Georgios Tziritas

Georgios Tziritas
University of Crete | UOC · Department of Computer Science

PhD

About

148
Publications
20,019
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
5,842
Citations

Publications

Publications (148)
Article
Full-text available
Automatic quantification of the left ventricle (LV) from cardiac magnetic resonance (CMR) images plays an important role in making the diagnosis procedure efficient, reliable, and alleviating the laborious reading work for physicians. Considerable efforts have been devoted to LV quantification using different strategies that include segmentation-ba...
Article
Semantic segmentation of cardiac MR images is a challenging task due to its importance in medical assessment of heart diseases. Having a detailed localization of specific regions of interest such as Right and Left Ventricular Cavities and Myocardium, doctors can infer important information about the presence of cardiovascular diseases, which are to...
Conference Paper
Full-text available
We present a fully-automatic fast method for heart segmentation in pediatric cardiac MRI. The segmentation algorithm is a two step process. In the first step a 3-D Markov random field (MRF) model is assumed for labeling the MR images into four intensity classes, the two of them corresponding to the blood pool areas. The intensity distribution of th...
Article
Full-text available
We present in this article a new method on unsupervised semantic parsing and structure recognition in peri-urban areas using satellite images. The automatic “building” and “road” detection is based on regions extracted by an unsupervised segmentation method. We propose a novel segmentation algorithm based on a Markov random field model and we give...
Article
Full-text available
In this paper, we propose a solution on microaggregation problem based on the hierarchical tree equi-partition (HTEP) algorithm. Microaggregation is a family of methods for statistical disclosure control of microdata, that is, for masking microdata, so that they can be released without disclose private information on the underlying individuals. Kno...
Article
Full-text available
In this paper, we propose a framework for interactive image segmentation. The goal of interactive image segmentation is to classify the image pixels into foreground and background classes, when some foreground and background markers are given. The proposed method minimizes a min–max Bayesian criterion that has been successfully used on image segmen...
Conference Paper
Full-text available
We propose a method for interactive image segmentation. We construct a weighted graph that represents the superpixels and the connections between them. An efficient algorithm for graph clustering based on synthetic coordinates is used yielding an initial map of classified pixels. The proposed method minimizes a min-max Bayesian criterion that has b...
Article
Full-text available
In this paper, we propose an efficient clustering algorithm that has been applied to the microaggregation problem. The goal is to partition $(N)$ given records into clusters, each of them grouping at least $(K)$ records, so that the sum of the within-partition squared error (SSE) is minimized. We propose a successive Group Selection algorithm that...
Article
Full-text available
This paper describes a semi-automatic method for moving object segmentation and tracking. This method is suitable when a few objects have to be tracked, while the camera moves and fixates on them. The user delineates approximately the initial locations in a selected frame and specifies the depth ordering of the objects to be tracked. First, motion-...
Article
Full-text available
We propose a general purpose image segmentation framework, which involves feature extraction and classification in feature space, followed by flooding and merging in spatial domain. Region growing is based on the computed local measurements and distances from the distribution of features describing the different classes. Using the properties of the...
Article
Full-text available
This paper introduces a new rigorous theoretical framework to address discrete MRF-based optimization in computer vision. Such a framework exploits the powerful technique of Dual Decomposition. It is based on a projected subgradient scheme that attempts to solve an MRF optimization problem by first decomposing it into a set of appropriately chosen...
Conference Paper
Full-text available
We propose a method for interactive colour image segmentation. The goal is to detect an object from the background, when some markers on object(s) and the background are given. As features only probability distributions of the data are used. At first, all the labelled seeds are independently propagated for obtaining homogeneous connected components...
Conference Paper
Full-text available
We propose a general framework for simultaneous segmentation and modelling of signals based on an Equipartition Principle (EP). According to EP, the signal is divided into segments with equal reconstruction errors by selecting the most suitable model to describe each segment. In addition, taking into account change detection on signal model an effi...
Article
Full-text available
The purpose of this study was to develop and evaluate a semiautomatic method for left ventricular (LV) segmentation on cine MR images and subsequent estimation of cardiac parameters. The study group comprised cardiac MR examinations of 18 consecutive patients with known or suspected coronary artery disease. The new method allowed the automatic dete...
