2012
Conference article
Restricted
The Hitchhiker's guide to the galaxy of mathematical tools for shape analysis
S Biasotti, B Falcidieno, D Giorgi, M Spagnuolo
A practical guide for researchers who are exploring the new frontiers of 3D shape analysis and managing the complex mathematical tools that most methods rely on. Many research solutions come from advances in pure and applied mathematics, as well as from re-reading classical mathematical theories. Managing these math tools is critical to understanding and solving current problems in 3D shape analysis. This course is designed to help mathematicians and scientists communicate in a world where boundaries between disciplines are (fortunately) blurred, so they can quickly find the right mathematical tools for a bright intuitive idea and strike a balance between theoretical rigor and computationally feasible solutions. The course presents basic concepts in differential geometry and proceeds to advanced topics in algebraic topology, always keeping an eye on their computational counterparts. It includes examples of applications to shape correspondence, symmetry detection, and shape retrieval that show how these mathematical concepts can be translated into practical solutions.
S Biasotti, B Falcidieno, D Giorgi, M Spagnuolo
A practical guide for researchers who are exploring the new frontiers of 3D shape analysis and managing the complex mathematical tools that most methods rely on. Many research solutions come from advances in pure and applied mathematics, as well as from re-reading classical mathematical theories. Managing these math tools is critical to understanding and solving current problems in 3D shape analysis. This course is designed to help mathematicians and scientists communicate in a world where boundaries between disciplines are (fortunately) blurred, so they can quickly find the right mathematical tools for a bright intuitive idea and strike a balance between theoretical rigor and computationally feasible solutions. The course presents basic concepts in differential geometry and proceeds to advanced topics in algebraic topology, always keeping an eye on their computational counterparts. It includes examples of applications to shape correspondence, symmetry detection, and shape retrieval that show how these mathematical concepts can be translated into practical solutions.
See at:
dl.acm.org 
| CNR IRIS | CNR IRIS
2013
Journal article
Restricted
Information-Theoretic Selection of High-Dimensional Spectral Features for Structural Recognition
Boyan B, Escolano F, Giorgi D, Biasotti S
Pattern recognition methods often deal with samples consisting of thousands of features. Therefore, the reduction of their dimensionality becomes crucial to make the data sets tractable. Feature selection techniques remove the irrelevant and noisy features and select a subset of features which describe better the samples and produce a better classification performance. In this paper, we propose a novel feature selection method for supervised classification within an information-theoretic framework. Mutual information is exploited for measuring the statistical relation between a subset of features and the class labels of the samples. Traditionally it has been measured for ranking single features; however, in most data sets the features are not independent and their combination provides much more information about the class than the sum of their individual prediction power. We analyze the use of different estimation methods which bypass the density estimation and estimate entropy and mutual information directly from the set of samples. These methods allow us to efficiently evaluate multivariate sets of thousands of features. Within this framework we experiment with spectral graph features extracted from 3D shapes. Most of the existing graph classification techniques rely on the graph attributes. We use unattributed graphs to show what is the contribution of each spectral feature to graph classification. Apart from succeeding to classify graphs from shapes relying only on their structure, we test to what extent the set of selected spectral features are robust to perturbations of the dataset.Source: COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 117 (issue 3), pp. 214-228
Boyan B, Escolano F, Giorgi D, Biasotti S
Pattern recognition methods often deal with samples consisting of thousands of features. Therefore, the reduction of their dimensionality becomes crucial to make the data sets tractable. Feature selection techniques remove the irrelevant and noisy features and select a subset of features which describe better the samples and produce a better classification performance. In this paper, we propose a novel feature selection method for supervised classification within an information-theoretic framework. Mutual information is exploited for measuring the statistical relation between a subset of features and the class labels of the samples. Traditionally it has been measured for ranking single features; however, in most data sets the features are not independent and their combination provides much more information about the class than the sum of their individual prediction power. We analyze the use of different estimation methods which bypass the density estimation and estimate entropy and mutual information directly from the set of samples. These methods allow us to efficiently evaluate multivariate sets of thousands of features. Within this framework we experiment with spectral graph features extracted from 3D shapes. Most of the existing graph classification techniques rely on the graph attributes. We use unattributed graphs to show what is the contribution of each spectral feature to graph classification. Apart from succeeding to classify graphs from shapes relying only on their structure, we test to what extent the set of selected spectral features are robust to perturbations of the dataset.Source: COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 117 (issue 3), pp. 214-228
