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Thomas Seidl - One of the best experts on this subject based on the ideXlab platform.
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gradient based signatures for efficient similarity search in large scale Multimedia Databases
Conference on Information and Knowledge Management, 2015Co-Authors: Christian Beecks, Merih Seran Uysal, Judith Hermanns, Thomas SeidlAbstract:With the continuous rise of Multimedia, the question of how to access large-scale Multimedia Databases efficiently has become of crucial importance. Given a Multimedia database comprising millions of Multimedia objects, how to approximate the content-based properties of the corresponding feature representations in order to carry out similarity search efficiently and with high accuracy? In this paper, we propose the concept of gradient-based signatures in order to aggregate content-based features of Multimedia objects by means of generative models. We provide theoretical insights into our approach including closed-form expressions for the computation of gradient-based signatures with respect to Gaussian mixture models and additionally investigate different binarization methods for gradient-based signatures in order to query Databases comprising millions of Multimedia objects with high accuracy in less than one second.
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content based exploration of Multimedia Databases
Content-Based Multimedia Indexing, 2013Co-Authors: Christian Beecks, Merih Seran Uysal, Philip Driessen, Thomas SeidlAbstract:Usability, effectiveness, and efficiency are the fundamental properties of content-based Multimedia exploration systems. While the usability of an exploration system is frequently ensured by intuitive and interactive visual interfaces, the effectiveness of the retrieval results and the efficiency of the exploration process are typically obtained by high quality similarity models and fast query evaluation strategies. As it is immensely important to maintain all the aforementioned properties concurrently in order to meet individual user requirements, we present a modular content-based Multimedia exploration system facilitating the access and insight into large Multimedia Databases by incorporating state-of-the-art content-based methods and techniques. To this end, we first survey and analyze various techniques and then briefly introduce our modular content-based exploration system.
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efficient emd based similarity search in Multimedia Databases via flexible dimensionality reduction
International Conference on Management of Data, 2008Co-Authors: Marc Wichterich, Ira Assent, Philipp Kranen, Thomas SeidlAbstract:The Earth Mover's Distance (EMD) was developed in computer vision as a flexible similarity model that utilizes similarities in feature space to define a high quality similarity measure in feature representation space. It has been successfully adopted in a multitude of applications with low to medium dimensionality. However, Multimedia applications commonly exhibit high-dimensional feature representations for which the computational complexity of the EMD hinders its adoption. An efficient query processing approach that mitigates and overcomes this effect is crucial. We propose novel dimensionality reduction techniques for the EMD in a filter-and-refine architecture for efficient lossless retrieval. Thorough experimental evaluation on real world data sets demonstrates a substantial reduction of the number of expensive high-dimensional EMD computations and thus remarkably faster response times. Our techniques are fully flexible in the number of reduced dimensions, which is a novel feature in approximation techniques for the EMD.
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efficient similarity search using the earth mover s distance for large Multimedia Databases
International Conference on Data Engineering, 2008Co-Authors: Ira Assent, Marc Wichterich, Tobias Meisen, Thomas SeidlAbstract:Multimedia similarity search in large Databases requires efficient query processing. The Earth mover's distance, introduced in computer vision, is successfully used as a similarity model in a number of small-scale applications. Its computational complexity hindered its adoption in large Multimedia Databases. We enable directly indexing the Earth mover's distance in structures such as the R-tree and the VA-file by providing the accurate 'MinDist' function to any bounding rectangle in the index. We exploit the computational structure of the new MinDist to derive a new lower bound for the EMD MinDist which is assembled from quantized partial solutions yielding very fast query processing times. We prove completeness of our approach in a multistep scheme. Extensive experiments on real world data demonstrate the high efficiency.
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subspace outlier mining in large Multimedia Databases
Dagstuhl Seminar Proceedings, 2007Co-Authors: Ira Assent, Ralph Krieger, Emmanuel Muller, Thomas SeidlAbstract:Increasingly large Multimedia Databases in life sciences, e- commerce, or monitoring applications cannot be browsed manually, but require automatic knowledge discovery in Databases (KDD) techniques to detect novel and interesting patterns. Clustering, aims at grouping similar objects into clusters, separating dissimilar objects. Density-based clustering has been shown to detect arbitrarily shaped clusters even in noisy data bases. In high-dimensional data bases, meaningful clusters can no longer be detected due to the curse of dimensionality. Consequently, subspace clustering searches for clusters hidden in any subset of the set of dimensions. Clustering information is very useful for applications like fraud detection where outliers, i.e. objects which dier from all clusters, are searched. We propose a density-based subspace clustering model for outlier detection. We dene outliers with respect to maximal and non- redundant subspace clusters. We demonstrate the quality of our subspace clustering results in experiments on real world Databases and discuss our outlier model as well as future work.