Article
Full-text available
In the context of several pathologies, the presence of lymphocytes has been correlated with disease outcome. The ability to automatically detect lymphocyte nuclei on histopathology imagery could potentially result in the development of an image based prognostic tool. In this paper we present a method based on the estimation of a mixture of Gaussian...
Conference Paper
In this paper we introduce a novel approach to single view reconstruction using shape grammars. Our approach consists in modeling architectural styles using a set of basic shapes and a set of parametric rules, corresponding to increasing levels of detail. This approach is able to model elaborate and varying architectural styles, using a tree repres...
Conference Paper
Full-text available
In this paper, we propose a method for time interval segmentation of signals based on an equipartition principle (EP). According to EP, the signal is segmented into segments that give equal errors in reconstruction selecting the most suitable model to describe each segment. Moreover, the segments are equivalent in the content domain, since the sign...
Article
Full-text available
In this paper we analyze the problem of partitioning a continuous curve into n parts with equal successive chords, the curve EquiPartition problem (EP). The goal is to locate n − 1 consecutive curve points, so that the curve can be divided into n segments with equal chords under a distance function. We adopt a level set approach to prove that for a...
Article
Full-text available
We present a key frames selection algorithm based on three iso-content principles (iso-content distance, iso-content error and iso-content distortion), so that the selected key frames are equidistant in video content according to the used principle. Two automatic approaches for defining the most appropriate number of key frames are proposed by expl...
Conference Paper
A new message-passing scheme for MRF optimization is proposed in this paper. This scheme inherits better theoretical properties than all other state-of-the-art mes-sage passing methods and in practice performs equally well/outperforms them. It is based on the very powerful technique of Dual Decomposition [1] and leads to an el-egant and general fra...
Article
Full-text available
Our system can be extended to handle multiple stereoscopic views (and therefore multiple local models) per key position of the path (related by a camera rotation). In this case, one local 3D panorama (per key position) is constructed, comprising all local 3D models therein, and so a ‘morphable 3D panorama’ is now used during the rendering process....
Conference Paper
Full-text available
In this paper we propose a novel approach to define task-driven regularization constraints in deformable image registration using learned deformation priors. Our method consists of representing deformation through a set of control points and an interpolation strategy. Then, using a training set of images and the corresponding deformations we seek f...
Article
Full-text available
We present an automatic human shape-motion analysis method based on a fusion architecture for human action and activity recognition in athletic videos. Robust shape and motion features are extracted from human detection and tracking. The features are combined within the Transferable Belief Model (TBM) framework for two levels of recognition. The TB...
Article
In this paper we introduce a novel method to address minimization of static and dynamic MRFs. Our approach is based on principles from linear programming and, in particular, on primal-dual strategies. It generalizes prior state-of-the-art methods such as α-expansion, while it can also be used for efficiently minimizing NP-hard problems with complex...
Article
Full-text available
We present a shape based method for automatic people detection and counting without any assumption or nowledge of camera motion. The proposed method is applied to athletic videos in order to classify them to videos of individual and team sports. Moreover, in the case of team (multi-agent) sport, we propose a shape deformations based method for runn...
Article
Full-text available
In this paper, we present a new and more general version of polygonal approximation problem (GPA). Given an N−vertex polygonal curve P in the n-dimensional space ℜn, we approximate P by finding another M−vertex polygonal curve ˙ P, such that the vertices of P ˙ are an ordered subsequence of the curve points along P. The definition of the classical...
Conference Paper
Full-text available
In this paper, we propose a novel dynamic discrete framework to address image morphing with application to optical flow estimation. We reformulate the prob- lem using a number of discrete displacements, and there- fore the estimation of the morphing parameters becomes a tractable matching criteria independent combinatorial problem which is solved t...
Article
Full-text available
This paper presents a hybrid (geometry- & image-based) framework suitable for providing photorealistic walkthroughs of large, complex outdoor scenes at interactive frame rates. To this end, based just on a sparse set of real stereoscopic views from the scene, a set of morphable 3D-mosaics is automatically constructed first, and then, during renderi...
Article
In this paper, we introduce a novel and efficient approach to dense image registration, which does not require a derivative of the employed cost function. In such a context, the registration problem is formulated using a discrete Markov random field objective function. First, towards dimensionality reduction on the variables we assume that the dens...