See at:
CNR IRIS | CNR IRIS | www.sciencedirect.com
2014
Book
Restricted
Mathematical tools for shape analysis and description
Biasotti S, Falcidieno B, Giorgi D, Spagnuolo M
This book is a guide for researchers and practitioners to the new frontiers of 3D shape analysis and the complex mathematical tools most methods rely on. The target reader includes students, researchers and professionals with an undergraduate mathematics background, who wish to understand the mathematics behind shape analysis. The authors begin with a quick review of basic concepts in geometry, topology, differential geometry, and proceed to advanced notions of algebraic topology, always keeping an eye on the application of the theory, through examples of shape analysis methods such as 3D segmentation, correspondence, and retrieval. A number of research solutions in the field come from advances in pure and applied mathematics, as well as from the re-reading of classical theories and their adaptation to the discrete setting. In a world where disciplines (fortunately) have blurred boundaries, the authors believe that this guide will help to bridge the distance between theory and practice.Source: SYNTHESIS LECTURES ON COMPUTER GRAPHICS AND ANIMATION
Biasotti S, Falcidieno B, Giorgi D, Spagnuolo M
This book is a guide for researchers and practitioners to the new frontiers of 3D shape analysis and the complex mathematical tools most methods rely on. The target reader includes students, researchers and professionals with an undergraduate mathematics background, who wish to understand the mathematics behind shape analysis. The authors begin with a quick review of basic concepts in geometry, topology, differential geometry, and proceed to advanced notions of algebraic topology, always keeping an eye on the application of the theory, through examples of shape analysis methods such as 3D segmentation, correspondence, and retrieval. A number of research solutions in the field come from advances in pure and applied mathematics, as well as from the re-reading of classical theories and their adaptation to the discrete setting. In a world where disciplines (fortunately) have blurred boundaries, the authors believe that this guide will help to bridge the distance between theory and practice.Source: SYNTHESIS LECTURES ON COMPUTER GRAPHICS AND ANIMATION
See at:
CNR IRIS | CNR IRIS | www.morganclaypool.com
2016
Conference article
Restricted
3D objects exploration: guidelines for future research
Biasotti S, Falcidieno B, Giorgi D, Spagnuolo M
Search engines provide the interface to interact with 3D object repositories, which are rapidly growing in both number and size. This position paper presents the current state of the art on 3D dataset navigation and 3D model retrieval. We discuss a number of challenges we consider as the main points to be tackled for developing effective 3D object exploration systems.
Biasotti S, Falcidieno B, Giorgi D, Spagnuolo M
Search engines provide the interface to interact with 3D object repositories, which are rapidly growing in both number and size. This position paper presents the current state of the art on 3D dataset navigation and 3D model retrieval. We discuss a number of challenges we consider as the main points to be tackled for developing effective 3D object exploration systems.
See at:
diglib.eg.org | CNR IRIS | CNR IRIS
2019
Journal article
Open Access
Towards a topological-geometrical theory of group equivariant non-expansive operators for data analysis and machine learning
Bergomi Mg, Frosini P, Giorgi D, Quercioli N
We provide a general mathematical framework for group and set equivariance in machine learning. We define group equivariant non-expansive operators (GENEOs) as maps between function spaces associated with groups of transformations. We study the topological and metric properties of the space of GENEOs to evaluate their approximating power and set the basis for general strategies to initialize and compose operators. We define suitable pseudo-metrics for the function spaces, the equivariance groups and the set of non-expansive operators. We prove that, under suitable assumptions, the space of GENEOs is compact and convex. These results provide fundamental guarantees in a machine learning perspective. By considering isometry-equivariant non-expansive operators, we describe a simple strategy to select and sample operators. Thereafter, we show how selected and sampled operators can be used both to perform classical metric learning and to inject knowledge in artificial neural networks.Source: NATURE MACHINE INTELLIGENCE, vol. 1 (issue 9), pp. 423-433
Bergomi Mg, Frosini P, Giorgi D, Quercioli N
We provide a general mathematical framework for group and set equivariance in machine learning. We define group equivariant non-expansive operators (GENEOs) as maps between function spaces associated with groups of transformations. We study the topological and metric properties of the space of GENEOs to evaluate their approximating power and set the basis for general strategies to initialize and compose operators. We define suitable pseudo-metrics for the function spaces, the equivariance groups and the set of non-expansive operators. We prove that, under suitable assumptions, the space of GENEOs is compact and convex. These results provide fundamental guarantees in a machine learning perspective. By considering isometry-equivariant non-expansive operators, we describe a simple strategy to select and sample operators. Thereafter, we show how selected and sampled operators can be used both to perform classical metric learning and to inject knowledge in artificial neural networks.Source: NATURE MACHINE INTELLIGENCE, vol. 1 (issue 9), pp. 423-433
See at:
CNR IRIS 
| ISTI Repository | www.nature.com | CNR IRIS | CNR IRIS
2012
Conference article
Open Access
SHREC'12 track: stability on abstract shapes
Biasotti S., Bai X., Bustos B., Cerri A., Giorgi D., Li L., Mortara M., Sipiran I., Zhang S., Spagnuolo M.
