A growing number of research approaches are focusing on combining multimedia retrieval processing... more A growing number of research approaches are focusing on combining multimedia retrieval processing with semantics and knowledge based methods in order to achieve higher-level understanding of multimedia content. This research direction, often called semantic multimedia, combines techniques such as low-level multimedia feature extraction and common semantic representation schemes for features and concepts, thus making possible to manage query based on semantics that is a way for better supporting end user searches and result visualization in multimedia retrieval. Since low-level representations of media greatly differ from the higher level concepts associated with them, understanding the semantics of a query required a further insight in multimedia retrieval to bridge the semantic gap. In this paper we review the state-of-the-art techniques in semantic multimedia retrieval by discussing how relevant multimedia retrieval systems incorporate a semantic layer to improve the system perfor...
Abstract—In this paper we present an overview of the most interesting object description techniqu... more Abstract—In this paper we present an overview of the most interesting object description techniques which depicts some descriptors that could be used to support higher level components for object recognition, behavior analysis, classification, and clustering. We are focused our attention on those techniques which are suitable to be used in what are known as real-life environments. In particular the underwater environment were taken into account since it shows a lot of difficulties concenring the low quality of the observed scene and the targets themselves (i.e. fish) which are characterized by fast and erratic movements and more degrees of freedom in motion than, for example, people or vehicles in urban environments. Keywords-object description; color, texture, motion and contour features; underwater environment; fish descriptors; I.
ABSTRACT In this thesis a set of novel video annotation methods for performance evaluation of obj... more ABSTRACT In this thesis a set of novel video annotation methods for performance evaluation of object detection, tracking and recognition applications is proposed. Large scale labeled datasets are of key importance for the development of automatic video analysis tools as they, from one hand, allow multi-class classifiers training and, from the other hand, support the algorithms’ evaluation phase. This is widely recognized by the multimedia and computer vision communities, as witnessed by the growing number of available datasets; however, the research still lacks in usable and effective annotation tools, since a lot of human effort is necessary to generate high quality ground truth data. However, it is not feasible to collect large video ground truths, covering as much scenarios and object categories as possible, by exploiting only the effort of isolated research groups. For these reasons in this thesis we first present a semi-automatic stand-alone tool for gathering ground truth data with the aim of improving the user experience by providing edit shortcuts such as hotkeys and drag-and-drop, and by integrating computer vision algorithms to make the whole process automatic with a little intervention by the end users. In this context we also present a collaborative web-based platform for video ground truthing which integrates the stand-alone tools and provides an easy and intuitive user interface that allows plain video annotation and instant sharing/integration of the generated ground truths, in order not to only alleviate a large part of the effort and time needed, but also to increase the quality of the generated annotations. These tools are specifically thought to help users in collecting annotations thanks to the introduction of simple interfaces, which considerably improve and facilitate their work, also by integrating novel methods for quality control, but still remain a burdensome task with regard to the attention and time needed to obtain good records. To motivate the users and relieve them from the tiresome task of making manual annotations, we devised strategies to automatically create annotation by processing data from the crowd. To this end we initially develop an approach based on an online game to collect big noisy data. By exploiting the information, we then propose data-driven approaches, mainly based on image segmentation and statistical methods, which allow us to obtain reliable video annotations by using low quality and noisy data gathered quickly and easily from the game. Also we demonstrate that the quality of the obtained annotations increases as more users play with the game making it an effective and valid application for the collection of consistent ground truth data.
ABSTRACT A growing number of research approaches are focusing on combining multimedia retrieval p... more ABSTRACT A growing number of research approaches are focusing on combining multimedia retrieval processing with semantics and knowledge based methods in order to achieve higher-level understanding of multimedia content. This research direction, often called semantic multimedia, combines techniques such as low-level multimedia feature extraction and common semantic representation schemes for features and concepts, thus making possible to manage query based on semantics that is a way for better supporting end user searches and result visualization in multimedia retrieval. Since low-level representations of media greatly differ from the higher level concepts associated with them, understanding the semantics of a query required a further insight in multimedia retrieval to bridge the semantic gap. In this paper we review the state-of-the-art techniques in semantic multimedia retrieval by discussing how relevant multimedia retrieval systems incorporate a semantic layer to improve the system performance. Some criticism is also expressed since the current systems lack in clustering to increase the recall and to support the reuse of multimedia material for developing new artefacts, thus envisaging novel research directions.