Moncef Gabbouj - One of the best experts on this subject based on the ideXlab platform.
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A Directional Texture Descriptor via 2D Walking Ant Histogram
2015Co-Authors: Serkan Kiranyaz, Miguel Ferreira, Moncef GabboujAbstract:A novel texture descriptor, which can be extracted from the major object edges automatically and used for the content-based retrieval in Multimedia Databases, is presented. The proposed method is adopted from the 2D Walking Ant Histogram, which is in fact a generic shape descriptor recently developed for general purpose Multimedia Databases. 2D WAH shape descriptor is motivated from the imaginary scenario of a walking ant with a limited line of sight over the boundary of a particular object; eventually each sub-segment is traversed and the process keeps describing a certain line of sight, whether it is a continuous branch or a corner, using individual 2D histograms. In this paper we tuned this approach as an efficient texture descriptor, which achieves a superior performance especially for directional textures. Integrating the whole process as feature extraction module into MUVIS framework allows us to test the mutual performance of the proposed texture descriptor in the context of Multimedia indexing and retrieval
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Hierarchical Cellular Tree: An Efficient Indexing Scheme for Content-Based Retrieval on Multimedia Databases
IEEE Transactions on Multimedia, 2007Co-Authors: Serkan Kiranyaz, Moncef GabboujAbstract:One of the challenges in the development of a content-based Multimedia indexing and retrieval application is to achieve an efficient indexing scheme. The developers and users who are accustomed to making queries to retrieve a particular Multimedia item from a large scale database can be frustrated by the long query times. Conventional indexing structures cannot usually cope with the requirements of a Multimedia database, such as dynamic indexing or the presence of high-dimensional audiovisual features. Such structures do not scale well with the ever increasing size of Multimedia Databases whilst inducing corruption and resulting in an over-crowded indexing structure. This paper addresses such problems and presents a novel indexing technique, hierarchical cellular tree (HCT), which is designed to bring an effective solution especially for indexing large Multimedia Databases. Furthermore it provides an enhanced browsing capability, which enables user to make a guided tour within the database. A pre-emptive cell-search mechanism is introduced in order to prevent corruption, which may occur due to erroneous item insertions. Among the hierarchical levels that are built in a bottom-up fashion, similar items are collected into appropriate cellular structures at some level. Cells are subject to mitosis operations when the dissimilarity exceeds a required level. By mitosis operations, cells are kept focused and compact and yet, they can grow into any dimension as long as the compactness is maintained. The proposed indexing scheme is then used along with a recently introduced query method, the progressive query, in order to achieve the ultimate goal, from the user point of view that is retrieval of the most relevant items in the earliest possible time regardless of the database size. Experimental results show that the speed of retrievals is significantly improved and the indexing structure shows no sign of degradations when the database size is increased. Furthermore, HCT indexing body can conveniently be used for efficient browsing and navigation operations among the Multimedia database items
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hierarchical cellular tree an efficient indexing method for browsing and navigation in Multimedia Databases
European Signal Processing Conference, 2005Co-Authors: Serkan Kiranyaz, Moncef GabboujAbstract:One of the challenges in the development of content-based Multimedia retrieval application is to achieve an efficient browsing and navigation scheme. Since browsing requires the capability of handling the entire database, a particular visualization system and tool(s) for navigation should be provided. Otherwise, browsing may turn out to be a disorienting process. Database items should be organized and especially for large Databases the underlying organization scheme such as the indexing structure should provide a hierarchical representation of the database. This paper presents a novel browsing technique based on a new indexing scheme, the Hierarchical Cellular Tree, which is designed to bring an effective solution especially for indexing large-scale Multimedia Databases and furthermore to provide an enhanced browsing capability, which enables user to make a guided tour within the database. A pre-emptive cell search mechanism is introduced in order to prevent the corruption of large Multimedia item collections due to the limited discrimination obtained from visual and aural descriptors. In addition, similar items are focused within appropriate cellular structures, which will be subject to mitosis operations when the dissimilarity emerges as a result of irrelevant item insertions. Mitosis operations ensure to keep the cells in a focused and compact form and yet the cells can grow into any dimension as long as compactness prevails. Experimental results show that the HCT indexing body can conveniently be used for efficient browsing and navigation operations among the Multimedia database items.
Serkan Kiranyaz - One of the best experts on this subject based on the ideXlab platform.