This contribution reports the results of the SHREC 2012 track: Stability on Abstract Shapes. This track saw six registrations of which only three participants effectively sent the results of their runs.
Biasotti S., Bai X., Bustos B., Cerri A., Giorgi D., Li L., Mortara M., Sipiran I., Zhang S., Spagnuolo M.
This contribution reports the results of the SHREC 2012 track: Stability on Abstract Shapes. This track saw six registrations of which only three participants effectively sent the results of their runs.
See at:
diglib.eg.org | CNR IRIS | CNR IRIS | CNR IRIS
2016
Journal article
Open Access
Retrieval and classification methods for textured 3D models: a comparative study
Biasotti Sm, Cerri A, Aono M, Hamza Ab, Garro V, Giachetti A, Giorgi D, Godil Aa, Li Gc, Sanada C, Spagnuolo M, Tatsuma A, Velasco Forero S
This paper presents a comparative study of six methods for the retrieval and classification of textured 3D models, which have been selected as representative of the state of the art. To better analyse and control how methods deal with specific classes of geometric and texture deformations, we built a collection of 572 synthetic textured mesh models, in which each class includes multiple texture and geometric modifications of a small set of null models. Results show a challenging, yet lively, scenario and also reveal interesting insights into how to deal with texture information according to different approaches, possibly working in the CIELab as well as in modifications of the RGB colour space.Source: THE VISUAL COMPUTER, vol. 32 (issue 2), pp. 217-241
Project(s): VISIONAIR
Biasotti Sm, Cerri A, Aono M, Hamza Ab, Garro V, Giachetti A, Giorgi D, Godil Aa, Li Gc, Sanada C, Spagnuolo M, Tatsuma A, Velasco Forero S
This paper presents a comparative study of six methods for the retrieval and classification of textured 3D models, which have been selected as representative of the state of the art. To better analyse and control how methods deal with specific classes of geometric and texture deformations, we built a collection of 572 synthetic textured mesh models, in which each class includes multiple texture and geometric modifications of a small set of null models. Results show a challenging, yet lively, scenario and also reveal interesting insights into how to deal with texture information according to different approaches, possibly working in the CIELab as well as in modifications of the RGB colour space.Source: THE VISUAL COMPUTER, vol. 32 (issue 2), pp. 217-241
Project(s): VISIONAIR
See at:
CNR IRIS | link.springer.com | ISTI Repository | CNR IRIS | CNR IRIS
2013
Journal article
Restricted
PHOG: Photometric and Geometric Functions for Textured Shape Retrieval
Biasotti S, Cerri A, Giorgi D, Spagnuolo M
In this paper we target the problem of textured 3D object retrieval. As a first contribution, we show how to include photometric information in the persistence homology setting, also proposing a novel theoretical result about multidimensional persistence spaces. As a second contribution, we introduce a generalization of the integral geodesic distance which fuses shape and color properties. Finally, we adopt a purely geometric description based on the selection of geometric functions that are mutually independent. The photometric, hybrid and geometric descriptions are combined into a signature, whose performance is tested on a benchmark dataset.Source: COMPUTER GRAPHICS FORUM (PRINT), vol. 32 (issue 5), pp. 13-22
Biasotti S, Cerri A, Giorgi D, Spagnuolo M
In this paper we target the problem of textured 3D object retrieval. As a first contribution, we show how to include photometric information in the persistence homology setting, also proposing a novel theoretical result about multidimensional persistence spaces. As a second contribution, we introduce a generalization of the integral geodesic distance which fuses shape and color properties. Finally, we adopt a purely geometric description based on the selection of geometric functions that are mutually independent. The photometric, hybrid and geometric descriptions are combined into a signature, whose performance is tested on a benchmark dataset.Source: COMPUTER GRAPHICS FORUM (PRINT), vol. 32 (issue 5), pp. 13-22
