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10 Papers

Collaborative Activities Understanding from 3D Data

Authors: Fabrizio Natola , Valsamis Ntouskos and Fiora Pirri

Affiliation: Sapienza University of Rome, Italy

Proceedings of DCPRAM 2015/ICPRAM

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Our work consists in finding a way to recognize activities performed by two people that collaborate in a working environment. Starting from results obtained in the past years by Gong, Medioni and other authors, we go a step forward, trying to construct a learning function that is able to generalize the model provided by the authors cited before. Moreover, we search for a space in which we can map the points corresponding to the poses, over time, of the skeletons of the two subjects, so that no information is lost.

Point Cloud Structural Parts Extraction based on Segmentation Energy Minimization

Topics: Scene and Object Modeling; Geometric Computing; Surface Modeling

Authors: Bruno Cafaro , Iman Azimi , Valsamis Ntouskos , Fiora Pirri and Manuel Ruiz

Affiliation: “Sapienza” University of Rome, Italy

Digital Object Identifier: 10.5220/0005309301500157

Proceedings of GRAPP 2015/VISIGRAPP, ISBN: 978-989-758-087-1

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In this work we consider 3D point sets, which in a typical setting represent unorganized point clouds. Segmentation of these point sets requires first to single out structural components of the unknown surface discretely approximated by the point cloud. Structural components, in turn, are surface patches approximating unknown parts of elementary geometric structures, such as planes, ellipsoids, spheres and so on. The approach used is based on level set methods computing the moving front of the surface and tracing the interfaces between different parts of it. Level set methods are widely recognized to be one of the most efficient methods to segment both 2D images and 3D medical images. Level set methods for 3D segmentation have recently received an increasing interest. We contribute by proposing a novel approach for raw point sets. Based on the motion and distance functions of the level set we introduce four energy minimization models, which are used for segmentation, by considering an equal number of distance functions specified by geometric features. Finally we evaluate the proposed algorithm on point sets simulating unorganized point clouds.
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Computer Vision, Visualization and Computer Graphics

Geometry and Modeling

Surface Modeling
Geometric Computing

Scene and Object Modeling

A Comprehensive Framework for Semantic Annotation of Web Content

Topics: Ontology Engineering; Semantic Web; Knowledge Acquisition

Authors: Manuel Fiorelli , Maria Teresa Pazienza and Armando Stellato

Affiliation: University of Rome, Italy

Digital Object Identifier: 10.5220/0004545702450252

Proceedings of KEOD 2013/IC3K, ISBN: 978-989-8565-81-5

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Studies on Semantic Annotation reveal how trying to match heterogeneous requirements leads to divergent methodologies, models and processes for annotation management and exchange. Community efforts towards the development of shared solutions are important to reduce the “entropy” of the field; nonetheless, any agreement on the ultimate annotation system is unlikely to be achieved. We propose a solution to this problem by defining a comprehensive framework, unbound to any specific design/annotation model, and instantiable into concrete system implementations, to meet different requirements. Towards this goal, we commit to fairly general assumptions, valid across disparate systems and not excessively constraining. Firstly, most systems deal with combined management of ontologies and Web content. Secondly, these systems can be described through a common behavioural model, in terms of an assignment of handlers to predetermined events. This behavioural model can be then enriched through progressive levels of specification, thus fostering a convention-over-configuration approach in detailing its characteristics. Then, recurring design fragments can be identified, in order to provide abstractions and specifications for the definition of concrete handlers.
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Artificial Intelligence

Information Systems Analysis and Specification

Ontology Engineering

Collaboration and e-Services

Knowledge Acquisition

Semantic Web

Data Engineering

Knowledge Engineering and Ontology Development

Soft Computing

e-Business

Knowledge-Based Systems

Symbolic Systems
Enterprise Information Systems

Ontologies and the Semantic Web

Discriminative Sequence Back-constrained GP-LVM for MOCAP based Action Recognition

Topics: Gaussian Processes; Classification; Embedding and Manifold Learning; Perception

Authors: Valsamis Ntouskos , Panagiotis Papadakis and Fiora Pirri

Affiliation: University of Rome, Italy

Digital Object Identifier: 10.5220/0004268600870096

Proceedings of ICPRAM 2013, ISBN: 978-989-8565-41-9

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In this paper we address the problem of human action recognition within Motion Capture sequences. We introduce a method based on Gaussian Process Latent Variable Models and Alignment Kernels. We build a new discriminative latent variable model with back-constraints induced by the similarity of the original sequences. We compare the proposed method with a standard sequence classification method based on Dynamic Time Warping and with the recently introduced V-GPDS model which is able to model highly dimensional dynamical systems. The proposed methodology exhibits high performance even for datasets that have not been manually preprocessed while it further allows fast inference by exploiting the back constraints.
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Applications

