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Author = Adamek, Tomasz;
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Displaying Results 1 - 23 of 23 on page 1 of 1
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A framework and user interface for automatic region based segmentation algorithms
(2006)
McGuinness, Kevin; Keenan, Gordon; Adamek, Tomasz; O'Connor, Noel E.
A framework and user interface for automatic region based segmentation algorithms
(2006)
McGuinness, Kevin; Keenan, Gordon; Adamek, Tomasz; O'Connor, Noel E.
Abstract:
In this paper we describe a framework and tool developed for running and evaluating automatic region based segmentation algorithms. The tool was designed to allow simple integration of existing and future segmentation algorithms, both single image based algorithms and those that operate on video data. Our framework supports plug-in segmenters, media decoders, and region-map codecs. We provide several sophisticated implementations of these plug-ins, including a video decoder capable of frame accurate decoding of a large variety of video formats, an image decoder which also handles a comprehensive collection of formats, and a efficient implementation of a region-map codec. The tool includes both a graphical user interface to allow users to browse, visually inspect, and evaluate the algorithm output, and a batch processing interface for segmentation of large data collections. The application allows researchers to focus more on the development and evaluation of segmentation methods, rel...
http://doras.dcu.ie/310/
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A multiscale representation method for nonrigid shapes with a single closed contour
(2004)
Adamek, Tomasz; O'Connor, Noel E.
A multiscale representation method for nonrigid shapes with a single closed contour
(2004)
Adamek, Tomasz; O'Connor, Noel E.
Abstract:
In this paper, we discuss the criteria that should be satisfied by a descriptor for nonrigid shapes with a single closed contour. We then propose a shape representation method that fulfills these criteria. In the proposed approach, contour convexities and concavities at different scale levels are represented using a two-dimensional (2-D) matrix. The representation can be visualized as a 2-D surface, where "hills" and "valleys" represent contour convexities and concavities, respectively. The optimal matching of two shape representations is achieved using dynamic programming and a dissimilarity measure is defined based on this matching. The proposed algorithm is very efficient and invariant to several kinds of transformations including some articulations and modest occlusions. The retrieval performance of the approach is illustrated using the MPEG-7 shape database, which is one of the most complete shape databases currently available. Our experiments indicate that ...
http://doras.dcu.ie/255/
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An integrated approach for object shape registration and modeling
(2005)
Adamek, Tomasz; O'Connor, Noel E.; Jones, Gareth J.F.; Murphy, Noel
An integrated approach for object shape registration and modeling
(2005)
Adamek, Tomasz; O'Connor, Noel E.; Jones, Gareth J.F.; Murphy, Noel
Abstract:
In this paper, an integrated approach to fast and efficient construction of statistical shape models is proposed that is a potentially useful tool in Information Retrieval(IR). The tool allows intuitive extraction of accurate contour examples from a set of images using a semi-automatic segmentation approach. The user is allowed to draw on the scene by simply dragging a mouse over the image and creating a set of labelled scribbles for the objects to be segmented. An automatic segmentation algorithm uses the scribbles to partition the scene and extract objects’ contour. A set of labelled points (landmarks) is identified automatically on the set of examples thereby allowing statistical modeling of the objects’ shape. The main contribution of this paper is the new approach to automatic landmark identification eliminating the burden of manual landmarking. The approach utilizes a robust method for pairwise correspondence proposed originally in [1, 2]. The landmarks are used to train stati...
http://doras.dcu.ie/384/
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Coherent segmentation of video into syntactic regions
(2005)
Smeaton, Alan F.; Adamek, Tomasz; Le Borgne, Hervé; Smyth, Oliver; O'Connor, Noel ...
Coherent segmentation of video into syntactic regions
(2005)
Smeaton, Alan F.; Adamek, Tomasz; Le Borgne, Hervé; Smyth, Oliver; O'Connor, Noel E.; de Burca, Seán
Abstract:
In this paper we report on our work in realising an approach to video shot matching which involves automatically segmenting video into abstract intertwinded shapes in such a way that there is temporal coherency. These shapes representing approximations of objects and background regions can then be matched giving fine-grained shot-shot matching. The main contributions of the paper are firstly the extension of our segmentation algorithm for still images to spatial segmentation in video, and secondly the introduction a measurement of temporal coherency of the spatial segmentation. This latter allows us to quantitatively demonstrate the effectiveness of our approach on real video data.
http://doras.dcu.ie/316/
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DCU and UTA at ImageCLEFPhoto 2007
(2007)
Järvelin, Anni; Wilkins, Peter; Adamek, Tomasz; Airio, Eija; Jones, Gareth J.F.