See at:
CNR IRIS | CNR IRIS | onlinelibrary.wiley.com
2014
Conference article
Restricted
SHREC'14 Track: Retrieval and Classification on Textured 3D Models
Biasotti S, Cerri A, Abdelrahman M, Aono M, Ben Hamza A, Elmelegy M, Farag A, Garro V, Giachetti D, Giorgi D, Godil A, Li C, Liu Y, Martono H, Sanada C, Tatsuma A, Velascoforero S, Xu C
This paper reports the results of the SHREC'14 track: Retrieval and classification on textured 3D models, whose goal is to evaluate the performance of retrieval algorithms when models vary either by geometric shape or texture, or both. The collection to search in is made of 572 textured mesh models, having a two-level classification based on geometry and texture. Together with the dataset, a training set of 96 models was provided. The track saw eight participants and the submission of 22 runs, to either the retrieval or the classification contest, or both. The evaluation results show a promising scenario about textured 3D retrieval methods, and reveal interesting insights in dealing with texture information in the CIELab rather than in the RGB colour space.
Biasotti S, Cerri A, Abdelrahman M, Aono M, Ben Hamza A, Elmelegy M, Farag A, Garro V, Giachetti D, Giorgi D, Godil A, Li C, Liu Y, Martono H, Sanada C, Tatsuma A, Velascoforero S, Xu C
This paper reports the results of the SHREC'14 track: Retrieval and classification on textured 3D models, whose goal is to evaluate the performance of retrieval algorithms when models vary either by geometric shape or texture, or both. The collection to search in is made of 572 textured mesh models, having a two-level classification based on geometry and texture. Together with the dataset, a training set of 96 models was provided. The track saw eight participants and the submission of 22 runs, to either the retrieval or the classification contest, or both. The evaluation results show a promising scenario about textured 3D retrieval methods, and reveal interesting insights in dealing with texture information in the CIELab rather than in the RGB colour space.
2014
Other
Restricted
SEMEOTICONS - In-depth analysis of state-of-the-art for facial expression analysis
Colantonio S, Chiarugi F, Giannakakis G, Pediaditis M, Iatraki G, Christinaki E, Manousos D, Pampouchidou A, Marias K, Tsiknakis M, Giorgi D, Matuszewski B J
Human face can reveal precious information about the healthy or unhealthy status of individuals. SEMEOTICONS aims to exploit the human face as an indicator of individual's health status and translate the semeiotic code of the face into measurements and descriptors automatically evaluated by computerized applications. WP5, in specific, focuses on developing methods for the assessment of stress, anxiety and fatigue based on automatic facial expression analysis using video. Consequently, a complete and thorough analysis of self-contained approaches, specialized methods and reported research results for facial expression analysis, targeted at the detection of signs that disclose such psycho-physical states is performed.Project(s): SEMEOTICONS
Colantonio S, Chiarugi F, Giannakakis G, Pediaditis M, Iatraki G, Christinaki E, Manousos D, Pampouchidou A, Marias K, Tsiknakis M, Giorgi D, Matuszewski B J
Human face can reveal precious information about the healthy or unhealthy status of individuals. SEMEOTICONS aims to exploit the human face as an indicator of individual's health status and translate the semeiotic code of the face into measurements and descriptors automatically evaluated by computerized applications. WP5, in specific, focuses on developing methods for the assessment of stress, anxiety and fatigue based on automatic facial expression analysis using video. Consequently, a complete and thorough analysis of self-contained approaches, specialized methods and reported research results for facial expression analysis, targeted at the detection of signs that disclose such psycho-physical states is performed.Project(s): SEMEOTICONS
2015
Other
Open Access
SEMEOTICONS - D1.3: Description of SEMEOTICONS reference dataset
Colantonio S, Giorgi D, Coppini G, Morales M, Favilla R, Mazzarisi A, Chiarugi F, Stromberg T, Larsson M, Randeberg L, Matuszewski Bj