Conference Paper
Full-text available
In diesem Beitrag wird eine neuartige Methode für die nichtlineare Bildregistrierung vorgestellt. Dabei wird das klassische Energieminimierungsproblem Intensitäts-basierter Methoden in eine Markov Random Field Formulierung eingebettet. Dieses ermöglicht die Nutzung von effizienten diskreten Optimierungsmethoden, die unabhängig von der tatsächlich v...
Conference Paper
Full-text available
A novel center-based clustering algorithm is proposed in this paper. We first formulate clustering as an NP-hard linear integer program and we then use linear programming and the duality theory to derive the solution of this optimization problem. This leads to an efficient and very general algorithm, which works in the dual domain, and can cluster...
Conference Paper
Full-text available
In this paper we propose a novel approach for automatic segmentation of cartilage using a statistical atlas and efficient primal/dual linear programming. To this end, a novel statistical atlas construction is considered from registered training examples. Segmentation is then solved through registration which aims at deforming the atlas such that th...
Article
In this paper, a new exemplar-based framework is presented, which treats image completion, texture synthesis, and image inpainting in a unified manner. In order to be able to avoid the occurrence of visually inconsistent results, we pose all of the above image-editing tasks in the form of a discrete global optimization problem. The objective functi...
Conference Paper
In this paper we propose a novel approach to ventricular motion estimation and segmentation. Our method is based on a MRF formulation where an optimal intensity-based separation between the endocardium and the rest of the cardiac volume is to be determined. Such a term is defined in the spatiotemporal domain, where the ventricular wall motion is in...
Conference Paper
Full-text available
A new message-passing scheme for MRF optimization is proposed in this paper. This scheme inherits better theoretical properties than all other state-of-the-art message passing methods and in practice performs equally well/outperforms them. It is based on the very powerful technique of Dual Decomposition [1] and leads to an elegant and general frame...
Conference Paper
Full-text available
In this paper we present a video summarization scheme. First, shot detection is performed and then we extract the key frames under an equality requirement on subshots. We propose a key frames selection algorithm (Iso-Content MINMAX), which is very flexible on any choice of content descriptors, and is based on MINMAX optimization formulation. The eq...
Conference Paper
Full-text available
A Bayesian, fully automatic moving object localization method is proposed, using inter-frame differences and background/foreground colour as discrimination cues. Change detection pixel classification to one of the labels "changed" or "unchanged" is obtained by mixture analysis, while histograms are used for statistical description of colours. High...
Conference Paper
Full-text available
We propose a general framework that focuses on automatic individual/multiple people motion-shape analysis and on suitable features extraction that can be used on action/activity recognition problems under real, dynamical and unconstrained environments. We have considered various athletic videos from a single uncalibrated, possibly moving camera in...
Article
A new framework is presented for both understanding and developing graph-cut-based combinatorial algorithms suitable for the approximate optimization of a very wide class of Markov Random Fields (MRFs) that are frequently encountered in computer vision. The proposed framework utilizes tools from the duality theory of linear programming in order to...
Conference Paper
Full-text available
We present a key frames selection algorithm, which is very flexible on any changes of content descriptors, based on iso-content distance and iso-distortion principles. In both of the cases, the equality principle provides to the selected key frames the property to be equivalent on content video summarization. The estimated key frames properties and...
Conference Paper
Full-text available
We propose a generic, unsupervised feature classification and image segmentation framework, where only the number of classes is assumed as known. Image segmentation is treated as an optimization problem. The framework involves block-based unsupervised clustering using k-means, followed by region growing in spatial domain. High confidence statistica...
Conference Paper
Full-text available
A newefficientMRF optimizationalgorithm, calledFast- PD, is proposed, which generalizes �-expansion. One of its main advantages is that it offers a substantial speedup over that method, e.g. it can be at least 3-9 times faster than �-expansion. Its efficiency is a result of the fact that Fast-PDexploitsinformationcomingnotonlyfrom theorig- inal MRF...
Article
Full-text available
In this paper, we present an algorithm based on equal errors principle, which solves the general version of polygonal approximation problem (GPA). The approximation nodes of GPA can be selected anywhere on the original polygonal curve, while the “classical” (usually used) polygonal approximation problem (PA) demands the vertices to be a subset of t...