DCU and UTA at ImageCLEFPhoto 2007
(2007)
Järvelin, Anni; Wilkins, Peter; Adamek, Tomasz; Airio, Eija; Jones, Gareth J.F.
Abstract:
Dublin City University (DCU) and University of Tampere(UTA) participated in the ImageCLEF 2007 photographic ad-hoc retrieval task with several monolingual and bilingual runs. Our approach was language independent: text retrieval based on fuzzy s-gram query translation was combined with visual retrieval. Data fusion between text and image content was performed using unsupervised query-time weight generation approaches. Our baseline was a combination of dictionary-based query translation and visual retrieval, which achieved the best result. The best mixed modality runs using fuzzy s-gram translation achieved on average around 83% of the performance of the baseline. Performance was more similar when only top rank precision levels of P10 and P20 were considered. This suggests that fuzzy sgram query translation combined with visual retrieval is a cheap alternative for cross-lingual image retrieval where only a small number of relevant items are required. Both sets of results emphasize th...
http://doras.dcu.ie/16193/
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Efficient contour-based shape representation and matching
(2003)
Adamek, Tomasz
Efficient contour-based shape representation and matching
(2003)
Adamek, Tomasz
Abstract:
This paper presents an efficient method for calculating the similarity between 2D closed shape contours. The proposed algorithm is invariant to translation, scale change and rotation. It can be used for database retrieval or for detecting regions with a particular shape in video sequences. The proposed algorithm is suitable for real-time applications. In the first stage of the algorithm, an ordered sequence of contour points approximating the shapes is extracted from the input binary images. The contours are translation and scale-size normalized, and small sets of the most likely starting points for both shapes are extracted. In the second stage, the starting points from both shapes are assigned into pairs and rotation alignment is performed. The dissimilarity measure is based on the geometrical distances between corresponding contour points. A fast sub-optimal method for solving the correspondence problem between contour points from two shapes is proposed. The dissimilarity measure...
http://doras.dcu.ie/396/
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Image segmentation evaluation using an integrated framework
(2007)
McGuinness, Kevin; Keenan, Gordon; Adamek, Tomasz; O'Connor, Noel E.
Image segmentation evaluation using an integrated framework
(2007)
McGuinness, Kevin; Keenan, Gordon; Adamek, Tomasz; O'Connor, Noel E.
Abstract:
In this paper we present a general framework we have developed for running and evaluating automatic image and video segmentation algorithms. This framework was designed to allow effortless integration of existing and forthcoming image segmentation algorithms, and allows researchers to focus more on the development and evaluation of segmentation methods, relying on the framework for encoding/decoding and visualization. We then utilize this framework to automatically evaluate four distinct segmentation algorithms, and present and discuss the results and statistical findings of the experiment.
http://doras.dcu.ie/270/
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Inexpensive fusion methods for enhancing feature detection
(2007)
Wilkins, Peter; Adamek, Tomasz; O'Connor, Noel E.; Smeaton, Alan F.
Inexpensive fusion methods for enhancing feature detection
(2007)
Wilkins, Peter; Adamek, Tomasz; O'Connor, Noel E.; Smeaton, Alan F.
Abstract:
Recent successful approaches to high-level feature detection in image and video data have treated the problem as a pattern classification task. These typically leverage the techniques learned from statistical machine learning, coupled with ensemble architectures that create multiple feature detection models. Once created, co-occurrence between learned features can be captured to further boost performance. At multiple stages throughout these frameworks, various pieces of evidence can be fused together in order to boost performance. These approaches whilst very successful are computationally expensive, and depending on the task, require the use of significant computational resources. In this paper we propose two fusion methods that aim to combine the output of an initial basic statistical machine learning approach with a lower-quality information source, in order to gain diversity in the classified results whilst requiring only modest computing resources. Our approaches, validated exp...
http://doras.dcu.ie/209/
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Interactive object contour extraction for shape modeling
(2006)
Adamek, Tomasz; O'Connor, Noel E.