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A Directional Texture Descriptor via 2D Walking Ant Histogram
2015Co-Authors: Serkan Kiranyaz, Miguel Ferreira, Moncef GabboujAbstract:A novel texture descriptor, which can be extracted from the major object edges automatically and used for the content-based retrieval in Multimedia Databases, is presented. The proposed method is adopted from the 2D Walking Ant Histogram, which is in fact a generic shape descriptor recently developed for general purpose Multimedia Databases. 2D WAH shape descriptor is motivated from the imaginary scenario of a walking ant with a limited line of sight over the boundary of a particular object; eventually each sub-segment is traversed and the process keeps describing a certain line of sight, whether it is a continuous branch or a corner, using individual 2D histograms. In this paper we tuned this approach as an efficient texture descriptor, which achieves a superior performance especially for directional textures. Integrating the whole process as feature extraction module into MUVIS framework allows us to test the mutual performance of the proposed texture descriptor in the context of Multimedia indexing and retrieval
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Hierarchical Cellular Tree: An Efficient Indexing Scheme for Content-Based Retrieval on Multimedia Databases
IEEE Transactions on Multimedia, 2007Co-Authors: Serkan Kiranyaz, Moncef GabboujAbstract:One of the challenges in the development of a content-based Multimedia indexing and retrieval application is to achieve an efficient indexing scheme. The developers and users who are accustomed to making queries to retrieve a particular Multimedia item from a large scale database can be frustrated by the long query times. Conventional indexing structures cannot usually cope with the requirements of a Multimedia database, such as dynamic indexing or the presence of high-dimensional audiovisual features. Such structures do not scale well with the ever increasing size of Multimedia Databases whilst inducing corruption and resulting in an over-crowded indexing structure. This paper addresses such problems and presents a novel indexing technique, hierarchical cellular tree (HCT), which is designed to bring an effective solution especially for indexing large Multimedia Databases. Furthermore it provides an enhanced browsing capability, which enables user to make a guided tour within the database. A pre-emptive cell-search mechanism is introduced in order to prevent corruption, which may occur due to erroneous item insertions. Among the hierarchical levels that are built in a bottom-up fashion, similar items are collected into appropriate cellular structures at some level. Cells are subject to mitosis operations when the dissimilarity exceeds a required level. By mitosis operations, cells are kept focused and compact and yet, they can grow into any dimension as long as the compactness is maintained. The proposed indexing scheme is then used along with a recently introduced query method, the progressive query, in order to achieve the ultimate goal, from the user point of view that is retrieval of the most relevant items in the earliest possible time regardless of the database size. Experimental results show that the speed of retrievals is significantly improved and the indexing structure shows no sign of degradations when the database size is increased. Furthermore, HCT indexing body can conveniently be used for efficient browsing and navigation operations among the Multimedia database items
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hierarchical cellular tree an efficient indexing method for browsing and navigation in Multimedia Databases
European Signal Processing Conference, 2005Co-Authors: Serkan Kiranyaz, Moncef GabboujAbstract:One of the challenges in the development of content-based Multimedia retrieval application is to achieve an efficient browsing and navigation scheme. Since browsing requires the capability of handling the entire database, a particular visualization system and tool(s) for navigation should be provided. Otherwise, browsing may turn out to be a disorienting process. Database items should be organized and especially for large Databases the underlying organization scheme such as the indexing structure should provide a hierarchical representation of the database. This paper presents a novel browsing technique based on a new indexing scheme, the Hierarchical Cellular Tree, which is designed to bring an effective solution especially for indexing large-scale Multimedia Databases and furthermore to provide an enhanced browsing capability, which enables user to make a guided tour within the database. A pre-emptive cell search mechanism is introduced in order to prevent the corruption of large Multimedia item collections due to the limited discrimination obtained from visual and aural descriptors. In addition, similar items are focused within appropriate cellular structures, which will be subject to mitosis operations when the dissimilarity emerges as a result of irrelevant item insertions. Mitosis operations ensure to keep the cells in a focused and compact form and yet the cells can grow into any dimension as long as compactness prevails. Experimental results show that the HCT indexing body can conveniently be used for efficient browsing and navigation operations among the Multimedia database items.
Ira Assent - One of the best experts on this subject based on the ideXlab platform.
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efficient emd based similarity search in Multimedia Databases via flexible dimensionality reduction
International Conference on Management of Data, 2008Co-Authors: Marc Wichterich, Ira Assent, Philipp Kranen, Thomas SeidlAbstract:The Earth Mover's Distance (EMD) was developed in computer vision as a flexible similarity model that utilizes similarities in feature space to define a high quality similarity measure in feature representation space. It has been successfully adopted in a multitude of applications with low to medium dimensionality. However, Multimedia applications commonly exhibit high-dimensional feature representations for which the computational complexity of the EMD hinders its adoption. An efficient query processing approach that mitigates and overcomes this effect is crucial. We propose novel dimensionality reduction techniques for the EMD in a filter-and-refine architecture for efficient lossless retrieval. Thorough experimental evaluation on real world data sets demonstrates a substantial reduction of the number of expensive high-dimensional EMD computations and thus remarkably faster response times. Our techniques are fully flexible in the number of reduced dimensions, which is a novel feature in approximation techniques for the EMD.
