. Significant scientific and technological challenges have been addressed to build the multisensory mirror, from touchless data acquisition, to real-time processing and integration of multimodal data.

Wize Mirror - a smart, multisensory cardio-metabolic risk monitoring system

A multi-sensor device for health self-monitoring and assessment is proposed.A real-time head pose estimation and tracking method is introduced.An inexpensive 3D scanner facilitating facial morphology analysis is described.Face 3D shape analysis facilitates tracking changes in weight and BMI index.The evaluation of stress and anxiety seems possible using dynamic facial features. In the recent years personal health monitoring systems have been gaining popularity, both as a result of the pull from the general population, keen to improve well-being and early detection of possibly serious health conditions and the push from the industry eager to translate the current significant progress in computer vision and machine learning into commercial products. One of such systems is the Wize Mirror, built as a result of the FP7 funded SEMEOTICONS (SEMEiotic Oriented Technology for Individuals CardiOmetabolic risk self-assessmeNt and Self-monitoring) project. The project aims to translate the semeiotic code of the human face into computational descriptors and measures, automatically extracted from videos, multispectral images, and 3D scans of the face. The multisensory platform, being developed as the result of that project, in the form of a smart mirror, looks for signs related to cardio-metabolic risks. The goal is to enable users to self-monitor their well-being status over time and improve their life-style via tailored user guidance. This paper is focused on the description of the part of that system, utilising computer vision and machine learning techniques to perform 3D morphological analysis of the face and recognition of psycho-somatic status both linked with cardio-metabolic risks. The paper describes the concepts, methods and the developed implementations as well as reports on the results obtained on both real and synthetic datasets.

Morphological analysis of 3D faces for weight gain assessment

In this paper we analyse patterns in face shape variation due to weight gain. We propose the use of persistent homology descriptors to get geometric and topological information about the configuration of anthropometric 3D face landmarks. In this way, evaluating face changes boils down to comparing the descriptors computed on 3D face scans taken at different times. By applying dimensionality reduction techniques to the dissimilarity matrix of descriptors, we get a shape space in which each face is a point and face shape variations are encoded as trajectories in that space. Our first results show that persistent homology is able to identify features which are well-related to overweight, and may help assessing individual weight trends. The research is carried out in the context of the European project SEMEOTICONS, which is developing a multisensory platform which detects and monitors over time facial signs of cardio-metabolic risk.

Towards a Robust System Helping Underwater Archaeologists Through the Acquisition of Geo-referenced Optical and Acoustic Data

In the framework of the ARROWS project September 2012 - August 2015, a venture funded by the European Commission, several modular Autonomous Underwater Vehicles AUV have been developed to the main purposes of mapping, diagnosing, cleaning, and securing underwater and coastal archaeological sites. These AUVs consist of modular mobile robots, designed and manufactured according to specific suggestions formulated by a pool of archaeologists featuring long-standing experience in the field of Underwater Cultural Heritage preservation. The vehicles are typically equipped with acoustic modems to communicate during the dive and with different payload devices to sense the environment. The selected sensors represent appealing choices to the oceanographic engineer since they provide complementary information about the surrounding environment. The maini¾?topics discussed in this paper concern i performing a systematic mapping of the marine seafloors, ii processing the output maps to detect and classify potential archaeological targets and finally iii developing dissemination systems with the purpose of creating virtual scenes as a photorealistic and informative representation of the surveyed underwater sites.

Computer Vision for Ambient Assisted Living

Abstract The Ambient Assisted Living (AAL) paradigm proposes advanced technologies and services to improve the quality of life, health, and wellbeing of citizens by making their daily-life activities easier and more secure, by monitoring patients under specific treatment, and by addressing at-risk subjects with proper counseling. The challenges brought by AAL range from robust, accurate, and nonintrusive data acquisition in daily-life settings to the development of services that are easy to use and appealing to the users and that support long-term engagement. This chapter offers a brief survey of existing vision-based monitoring solutions for personalized healthcare and wellness, and introduces the Wize Mirror, a multisensory platform featuring advanced algorithms for cardiometabolic risk prevention and quality-of-life improvement.

Long-Term Monitoring of Crack Patterns in Historic Structures Using UAVs and Planar Markers: A Preliminary Study

This paper describes how Unmanned Aerial Vehicles (UAVs) may support the long-term monitoring of crack patterns in the context of architectural heritage preservation. In detail, this work includes: (i) a state of the art about the most used techniques in ancient structural monitoring; (ii) the description of the implemented methods, taking into account the requirements and constraints of the case study; (iii) the results of the experimentation carried out in the lab; and (iv) conclusions and future works.

Towards Structural Monitoring and 3D Documentation of Architectural Heritage Using UAV

This paper describes how Unmanned Aerial Vehicles (UAVs) may support the architectural heritage preservation and dissemination. In detail, this work deals with the long-term monitoring of the crack pattern of historic structures, and with the reconstruction of interactive 3D scene in order to provide both the scholar and the general public with a simple and engaging tool to analyze or visit the historic structure.