Interactive object contour extraction for shape modeling
(2006)
Adamek, Tomasz; O'Connor, Noel E.
Abstract:
In this paper we present a semi-automatic segmentation approach suitable for extracting object contours as a precursor to 2D shape modeling. The approach is a modified and extended version of an existing state-of-the-art approach based on the concept of a Binary Partition Tree (BPT) [1]. The resulting segmentation tool facilitates quick and easy extraction of an object’s contour via a small amount of user interaction that is easy to perform, even in complicated scenes. Illustrative segmentation results are presented and the usefulness of the approach in generating object shape models is discussed.
http://doras.dcu.ie/388/
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K-Space at TRECVid 2006
(2006)
Wilkins, Peter; Adamek, Tomasz; Ferguson, Paul; Hughes, Mark; Jones, Gareth J.F.; Keena...
K-Space at TRECVid 2006
(2006)
Wilkins, Peter; Adamek, Tomasz; Ferguson, Paul; Hughes, Mark; Jones, Gareth J.F.; Keenan, Gordon; McGuinness, Kevin; Malobabić, Jovanka; O'Connor, Noel E.; Sadlier, David A.; Smeaton, Alan F.
Abstract:
In this paper we describe the K-Space participation in TRECVid 2006. K-Space participated in two tasks, high-level feature extraction and search. We present our approaches for each of these activities and provide a brief analysis of our results. Our high-level feature submission made use of support vector machines (SVMs) created with low-level MPEG-7 visual features, fused with specific concept detectors. Search submissions were both manual and automatic and made use of both low- and high-level features. In the high-level feature extraction submission, four of our six runs achieved performance above the TRECVid median, whilst our search submission performed around the median. The K-Space team consisted of eight partner institutions from the EU-funded K-Space Network, and our submissions made use of tools and techniques from each partner. As such this paper will provide overviews of each partner’s contributions and provide appropriate references for specific descriptions of individua...
http://doras.dcu.ie/429/
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K-Space at TRECVid 2007
(2007)
Wilkins, Peter; Adamek, Tomasz; Byrne, Daragh; Jones, Gareth J.F.; Lee, Hyowon; Keenan,...
K-Space at TRECVid 2007
(2007)
Wilkins, Peter; Adamek, Tomasz; Byrne, Daragh; Jones, Gareth J.F.; Lee, Hyowon; Keenan, Gordon; McGuinness, Kevin; O'Connor, Noel E.; Smeaton, Alan F.
Abstract:
In this paper we describe K-Space participation in TRECVid 2007. K-Space participated in two tasks, high-level feature extraction and interactive search. We present our approaches for each of these activities and provide a brief analysis of our results. Our high-level feature submission utilized multi-modal low-level features which included visual, audio and temporal elements. Specific concept detectors (such as Face detectors) developed by K-Space partners were also used. We experimented with different machine learning approaches including logistic regression and support vector machines (SVM). Finally we also experimented with both early and late fusion for feature combination. This year we also participated in interactive search, submitting 6 runs. We developed two interfaces which both utilized the same retrieval functionality. Our objective was to measure the effect of context, which was supported to different degrees in each interface, on user performance. The first of the two ...
http://doras.dcu.ie/432/
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K-Space at TRECVid 2008
(2008)
Wilkins, Peter; Byrne, Daragh; Jones, Gareth J.F.; Lee, Hyowon; Keenan, Gordon; McGuinn...
K-Space at TRECVid 2008
(2008)
Wilkins, Peter; Byrne, Daragh; Jones, Gareth J.F.; Lee, Hyowon; Keenan, Gordon; McGuinness, Kevin; O'Connor, Noel E.; O'Hare, Neil; Smeaton, Alan F.; Adamek, Tomasz
Abstract:
In this paper we describe K-Space’s participation in TRECVid 2008 in the interactive search task. For 2008 the K-Space group performed one of the largest interactive video information retrieval experiments conducted in a laboratory setting. We had three institutions participating in a multi-site multi-system experiment. In total 36 users participated, 12 each from Dublin City University (DCU, Ireland), University of Glasgow (GU, Scotland) and Centrum Wiskunde & Informatica (CWI, the Netherlands). Three user interfaces were developed, two from DCU which were also used in 2007 as well as an interface from GU. All interfaces leveraged the same search service. Using a latin squares arrangement, each user conducted 12 topics, leading in total to 6 runs per site, 18 in total. We officially submitted for evaluation 3 of these runs to NIST with an additional expert run using a 4th system. Our submitted runs performed around the median. In this paper we will present an overview of the se...
http://doras.dcu.ie/2104/
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Multi-view 3D retrieval using silhouette intersection and multi-scale contour representation
(2007)
Napoléon, Thibault; Adamek, Tomasz; Schmitt, Francis; O'Connor, Noel E.