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efficient similarity search using the earth mover s distance for large Multimedia Databases
International Conference on Data Engineering, 2008Co-Authors: Ira Assent, Marc Wichterich, Tobias Meisen, Thomas SeidlAbstract:Multimedia similarity search in large Databases requires efficient query processing. The Earth mover's distance, introduced in computer vision, is successfully used as a similarity model in a number of small-scale applications. Its computational complexity hindered its adoption in large Multimedia Databases. We enable directly indexing the Earth mover's distance in structures such as the R-tree and the VA-file by providing the accurate 'MinDist' function to any bounding rectangle in the index. We exploit the computational structure of the new MinDist to derive a new lower bound for the EMD MinDist which is assembled from quantized partial solutions yielding very fast query processing times. We prove completeness of our approach in a multistep scheme. Extensive experiments on real world data demonstrate the high efficiency.
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subspace outlier mining in large Multimedia Databases
Dagstuhl Seminar Proceedings, 2007Co-Authors: Ira Assent, Ralph Krieger, Emmanuel Muller, Thomas SeidlAbstract:Increasingly large Multimedia Databases in life sciences, e- commerce, or monitoring applications cannot be browsed manually, but require automatic knowledge discovery in Databases (KDD) techniques to detect novel and interesting patterns. Clustering, aims at grouping similar objects into clusters, separating dissimilar objects. Density-based clustering has been shown to detect arbitrarily shaped clusters even in noisy data bases. In high-dimensional data bases, meaningful clusters can no longer be detected due to the curse of dimensionality. Consequently, subspace clustering searches for clusters hidden in any subset of the set of dimensions. Clustering information is very useful for applications like fraud detection where outliers, i.e. objects which dier from all clusters, are searched. We propose a density-based subspace clustering model for outlier detection. We dene outliers with respect to maximal and non- redundant subspace clusters. We demonstrate the quality of our subspace clustering results in experiments on real world Databases and discuss our outlier model as well as future work.
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approximation techniques for indexing the earth movers distance in Multimedia Databases
International Conference on Data Engineering, 2006Co-Authors: Ira Assent, A Wenning, Thomas SeidlAbstract:Todays abundance of storage coupled with digital technologies in virtually any scientific or commercial application such as medical and biological imaging or music archives deal with tremendous quantities of images, videos or audio files stored in large Multimedia Databases. For content-based data mining and retrieval purposes suitable similarity models are crucial. The Earth Movers Distance was introduced in Computer Vision to better approach human perceptual similarities. Its computation, however, is too complex for usage in interactive Multimedia database scenarios. In order to enable efficient query processing in large Databases, we propose an index-supported multistep algorithm. We therefore develop new lower bounding approximation techniques for the Earth Movers Distance which satisfy high quality criteria including completeness (no false drops), index-suitability and fast computation. We demonstrate the efficiency of our approach in extensive experiments on large image Databases
Lisbeth Rodriguez - One of the best experts on this subject based on the ideXlab platform.
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dymond an active system for dynamic vertical partitioning of Multimedia Databases
International Database Engineering and Applications Symposium, 2012Co-Authors: Lisbeth Rodriguez, Jair Cervantes, Farid GarcialamontAbstract:In recent years, vertical partitioning techniques have been employed in Multimedia Databases to achieve efficient retrieval of Multimedia objects. These techniques are static because the input to the partitioning process, which includes queries accessing database and their frequency as well as the database schema, is obtained from an earlier analysis stage. This implies that when the system undergoes sufficient changes, a new analysis stage is carried out to re-run the partitioning process. Multimedia Databases are accessed by many users simultaneously, therefore queries and their frequency tend to quickly change over time. In this context, dynamic vertical partitioning can significantly improve performance. In this paper we present an active system called DYMOND (DYnamic Multimedia ON line Distribution), which performs a dynamic vertical partitioning in Multimedia Databases to improve query performance. Experimental results on benchmark Multimedia Databases clarify the validness of our system.
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a vertical partitioning algorithm for distributed Multimedia Databases
Database and Expert Systems Applications, 2011Co-Authors: Lisbeth RodriguezAbstract:Efficient retrieval of Multimedia objects is a key factor for the success of distributed Multimedia Databases. One way to provide faster access to Multimedia objects in these Databases is using vertical partitioning. In this paper, we present a vertical partitioning algorithm for distributed Multimedia Databases (MAVP) that takes into account the size of the Multimedia objects in order to generate an optimal vertical partitioning scheme. The objective function of MAVP minimizes the amount of access to irrelevant data and the transportation cost of the queries in distributed Multimedia Databases to achieve efficient retrieval of Multimedia objects. A cost model for evaluating vertical partitioning schemes in distributed Multimedia Databases is developed. Experimental results clarify the validness of the proposed algorithm.