Proceedings of the 13th WSEAS international …, 2011
... [38] SI Park, SP Ponce, J. Huang, Y. Cao, F. Quek, Low-cost, high-speed computer vision usin... more ... [38] SI Park, SP Ponce, J. Huang, Y. Cao, F. Quek, Low-cost, high-speed computer vision using NVIDIA's CUDA architecture, 2008 37th IEEE Applied Imagery Pattern Recognition Workshop, Oct. ... [41] J. Gomez-Luna, JM González-Linares, JI Benavides, N. Guil ...
Title: Complex networks in geosciences: a global and a local scale cases study. Authors: Bonforte... more Title: Complex networks in geosciences: a global and a local scale cases study. Authors: Bonforte, Alessandro; Nunnari, Giuseppe; Puglisi, Giuseppe; di Salvo, Roberto; Spata, Alessandro. Affiliation: AA(Istituto Nazionale di Geofisica ...
Title: Complex networks in geosciences: a global and a local scale cases study. Authors: Bonforte... more Title: Complex networks in geosciences: a global and a local scale cases study. Authors: Bonforte, Alessandro; Nunnari, Giuseppe; Puglisi, Giuseppe; di Salvo, Roberto; Spata, Alessandro. Affiliation: AA(Istituto Nazionale di Geofisica ...
Il monitoraggio sistematico delle variazioni dell'inclinazione del suolo, viene effettuato s... more Il monitoraggio sistematico delle variazioni dell'inclinazione del suolo, viene effettuato sui vulcani siciliani dall'INGV-CT, utilizzando differenti tipi di sensori ad alta precisione capaci di rilevare inclinazioni del suolo fino a 10-8 radianti (Bonaccorso ed al., 2004). Le misure di tilt in continuo sui vulcani rappresentano un metodo rapido per l'individuazione di precursori di un'eruzione ed uno strumento di studio del comportamento dei vulcani stessi nelle fasi pre e post-eruttive.
In this thesis a set of novel video annotation methods for performance evaluation of object detec... more In this thesis a set of novel video annotation methods for performance evaluation of object detection, tracking and recognition applications is proposed. Large scale labeled datasets are of key importance for the development of automatic video analysis tools as they, from one hand, allow multi-class classifiers training and, from the other hand, support the algorithms’ evaluation phase. This is widely recognized by the multimedia and computer vision communities, as witnessed by the growing number of available datasets; however, the research still lacks in usable and effective annotation tools, since a lot of human effort is necessary to generate high quality ground truth data. However, it is not feasible to collect large video ground truths, covering as much scenarios and object categories as possible, by exploiting only the effort of isolated research groups. For these reasons in this thesis we first present a semi-automatic stand-alone tool for gathering ground truth data with the...
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013), 2013
ABSTRACT The growth of data produced by the medical and clinical community requires the introduct... more ABSTRACT The growth of data produced by the medical and clinical community requires the introduction of advanced techniques and resources in terms of computational and storage capabilities. The different problems and needs that afflict the information technologies for health support conduce to adoption of new infrastructure and application based on cloud computing. The different problems concerning to one side to the managerial, administrative and management aspects, to the other side concern who works as a physician or researcher, that needs the infrastructure to process, store, manage patient data, analysis, diagnosis, and so on. Today, cloud computing represents an important alternative to ensure high performance data processing and easy management of the complex tools in different area and in health. Cloud computing can solve many of these problems providing several advantages in terms of resource management and computational capabilities. In this paper a survey concerning the current models of health that are switching to solutions based on cloud computing, is proposed. Different applications and services are explored and concluded that the use of cloud computing and in particular of hybrid cloud solution can represent a significant opportunity to increase the development of the health sector in all its aspects.
Proceedings of the International Workshop on Video and Image Ground Truth in Computer Vision Applications - VIGTA '13, 2013
ABSTRACT In this paper we present an innovative approach to support efficient large scale video a... more ABSTRACT In this paper we present an innovative approach to support efficient large scale video annotation by exploiting the crowdsourcing. In particular, we collect big noisy annotations by an on-line Flash game which aims at taking photos of objects appearing through the game levels. The data gathered (suitably processed) from the game is then used to drive image segmentation approaches, namely the Region Growing and Grab Cut, which allow us to derive meaningful annotations. A comparison against hand-labeled ground truth data showed that the proposed approach constitutes a valid alternative to the existing video annotation approaches and allow a reliable and fast collection of large scale ground truth data for performance evaluation in computer vision.