Multi-view 3D retrieval using silhouette intersection and multi-scale contour representation
(2007)
Napoléon, Thibault; Adamek, Tomasz; Schmitt, Francis; O'Connor, Noel E.
Abstract:
We describe in this paper two methods for 3D shape indexing and retrieval that we apply on two data collections of the SHREC - SHape Retrieval Contest 2007: Watertight models and 3D CAD models. Both methods are based on a set of 2D multi-views after a pose and scale normalization of the models using PCA and the enclosing sphere. In all views we extract the models silhouettes and compare them pairwise. In the first method the similitude measure is obtained by integrating on the pairs of views the difference between the areas of the silhouettes union and the silhouettes intersection. In the second method we consider the external contour of the silhouettes, extract their convexities and concavities at different scale levels and build a multiscale representation. The pairs of contours are then compared by elastic matching achieved by using dynamic programming. Comparisons of the two methods are shown with their respective strengths and weaknesses.
http://doras.dcu.ie/271/
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QIMERA: a software platform for video object segmentation and tracking
(2003)
O'Connor, Noel E.; Adamek, Tomasz; Sav, Sorin Vasile; Murphy, Noel; Marlow, Seán
QIMERA: a software platform for video object segmentation and tracking
(2003)
O'Connor, Noel E.; Adamek, Tomasz; Sav, Sorin Vasile; Murphy, Noel; Marlow, Seán
Abstract:
In this paper we present an overview of an ongoing collaborative project in the field of video object segmentation and tracking. The objective of the project is to develop a flexible modular software architecture that can be used as test-bed for segmentation algorithms. The background to the project is described, as is the first version of the software system itself. Some sample results for the first segmentation algorithm developed using the system are presented and directions for future work are discussed.
http://doras.dcu.ie/418/
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Region and object segmentation algorithms in the Qimera segmentation platform
(2003)
O'Connor, Noel E.; Sav, Sorin Vasile; Adamek, Tomasz; Mezaris, Vasileios; Kompatsi...
Region and object segmentation algorithms in the Qimera segmentation platform
(2003)
O'Connor, Noel E.; Sav, Sorin Vasile; Adamek, Tomasz; Mezaris, Vasileios; Kompatsiaris, Ioannis; Lui, Tsz Ying; Izquierdo, Ebroul; Bennström, Christian Ferran; Casas, Josep R.
Abstract:
In this paper we present the Qimera segmentation platform and describe the different approaches to segmentation that have been implemented in the system to date. Analysis techniques have been implemented for both region-based and object-based segmentation. The region-based segmentation algorithms include: a colour segmentation algorithm based on a modified Recursive Shortest Spanning Tree (RSST) approach, an implementation of a colour image segmentation algorithm based on the K-Means-with-Connectivity-Constraint (KMCC) algorithm and an approach based on the Expectation Maximization (EM) algorithm applied in a 6D colour/texture space. A semi-automatic approach to object segmentation that uses the modified RSST approach is outlined. An automatic object segmentation approach via snake propagation within a level-set framework is also described. Illustrative segmentation results are presented in all cases. Plans for future research within the Qimera project are also discussed.
http://doras.dcu.ie/389/
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Region-based segmentation of images using syntactic visual features
(2005)
Adamek, Tomasz; O'Connor, Noel E.; Murphy, Noel
Region-based segmentation of images using syntactic visual features
(2005)
Adamek, Tomasz; O'Connor, Noel E.; Murphy, Noel
Abstract:
This paper presents a robust and efficient method for segmentation of images into large regions that reflect the real world objects present in the scene. We propose an extension to the well known Recursive Shortest Spanning Tree (RSST) algorithm based on a new color model and so-called syntactic features [1]. We introduce practical solutions, integrated within the RSST framework, to structure analysis based on the shape and spatial configuration of image regions. We demonstrate that syntactic features provide a reliable basis for region merging criteria which prevent formation of regions spanning more than one semantic object, thereby significantly improving the perceptual quality of the output segmentation. Experiments indicate that the proposed features are generic in nature and allow satisfactory segmentation of real world images from various sources without adjustment to algorithm parameters.
http://doras.dcu.ie/453/
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Stopping region-based image segmentation at meaningful partitions
(2007)
Adamek, Tomasz; O'Connor, Noel E.