This report describes the data that were include in the SEMEOTICONS reference data set following the acquisition campaign held in Pisa in May 2014 (Task 1.3). The Campaign saw the participation of all partners involved both in semeiotic modelling of cardio-metabolic risk and in developing methods to extract computational descriptor of facial sign of CM risk.Project(s): SEMEOTICONS
Colantonio S, Giorgi D, Coppini G, Morales M, Favilla R, Mazzarisi A, Chiarugi F, Stromberg T, Larsson M, Randeberg L, Matuszewski Bj
This report describes the data that were include in the SEMEOTICONS reference data set following the acquisition campaign held in Pisa in May 2014 (Task 1.3). The Campaign saw the participation of all partners involved both in semeiotic modelling of cardio-metabolic risk and in developing methods to extract computational descriptor of facial sign of CM risk.Project(s): SEMEOTICONS
2015
Other
Restricted
SEMEOTICONS - D6.1 User's profiling tools
Genitsaridi I, Chiarugi F, Marias K, Tsiknakis M, Coppini G, Morales M, Marraccini P, Giorgi D, Pascali M A
This document reports on the activities performed in Task 6.1 "User's profiling". The reported activities on this task have been undertaken between month 1 and 18 of the project. The task was ended in month 18 with the release of this deliverable D6.1 "User's profiling tools". The accurate definition of the user's profile is necessary to set, for each subject, a reliable starting point for the wellness status assessment. Many medical and behavioural data such as: age, height, weight, cholesterol level, phenotype, habits, sports, others may influence the user's profile. Also the psychological information, such as anxiety, stress, and attitude towards health issues should be taken into account because of their strong relevance in the choice of the support to be provided by the system.Project(s): SEMEOTICONS
Genitsaridi I, Chiarugi F, Marias K, Tsiknakis M, Coppini G, Morales M, Marraccini P, Giorgi D, Pascali M A
This document reports on the activities performed in Task 6.1 "User's profiling". The reported activities on this task have been undertaken between month 1 and 18 of the project. The task was ended in month 18 with the release of this deliverable D6.1 "User's profiling tools". The accurate definition of the user's profile is necessary to set, for each subject, a reliable starting point for the wellness status assessment. Many medical and behavioural data such as: age, height, weight, cholesterol level, phenotype, habits, sports, others may influence the user's profile. Also the psychological information, such as anxiety, stress, and attitude towards health issues should be taken into account because of their strong relevance in the choice of the support to be provided by the system.Project(s): SEMEOTICONS
2019
Other
Restricted
A survey on 3D shape segmentation with focus on digital fabrication
Filoscia I, Alderighi T Cignoni P, Giorgi D, Malomo L
Segmenting 3D objects into parts is fundamental to a number of applications in computer graphics, including parametrization, texture mapping, shape matching, morphing, multi-resolution modeling, mesh editing, compression and animation [22]. Broadly speaking, shape segmentation techniques can be divided into geometry-based and semantics-based techniques. Geometry-based segmentations aim to partition the object into parts which have well-defined geometric properties such as size, curvature, or distance to a fitting primitive like a plane. Semantics-based segmentations, in turn, aim at identifying parts which are either visually relevant or meaningful in a given context, such as functional parts on mechanical objects or body parts on human models. Recently, 3D segmentation also drawn attention as a tool for efficient fabrication. The decomposition of objects into parts, indeed, helps solving different issues related to fabrication, such as height field constraints, volume constraints and need for supporting structures. In this work we present a complete survey of segmentation techniques, also highlighting their strengths and weaknesses. Our aim is to produce a handy overview to people who want to approach the problem of segmentation, especially if they want to apply it to digital fabrication.