Gaussian Processes

Perception

Classification

Pattern Recognition

Theory and Methods
Embedding and Manifold Learning

A COMPREHENSIVE ANALYSIS OF HUMAN MOTION CAPTURE DATA FOR ACTION RECOGNITION

Topics: Event and Human Activity Recognition; Vision for Robotics

Authors: Valsamis Ntouskos , Panagiotis Papadakis and Fiora Pirri

Affiliation: University of Rome ”La Sapienza”, Italy

Digital Object Identifier: 10.5220/0003868806470652

Proceedings of VISAPP 2012/VISIGRAPP, ISBN: 978-989-8565-03-7

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In this paper, we present an analysis of human motion that can assist the recognition of human actions irrespective of the selection of particular features. We begin with an analysis on the entire set of preclassified motions in order to derive the generic characteristics of articulated human motion and complement the analysis by a more detailed inter-class analysis. The statistical analysis concerns features that describe the significancecontribution of the human joints in performing an action. Furthermore, we adopt a hierarchical analysis on the human body itself in the study of different actions, by grouping joints that share common characteristics. We present our experiments on standard databases for human motion capture data as well as a new commercial dataset with additional classes of human motion and highlight certain interesting results.
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Applications

Robotics

Software Engineering
Pattern Recognition

CONSTRAINT-FREE TOPOLOGICAL MAPPING AND PATH PLANNING BY MAXIMA DETECTION OF THE KERNEL SPATIAL CLEARANCE DENSITY

Topics: Perception; Robotics

Authors: Panagiotis Papadakis , Mario Gianni , Fiora Pirri and Matia Pizzoli

Affiliation: University of Rome “La Sapienza”, Italy

Digital Object Identifier: 10.5220/0003735300710079

Proceedings of ICPRAM 2012, ISBN: 978-989-8425-99-7

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Asserting the inherent topology of the environment perceived by a robot is a key prerequisite of high-level decision making. This is achieved through the construction of a concise representation of the environment that endows a robot with the ability to operate in a coarse-to-fine strategy. In this paper, we propose a novel topological segmentation method of generic metric maps operating concurrently as a path-planning algorithm. First, we apply a Gaussian Distance Transform on the map that weighs points belonging to free space according to the proximity of the surrounding free area in a noise resilient mode. We define a region as the set of all the points that locally converge to a common point of maximum space clearance and employ a weighed meanshift gradient ascent onto the kernel space clearance density in order to detect the maxima that characterize the regions. The spatial intra-connectivity of each cluster is ensured by allowing only for linearly unobstructed mean-shifts which in parallel serves as a path-planning algorithm by concatenating the consecutive mean-shift vectors of the convergence paths. Experiments on structured and unstructured environments demonstrate the effectiveness and potential of the proposed approach.
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Applications

Perception

Software Engineering
Pattern Recognition

Robotics

EDUCATION WITH “LIVING ARTWORKS” IN MUSEUMS

Topic: Intelligent Tutoring Systems

Authors: Roberta Beccaceci , Francesca Fallucchi , Cristina Giannone , Francesca Spagnoulo and Fabio Massimo Zanzotto

Affiliation: University of Rome ”Tor Vergata”, Italy

Digital Object Identifier: 10.5220/0002158903460349

Proceedings of CSEDU 2009, ISBN: 978-989-8111-82-1

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Museums need to find innovative ways of communicating if these institutions want to survive in the new era and want to play their active role of educators. In this paper, we will present our idea of living artworks. Using conversational agents we want to give artworks the capability of talking to visitors. A living artwork attracts attention, being a funny and novel combination of art and technology. The mix of experience and action has a beneficial effect in learning new concepts or facts. We will then present our methodology for building living artworks, the enabling technologies, and a case study.
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Artificial Intelligence and Decision Support Systems

e-Learning

Information Technologies Supporting Learning

Computer-Supported Education

Enterprise Information Systems

Intelligent Tutoring Systems

SEMANTIC TURKEY - A New Web Experience in between Ontology Editing and Semantic Annotation

Topics: XML and Data Management; Searching and Browsing; System Integration; Web Services and Web Engineering; Distributed and Parallel Applications; Multimedia and User Interfaces; Digital Libraries; Databases and Datawarehouses; Ontology and the Semantic Web; Web Mining

Authors: Francesca Falluchi , Maria Teresa Pazienza , Noemi Scarpato and Armando Stellato