Stopping region-based image segmentation at meaningful partitions
(2007)
Adamek, Tomasz; O'Connor, Noel E.
Abstract:
This paper proposes a new stopping criterion for automatic image segmentation based on region merging. The criterion is dependent on image content itself and when combined with the recently proposed approaches to syntactic segmentation can produce results aligned with the most salient semantic regions/objects present in the scene across heterogeneous image collections. The method identifies a single iteration from the merging process as the stopping point, based on the evolution of an accumulated merging cost during the complete merging process. The approach is compared to three commonly used stopping criteria: (i) required number of regions, (ii) value of the least link cost, and (iii) Peak Signal to Noise Ratio (PSNR). For comparison, the stopping criterion is also evaluated for a segmentation approach that does not use syntactic extensions. All experiments use a manually generated segmentation ground truth and spatial accuracy measures. Results show that the proposed stopping cri...
http://doras.dcu.ie/451/
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The aceToolbox: low-level audiovisual feature extraction for retrieval and classification
(2005)
O'Connor, Noel E.; Cooke, Eddie; Le Borgne, Hervé; Blighe, Michael; Adamek, Tomasz
The aceToolbox: low-level audiovisual feature extraction for retrieval and classification
(2005)
O'Connor, Noel E.; Cooke, Eddie; Le Borgne, Hervé; Blighe, Michael; Adamek, Tomasz
Abstract:
In this paper we present an overview of a software platform that has been developed within the aceMedia project, termed the aceToolbox, that provides global and local lowlevel feature extraction from audio-visual content. The toolbox is based on the MPEG-7 eXperimental Model (XM), with extensions to provide descriptor extraction from arbitrarily shaped image segments, thereby supporting local descriptors reflecting real image content. We describe the architecture of the toolbox as well as providing an overview of the descriptors supported to date. We also briefly describe the segmentation algorithm provided. We then demonstrate the usefulness of the toolbox in the context of two different content processing scenarios: similarity-based retrieval in large collections and scene-level classification of still images.
http://doras.dcu.ie/392/
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TRECVid 2006 experiments at Dublin City University
(2006)
Koskela, Markus; Wilkins, Peter; Adamek, Tomasz; Smeaton, Alan F.; O'Connor, Noel E.
TRECVid 2006 experiments at Dublin City University
(2006)
Koskela, Markus; Wilkins, Peter; Adamek, Tomasz; Smeaton, Alan F.; O'Connor, Noel E.
Abstract:
In this paper we describe our retrieval system and experiments performed for the automatic search task in TRECVid 2006. We submitted the following six automatic runs: • F A 1 DCU-Base 6: Baseline run using only ASR/MT text features. • F A 2 DCU-TextVisual 2: Run using text and visual features. • F A 2 DCU-TextVisMotion 5: Run using text, visual, and motion features. • F B 2 DCU-Visual-LSCOM 3: Text and visual features combined with concept detectors. • F B 2 DCU-LSCOM-Filters 4: Text, visual, and motion features with concept detectors. • F B 2 DCU-LSCOM-2 1: Text, visual, motion, and concept detectors with negative concepts. The experiments were designed both to study the addition of motion features and separately constructed models for semantic concepts, to runs using only textual and visual features, as well as to establish a baseline for the manually-assisted search runs performed within the collaborative K-Space project and described in the corresponding TRECVid 2006 notebook pa...
http://doras.dcu.ie/428/
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TRECVid 2007 experiments at Dublin City University
(2007)
Wilkins, Peter; Adamek, Tomasz; Jones, Gareth J.F.; O'Connor, Noel E.; Smeaton, Al...