Filoscia I, Alderighi T Cignoni P, Giorgi D, Malomo L
Segmenting 3D objects into parts is fundamental to a number of applications in computer graphics, including parametrization, texture mapping, shape matching, morphing, multi-resolution modeling, mesh editing, compression and animation [22]. Broadly speaking, shape segmentation techniques can be divided into geometry-based and semantics-based techniques. Geometry-based segmentations aim to partition the object into parts which have well-defined geometric properties such as size, curvature, or distance to a fitting primitive like a plane. Semantics-based segmentations, in turn, aim at identifying parts which are either visually relevant or meaningful in a given context, such as functional parts on mechanical objects or body parts on human models. Recently, 3D segmentation also drawn attention as a tool for efficient fabrication. The decomposition of objects into parts, indeed, helps solving different issues related to fabrication, such as height field constraints, volume constraints and need for supporting structures. In this work we present a complete survey of segmentation techniques, also highlighting their strengths and weaknesses. Our aim is to produce a handy overview to people who want to approach the problem of segmentation, especially if they want to apply it to digital fabrication.
2021
Journal article
Open Access
Smart Working at CNR-ISTI in the COVID-19 Era
Scopigno R, Giorgi D
The CNR Institute for Information Science and Technologies describes its experience in adapting to smart working, which has dramatically changed the institute's modus operandi for most of the year 2020.Source: ERCIM NEWS, pp. 6-7
Scopigno R, Giorgi D
The CNR Institute for Information Science and Technologies describes its experience in adapting to smart working, which has dramatically changed the institute's modus operandi for most of the year 2020.Source: ERCIM NEWS, pp. 6-7
See at:
ercim-news.ercim.eu | CNR IRIS | ISTI Repository | CNR IRIS
2017
Journal article
Open Access
Lip segmentation on hyper-spectral images
Danielis A, Giorgi D, Colantonio S
We present a lip segmentation method based on simulated Lambertian shadings. The input consists of hyper-spectral images generated by a prototype for medical applications.Source: ERCIM NEWS, pp. 40-41
Project(s): SEMEOTICONS
Danielis A, Giorgi D, Colantonio S
We present a lip segmentation method based on simulated Lambertian shadings. The input consists of hyper-spectral images generated by a prototype for medical applications.Source: ERCIM NEWS, pp. 40-41
Project(s): SEMEOTICONS
See at:
ISTI Repository | ercim-news.ercim.eu | CNR IRIS | CNR IRIS
2011
Journal article
Open Access
A new algorithm for computing the 2-dimensional matching distance between size functions
Biasotti S., Cerri A., Frosini P., Giorgi D.
Size Theory has proven to be a useful geometrical/topological approach to shape comparison. Originally introduced by considering 1-dimensional properties of shapes, described by means of real-valued functions, it has recently been generalized to taking into account multi-dimensional properties coded by functions valued in R^k. This has led to the introduction of a shape descriptor called k-dimensional size function, and the k-dimensional matching distance to compare size functions. This paper presents new theoretical results about the 2-dimensional matching distance, leading to the formulation of an algorithm for its approximation up to an arbitrary error threshold. Experiments on 3D object comparison are shown to discuss the efficacy and effectiveness of the algorithm.Source: PATTERN RECOGNITION LETTERS, vol. 32 (issue 14), pp. 1735-1746
Biasotti S., Cerri A., Frosini P., Giorgi D.
Size Theory has proven to be a useful geometrical/topological approach to shape comparison. Originally introduced by considering 1-dimensional properties of shapes, described by means of real-valued functions, it has recently been generalized to taking into account multi-dimensional properties coded by functions valued in R^k. This has led to the introduction of a shape descriptor called k-dimensional size function, and the k-dimensional matching distance to compare size functions. This paper presents new theoretical results about the 2-dimensional matching distance, leading to the formulation of an algorithm for its approximation up to an arbitrary error threshold. Experiments on 3D object comparison are shown to discuss the efficacy and effectiveness of the algorithm.Source: PATTERN RECOGNITION LETTERS, vol. 32 (issue 14), pp. 1735-1746
See at:
CNR IRIS | www.sciencedirect.com | CNR IRIS | CNR IRIS
2011
Conference article
Restricted
Robustness and modularity of 2-dimensional size-functions functions - An experimental study
Biasotti S., Cerri A., Giorgi D.