A growing number of research approaches are focusing on combining multimedia retrieval processing... more A growing number of research approaches are focusing on combining multimedia retrieval processing with semantics and knowledge based methods in order to achieve higher-level understanding of multimedia content. This research direction, often called semantic multimedia, combines techniques such as low-level multimedia feature extraction and common semantic representation schemes for features and concepts, thus making possible to manage query based on semantics that is a way for better supporting end user searches and result visualization in multimedia retrieval. Since low-level representations of media greatly differ from the higher level concepts associated with them, understanding the semantics of a query required a further insight in multimedia retrieval to bridge the semantic gap. In this paper we review the state-of-the-art techniques in semantic multimedia retrieval by discussing how relevant multimedia retrieval systems incorporate a semantic layer to improve the system perfor...
Abstract—In this paper we present an overview of the most interesting object description techniqu... more Abstract—In this paper we present an overview of the most interesting object description techniques which depicts some descriptors that could be used to support higher level components for object recognition, behavior analysis, classification, and clustering. We are focused our attention on those techniques which are suitable to be used in what are known as real-life environments. In particular the underwater environment were taken into account since it shows a lot of difficulties concenring the low quality of the observed scene and the targets themselves (i.e. fish) which are characterized by fast and erratic movements and more degrees of freedom in motion than, for example, people or vehicles in urban environments. Keywords-object description; color, texture, motion and contour features; underwater environment; fish descriptors; I.
ABSTRACT In this thesis a set of novel video annotation methods for performance evaluation of obj... more ABSTRACT In this thesis a set of novel video annotation methods for performance evaluation of object detection, tracking and recognition applications is proposed. Large scale labeled datasets are of key importance for the development of automatic video analysis tools as they, from one hand, allow multi-class classifiers training and, from the other hand, support the algorithms’ evaluation phase. This is widely recognized by the multimedia and computer vision communities, as witnessed by the growing number of available datasets; however, the research still lacks in usable and effective annotation tools, since a lot of human effort is necessary to generate high quality ground truth data. However, it is not feasible to collect large video ground truths, covering as much scenarios and object categories as possible, by exploiting only the effort of isolated research groups. For these reasons in this thesis we first present a semi-automatic stand-alone tool for gathering ground truth data with the aim of improving the user experience by providing edit shortcuts such as hotkeys and drag-and-drop, and by integrating computer vision algorithms to make the whole process automatic with a little intervention by the end users. In this context we also present a collaborative web-based platform for video ground truthing which integrates the stand-alone tools and provides an easy and intuitive user interface that allows plain video annotation and instant sharing/integration of the generated ground truths, in order not to only alleviate a large part of the effort and time needed, but also to increase the quality of the generated annotations. These tools are specifically thought to help users in collecting annotations thanks to the introduction of simple interfaces, which considerably improve and facilitate their work, also by integrating novel methods for quality control, but still remain a burdensome task with regard to the attention and time needed to obtain good records. To motivate the users and relieve them from the tiresome task of making manual annotations, we devised strategies to automatically create annotation by processing data from the crowd. To this end we initially develop an approach based on an online game to collect big noisy data. By exploiting the information, we then propose data-driven approaches, mainly based on image segmentation and statistical methods, which allow us to obtain reliable video annotations by using low quality and noisy data gathered quickly and easily from the game. Also we demonstrate that the quality of the obtained annotations increases as more users play with the game making it an effective and valid application for the collection of consistent ground truth data.
ABSTRACT A growing number of research approaches are focusing on combining multimedia retrieval p... more ABSTRACT A growing number of research approaches are focusing on combining multimedia retrieval processing with semantics and knowledge based methods in order to achieve higher-level understanding of multimedia content. This research direction, often called semantic multimedia, combines techniques such as low-level multimedia feature extraction and common semantic representation schemes for features and concepts, thus making possible to manage query based on semantics that is a way for better supporting end user searches and result visualization in multimedia retrieval. Since low-level representations of media greatly differ from the higher level concepts associated with them, understanding the semantics of a query required a further insight in multimedia retrieval to bridge the semantic gap. In this paper we review the state-of-the-art techniques in semantic multimedia retrieval by discussing how relevant multimedia retrieval systems incorporate a semantic layer to improve the system performance. Some criticism is also expressed since the current systems lack in clustering to increase the recall and to support the reuse of multimedia material for developing new artefacts, thus envisaging novel research directions.