TRECVid 2007 experiments at Dublin City University
(2007)
Wilkins, Peter; Adamek, Tomasz; Jones, Gareth J.F.; O'Connor, Noel E.; Smeaton, Alan F.
Abstract:
In this paper we describe our retrieval system and experiments performed for the automatic search task in TRECVid 2007. We submitted the following six automatic runs: • F A 1 DCU-TextOnly6: Baseline run using only ASR/MT text features. • F A 1 DCU-ImgBaseline4: Baseline visual expert only run, no ASR/MT used. Made use of query-time generation of retrieval expert coefficients for fusion. • F A 2 DCU-ImgOnlyEnt5: Automatic generation of retrieval expert coefficients for fusion at index time. • F A 2 DCU-imgOnlyEntHigh3: Combination of coefficient generation which combined the coefficients generated by the query-time approach, and the index-time approach, with greater weight given to the index-time coefficient. • F A 2 DCU-imgOnlyEntAuto2: As above, except that greater weight is given to the query-time coefficient that was generated. • F A 2 DCU-autoMixed1: Query-time expert coefficient generation that used both visual and text experts.
http://doras.dcu.ie/431/
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Using contour information and segmentation for object registration, modeling and retrieval
(2006)
Adamek, Tomasz
Using contour information and segmentation for object registration, modeling and retrieval
(2006)
Adamek, Tomasz
Abstract:
This thesis considers different aspects of the utilization of contour information and syntactic and semantic image segmentation for object registration, modeling and retrieval in the context of content-based indexing and retrieval in large collections of images. Target applications include retrieval in collections of closed silhouettes, holistic w ord recognition in handwritten historical manuscripts and shape registration. Also, the thesis explores the feasibility of contour-based syntactic features for improving the correspondence of the output of bottom-up segmentation to semantic objects present in the scene and discusses the feasibility of different strategies for image analysis utilizing contour information, e.g. segmentation driven by visual features versus segmentation driven by shape models or semi-automatic in selected application scenarios. There are three contributions in this thesis. The first contribution considers structure analysis based on the shape and spatial con...
http://doras.dcu.ie/17431/
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Using dempster-shafer theory to fuse multiple information sources in region-based segmentation
(2007)
Adamek, Tomasz; O'Connor, Noel E.
Using dempster-shafer theory to fuse multiple information sources in region-based segmentation
(2007)
Adamek, Tomasz; O'Connor, Noel E.
Abstract:
This paper presents a new method for segmentation of images into large regions that reflect the real world objects present in a scene. It explores the feasibility of utilizing spatial configuration of regions and their geometric properties (the so-called Syntactic Visual Features [1]) for improving the correspondence of segmentation results produced by the well-known Recursive Shortest Spanning Tree (RSST) algorithm [2] to semantic objects present in the scene. The main contribution of this paper is a novel framework for integration of evidence from multiple sources with the region merging process based on the Dempster-Shafer (DS) theory [3] that allows integration of sources providing evidence with different accuracy and reliability. Extensive experiments indicate that the proposed solution limits formation of regions spanning more than one semantic object.
http://doras.dcu.ie/217/
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Word matching using single closed contours for indexing handwritten historical documents
(2007)
Adamek, Tomasz; O'Connor, Noel E.; Murphy, Noel; Smeaton, Alan F.
Word matching using single closed contours for indexing handwritten historical documents
(2007)
Adamek, Tomasz; O'Connor, Noel E.; Murphy, Noel; Smeaton, Alan F.
Abstract:
Effective indexing is crucial for providing convenient access to scanned versions of large collections of historically valuable handwritten manuscripts. Since traditional handwriting recognizers based on optical character recognition (OCR) do not perform well on historical documents, recently a holistic word recognition approach has gained in popularity as an attractive and more straightforward solution (Lavrenko et al. in proc. document Image Analysis for Libraries (DIAL’04), pp. 278–287, 2004). Such techniques attempt to recognize words based on scalar and profile-based features extracted from whole word images. In this paper, we propose a new approach to holistic word recognition for historical handwritten manuscripts based on matching word contours instead of whole images or word profiles. The new method consists of robust extraction of closed word contours and the application of an elastic contour matching technique proposed originally for general shapes (Adamek and O’Connor in...
http://doras.dcu.ie/450/
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