Article
Full-text available
In this paper we propose a novel approach for automatic segmentation of cartilage using a statistical atlas and efficient primal/dual linear programming. To this end, a novel statistical atlas construction is considered from registered training examples. Segmentation is then solved through registration which aims at deforming the atlas such that th...
Conference Paper
Full-text available
In this paper we propose a novel non-rigid volume registration based on discrete labeling and linear programming. The proposed framework reformulates registration as a minimal path extraction in a weighted graph. The space of solutions is represented using a set of a labels which are assigned to predefined displacements. The graph topology correspo...
Article
Full-text available
A new efficient MRF optimization algorithm, called Fast-PD, is proposed, which gen- eralizes �-expansion. One of its main advantages is that it offers a substantial speedup over that method, e.g. it can be at least 3-9 times faster than �-expansion. Its efficiency is a result of the fact that Fast-PD exploits information coming not only from the or...
Article
Full-text available
We present an unsupervised, automatic human motion analy-sis and action recognition scheme tested on athletics videos. First, four major human points are recognized and tracked us-ing human silhouettes that are computed by a robust camera estimation and object localization method. Statistical analy-sis of the tracking points motion obtains a tempor...
Conference Paper
Full-text available
In this paper we propose a new method for image segmen- tation. The new algorithm is applied to the video segmenta- tion task, where the localization of moving objects is based on change detection. The change detection problem in the pixel domain is formulated by two zero mean Laplacian dis- tributions. The new method follows the concept of the wel...
Article
Full-text available
We present a method for a 3D snake model construction and terrestrial snake locomotion synthesis in 3D virtual environments using image sequences. The snake skeleton is extracted and partitioned into equal segments using a new iterative algorithm for solving the equipartition problem. This method is applied to D model construction and at the motion...
Conference Paper
Full-text available
An automatic human shape-motion analysis method based on a fusion architecture is proposed for human action recognition in videos. Robust shape-motion features are extracted from human points detection and tracking. The features are combined within the Transferable Belief Model (TBM) framework for action recognition. The TBM-based modelling and fus...
Conference Paper
Full-text available
In this paper, an adaptable neural network model is used for real time video delivery over communication networks of low and variable bandwidth, such as the wireless ones. The scheme performs video delivery in content domain in contrast to the previous approaches in which only temporal frame skipping is adopted. The proposed method requires no buff...
Article
Full-text available
We describe briefly the problem of partitioning a con- tinuous curve into N parts with equal chords. (The length of a chord may be defined by any smooth distance metric applied on its endpoints-the Euclidean metric being one of them.) A have proved that a decision variation of this prob- lem is NP-complete, yet for any continuouscurve and any N the...
Conference Paper
Full-text available
A new framework is presented that uses tools from duality theory of linear programming to derive graph-cut based combinatorial algorithms for approximating NP-hard classification problems. The derived algorithms include alpha-expansion graph cut techniques merely as a special case, have guaranteed optimality properties even in cases where alpha-exp...
Article
Full-text available
The European DHX project is introduced in this paper and the vision-based 3D content authoring tools that have been implemented as a core part of its framework are presented. These tools consist mainly of two interrelated components. The first one is a hybrid (geometry and image based) modeling and rendering system capable of providing photorealist...
Conference Paper
Full-text available
Many applications are concerned by human action recognition notably in multimedia and more particularly for video retrieval and archival. Usual approaches focus on probabilistic methods and assume a still camera. In this paper, a method based on the Transferable Belief Model fusion process and considering a moving camera is proposed. In this framew...
Article
Full-text available
In this paper we propose a method for the detection and localiza-tion of moving objects. The change detection problem in the pixel domain is formulated by two zero mean Laplacian distributions. Furthermore, the image is split in homogeneous colour regions and their inter-frame mean absolute difference is used to describe the change detection proble...
Article
Full-text available
Over the last several years, major efforts have been made to develop methods for extracting information from audiovisual media, in order that they may be stored and retrieved in databases automatically, based on their content. In this work we deal with the characterization of an audio signal, which may be part of a larger audiovisual system or may...
Article
In this paper, we explore image retrieval mechanisms based on a combination of texture and color features. Texture features are extracted using Discrete Wavelet Frames (DWF) analysis, an over-complete decomposition in scale and orientation. Two-dimensional (2-D) or one-dimensional (1-D) histograms of the CIE Lab chromaticity coordinates are used as...