Proceedings of the 13th WSEAS international …, 2011
... [38] SI Park, SP Ponce, J. Huang, Y. Cao, F. Quek, Low-cost, high-speed computer vision usin... more ... [38] SI Park, SP Ponce, J. Huang, Y. Cao, F. Quek, Low-cost, high-speed computer vision using NVIDIA's CUDA architecture, 2008 37th IEEE Applied Imagery Pattern Recognition Workshop, Oct. ... [41] J. Gomez-Luna, JM González-Linares, JI Benavides, N. Guil ...
Title: Complex networks in geosciences: a global and a local scale cases study. Authors: Bonforte... more Title: Complex networks in geosciences: a global and a local scale cases study. Authors: Bonforte, Alessandro; Nunnari, Giuseppe; Puglisi, Giuseppe; di Salvo, Roberto; Spata, Alessandro. Affiliation: AA(Istituto Nazionale di Geofisica ...
Title: Complex networks in geosciences: a global and a local scale cases study. Authors: Bonforte... more Title: Complex networks in geosciences: a global and a local scale cases study. Authors: Bonforte, Alessandro; Nunnari, Giuseppe; Puglisi, Giuseppe; di Salvo, Roberto; Spata, Alessandro. Affiliation: AA(Istituto Nazionale di Geofisica ...
Il monitoraggio sistematico delle variazioni dell'inclinazione del suolo, viene effettuato s... more Il monitoraggio sistematico delle variazioni dell'inclinazione del suolo, viene effettuato sui vulcani siciliani dall'INGV-CT, utilizzando differenti tipi di sensori ad alta precisione capaci di rilevare inclinazioni del suolo fino a 10-8 radianti (Bonaccorso ed al., 2004). Le misure di tilt in continuo sui vulcani rappresentano un metodo rapido per l'individuazione di precursori di un'eruzione ed uno strumento di studio del comportamento dei vulcani stessi nelle fasi pre e post-eruttive.
In this thesis a set of novel video annotation methods for performance evaluation of object detec... more In this thesis a set of novel video annotation methods for performance evaluation of object detection, tracking and recognition applications is proposed. Large scale labeled datasets are of key importance for the development of automatic video analysis tools as they, from one hand, allow multi-class classifiers training and, from the other hand, support the algorithms’ evaluation phase. This is widely recognized by the multimedia and computer vision communities, as witnessed by the growing number of available datasets; however, the research still lacks in usable and effective annotation tools, since a lot of human effort is necessary to generate high quality ground truth data. However, it is not feasible to collect large video ground truths, covering as much scenarios and object categories as possible, by exploiting only the effort of isolated research groups. For these reasons in this thesis we first present a semi-automatic stand-alone tool for gathering ground truth data with the...
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013), 2013
ABSTRACT The growth of data produced by the medical and clinical community requires the introduct... more ABSTRACT The growth of data produced by the medical and clinical community requires the introduction of advanced techniques and resources in terms of computational and storage capabilities. The different problems and needs that afflict the information technologies for health support conduce to adoption of new infrastructure and application based on cloud computing. The different problems concerning to one side to the managerial, administrative and management aspects, to the other side concern who works as a physician or researcher, that needs the infrastructure to process, store, manage patient data, analysis, diagnosis, and so on. Today, cloud computing represents an important alternative to ensure high performance data processing and easy management of the complex tools in different area and in health. Cloud computing can solve many of these problems providing several advantages in terms of resource management and computational capabilities. In this paper a survey concerning the current models of health that are switching to solutions based on cloud computing, is proposed. Different applications and services are explored and concluded that the use of cloud computing and in particular of hybrid cloud solution can represent a significant opportunity to increase the development of the health sector in all its aspects.
Proceedings of the International Workshop on Video and Image Ground Truth in Computer Vision Applications - VIGTA '13, 2013
ABSTRACT In this paper we present an innovative approach to support efficient large scale video a... more ABSTRACT In this paper we present an innovative approach to support efficient large scale video annotation by exploiting the crowdsourcing. In particular, we collect big noisy annotations by an on-line Flash game which aims at taking photos of objects appearing through the game levels. The data gathered (suitably processed) from the game is then used to drive image segmentation approaches, namely the Region Growing and Grab Cut, which allow us to derive meaningful annotations. A comparison against hand-labeled ground truth data showed that the proposed approach constitutes a valid alternative to the existing video annotation approaches and allow a reliable and fast collection of large scale ground truth data for performance evaluation in computer vision.
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Papers by Roberto Di Salvo