Affiliation: DISP, University of Tor Vergata, Italy

Digital Object Identifier: 10.5220/0001526600900097

Proceedings of WEBIST 2008, ISBN: 978-989-8111-27-2

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In this work we describe Semantic Turkey, a Semantic Extension for the popular web browser Mozilla Firefox. Semantic Turkey can be used to keep track of relevant information from visited web sites and organize collected content according to a personally defined ontology. In this sense, Semantic Turkey can be seen both as an advanced semantic bookmarking system as well as an ontology editing assistant, which allows domain experts and ontology developers to build ontologies starting from the very raw source of information which they find on the web. The open architecture of Semantic Turkey and the specific three-layered approach of its design also allows for scaling the basic personal desktop application embodied by this tool up to a distributed framework for collaborative semantic annotation and ontology editing. This paper describes the architecture and the functionalities of the Semantic Turkey extension for Firefox, and describe possible evolutions for future improvement of the tool.
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Artificial Intelligence

Knowledge Management and Information Sharing

Symbolic Systems

Data Engineering

Knowledge-Based Systems

System Integration

Databases and Datawarehouses

Multimedia and User Interfaces

Web Information Systems and Technologies

Digital Libraries

Ontologies and the Semantic Web

Web Interfaces and Applications

Distributed and Parallel Applications

Ontology and the Semantic Web

Web Mining

Internet Technology

Searching and Browsing

Web Services and Web Engineering

Knowledge Discovery and Information Retrieval

Soft Computing

XML and Data Management

SOFTWARE SEMANTIC PROVISIONING - Actually Reusing Software

Topics: Agile Software Development; Knowledge Management and Engineering; Cross-Feeding between Data Engineering and Software Engineering; Software Development Methodologies

Authors: Savino Sguera 1 , Philippe Ombredanne 2 , Armando Stellato 1 and Maria Teresa Pazienza 1

Affiliations: 1 DISP, University of Rome Tor Vergata, Italy , 2 Eclipse Software Foundation, Italy

Digital Object Identifier: 10.5220/0001763501850188

Proceedings of ENASE 2008, ISBN: 978-989-8111-28-9

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Delivering component-oriented architectures is a well-established trend in software engineering and development. Assessing software reuse scenarios goes much beyond the usual “build vs buy” dilemma that so often occurs in early stages of a software process: scouting, comparing, choosing and integrating the right set of components meeting project’s requirements is still an ad-hoc and error-prone task, performed by developers with little or no frameworks and tools to support them. This paper describes the SSP (Software Semantic Provisioning) project, funded in its early stages by GoogleTM Inc., developed during the Google Summer of CodeTM 2007 program, and incubated by the Eclipse Software Foundation; the project aims to provide an ontological description of the software domain to underlie a semantic web framework to support developers in scouting and provisioning software components. A prototypical RESTful semantic repository, and an Eclipse plug-in consuming the repository services have been implemented and will be discussed.
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Agile Methodologies

Knowledge Engineering and Ontology Development

Software Engineering

Artificial Intelligence

Knowledge-Based Systems

Software Project Management

Cross-Feeding between Data and Software Engineering

Service-Oriented Software Engineering and Management

Symbolic Systems
Knowledge Engineering

Software and Systems Development Methodologies

THEMATIC OASES - Towards a Social Semantic Web

Topics: Searching and Browsing; Web Services and Web Engineering; Ontology and the Semantic Web

Authors: Maria Teresa Pazienza , Savino Sguera and Armando Stellato

Affiliation: DISP, University of Tor Vergata, Italy

Digital Object Identifier: 10.5220/0001532603510354

Proceedings of WEBIST 2008, ISBN: 978-989-8111-27-2

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A few years have passed from the first alarming yells about the unmanageable growth of data which is literally exploding from the Web. While Web2.0 technologies, born and grown from the crowd of the web community, are reaching their full maturity, and with W3C eventually managing to give concreteness to Berners-Lee Semantic Web Vision through a plethora of new languages and protocols, the same problem is still a living matter. Lots of vendors and providers offer social services with more-than-overlapping aspects, but with no intentions of sharing their data. RSS aggregators as well as blog and mailing list scrapers, erupt tons of data which are irritatingly replicated by search engines indexes. At the same time, most of the information services (wikis, blogs, mailing lists, forums, newsgroups etc...) still maintain their traditional functionalities and move no step forward reaching any kind of interoperability. In this paper we analyze the current scenario and propose our personal view on how new Semantic Web technologies could be employed to give life to a new generation of social, heterogeneous and coordinated informative services: Thematic Oases.
Collapse Button Related Ontology Subjects/Areas/Topics (6)
Internet Technology

Searching and Browsing

Web Interfaces and Applications

Ontology and the Semantic Web

Web Information Systems and Technologies

Web Services and Web Engineering

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