This paper deals with the concepts of 2-dimensional size function and 2-dimensional matching distance. These are two ingredients of (2-dimensional) Size Theory, a geometrical/topological approach to shape analysis and comparison. 2-dimensional size functions are shape descriptors providing a signature of the shapes under study, while the 2-dimensional distance is the tool to compare them. The aim of the present paper is to validate, through some experiments on 3D-models, a computational framework recently introduced to deal with 2-dimensional Size Theory. We will show that the cited framework is modular and robust with respect to noise, non-rigid and non-metric-preserving shape transformations. The proposed framework allows us to improve the ability of 2-dimensional size functions in discriminating between shapes.Source: LECTURE NOTES IN COMPUTER SCIENCE, vol. 6854, pp. 34-41. Seville, Spain, 29-31/08/2011
Biasotti S., Cerri A., Giorgi D.
This paper deals with the concepts of 2-dimensional size function and 2-dimensional matching distance. These are two ingredients of (2-dimensional) Size Theory, a geometrical/topological approach to shape analysis and comparison. 2-dimensional size functions are shape descriptors providing a signature of the shapes under study, while the 2-dimensional distance is the tool to compare them. The aim of the present paper is to validate, through some experiments on 3D-models, a computational framework recently introduced to deal with 2-dimensional Size Theory. We will show that the cited framework is modular and robust with respect to noise, non-rigid and non-metric-preserving shape transformations. The proposed framework allows us to improve the ability of 2-dimensional size functions in discriminating between shapes.Source: LECTURE NOTES IN COMPUTER SCIENCE, vol. 6854, pp. 34-41. Seville, Spain, 29-31/08/2011
See at:
CNR IRIS | CNR IRIS | CNR IRIS | www.springerlink.com
2020
Conference article
Open Access
Topological classification of Vittorio Giorgini's sculptures
Giorgi D., Del Francia M., Ferri M., Cignoni P.
The Italian architect Vittorio Giorgini (1926 - 2010) was among the first artists to incorporate the topological concepts of space and transformation into architecture and art. In this paper, we first present Giorgini's beautiful pieces of art, which were largely unrecognized in his lifetime. Then we unveil the true mathematical types of some of his most famous sculptures.
Giorgi D., Del Francia M., Ferri M., Cignoni P.
The Italian architect Vittorio Giorgini (1926 - 2010) was among the first artists to incorporate the topological concepts of space and transformation into architecture and art. In this paper, we first present Giorgini's beautiful pieces of art, which were largely unrecognized in his lifetime. Then we unveil the true mathematical types of some of his most famous sculptures.
See at:
archive.bridgesmathart.org | CNR IRIS | CNR IRIS
2016
Journal article
Open Access
Wize Mirror - a smart, multisensory cardio-metabolic risk monitoring system
Andreu Y, Chiarugi F, Colantonio S, Giannakakis G, Giorgi D, Henriquez P, Kazantzaki E, Manousos D, Kostas M, Matuszewski B J, Pascali M A, Pediaditis M, Raccichini G, Tsiknakis M
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.Source: COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 148, pp. 3-22
Project(s): SEMEOTICONS
Andreu Y, Chiarugi F, Colantonio S, Giannakakis G, Giorgi D, Henriquez P, Kazantzaki E, Manousos D, Kostas M, Matuszewski B J, Pascali M A, Pediaditis M, Raccichini G, Tsiknakis M
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.Source: COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 148, pp. 3-22
Project(s): SEMEOTICONS
See at:
CNR IRIS | ISTI Repository | www.sciencedirect.com | CNR IRIS
2016
Journal article
Open Access
Face morphology: Can it tell us something about body weight and fat?
Pascali Ma, Giorgi D, Bastiani L, Buzzigoli E, Henriquez P, Matuszewski Bj, Morales Ma, Colantonio S
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.Source: COMPUTERS IN BIOLOGY AND MEDICINE, vol. 76, pp. 238-249
Pascali Ma, Giorgi D, Bastiani L, Buzzigoli E, Henriquez P, Matuszewski Bj, Morales Ma, Colantonio S
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.Source: COMPUTERS IN BIOLOGY AND MEDICINE, vol. 76, pp. 238-249
See at:
CNR IRIS | ISTI Repository | www.sciencedirect.com | CNR IRIS | CNR IRIS