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Author |
Mikhail Mozerov; Ariel Amato; Xavier Roca |
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Title |
Occlusion Handling in Trinocular Stereo using Composite Disparity Space Image |
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Conference Article |
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Year |
2009 |
Publication |
19th International Conference on Computer Graphics and Vision |
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69–73 |
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In this paper we propose a method that smartly improves occlusion handling in stereo matching using trinocular stereo. The main idea is based on the assumption that any occluded region in a matched stereo pair (middle-left images) in general is not occluded in the opposite matched pair (middle-right images). Then two disparity space images (DSI) can be merged in one composite DSI. The proposed integration differs from the known approach that uses a cumulative cost. A dense disparity map is obtained with a global optimization algorithm using the proposed composite DSI. The experimental results are evaluated on the Middlebury data set, showing high performance of the proposed algorithm especially in the occluded regions. One of the top positions in the rank of the Middlebury website confirms the performance of our method to be competitive with the best stereo matching. |
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Moscow (Russia) |
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978-5-317-02975-3 |
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GRAPHICON |
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ISE |
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no |
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ISE @ ise @ MAR2009b |
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1207 |
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Author |
Pau Baiget |
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Title |
Modeling Human Behavior for Image Sequence Understanding and Generation |
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Book Whole |
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Year |
2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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The comprehension of animal behavior, especially human behavior, is one of the most ancient and studied problems since the beginning of civilization. The big list of factors that interact to determine a person action require the collaboration of different disciplines, such as psichology, biology, or sociology. In the last years the analysis of human behavior has received great attention also from the computer vision community, given the latest advances in the acquisition of human motion data from image sequences.
Despite the increasing availability of that data, there still exists a gap towards obtaining a conceptual representation of the obtained observations. Human behavior analysis is based on a qualitative interpretation of the results, and therefore the assignment of concepts to quantitative data is linked to a certain ambiguity.
This Thesis tackles the problem of obtaining a proper representation of human behavior in the contexts of computer vision and animation. On the one hand, a good behavior model should permit the recognition and explanation the observed activity in image sequences. On the other hand, such a model must allow the generation of new synthetic instances, which model the behavior of virtual agents.
First, we propose methods to automatically learn the models from observations. Given a set of quantitative results output by a vision system, a normal behavior model is learnt. This results provides a tool to determine the normality or abnormality of future observations. However, machine learning methods are unable to provide a richer description of the observations. We confront this problem by means of a new method that incorporates prior knowledge about the enviornment and about the expected behaviors. This framework, formed by the reasoning engine FMTL and the modeling tool SGT allows the generation of conceptual descriptions of activity in new image sequences. Finally, we demonstrate the suitability of the proposed framework to simulate behavior of virtual agents, which are introduced into real image sequences and interact with observed real agents, thereby easing the generation of augmented reality sequences.
The set of approaches presented in this Thesis has a growing set of potential applications. The analysis and description of behavior in image sequences has its principal application in the domain of smart video--surveillance, in order to detect suspicious or dangerous behaviors. Other applications include automatic sport commentaries, elderly monitoring, road traffic analysis, and the development of semantic video search engines. Alternatively, behavioral virtual agents allow to simulate accurate real situations, such as fires or crowds. Moreover, the inclusion of virtual agents into real image sequences has been widely deployed in the games and cinema industries. |
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Bellaterra (Spain) |
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Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Jordi Gonzalez;Xavier Roca |
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no |
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Call Number |
Admin @ si @ Bai2009 |
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1210 |
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Author |
Jordi Gonzalez; Dani Rowe; Javier Varona; Xavier Roca |
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Title |
Understanding Dynamic Scenes based on Human Sequence Evaluation |
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Journal Article |
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Year |
2009 |
Publication |
Image and Vision Computing |
Abbreviated Journal |
IMAVIS |
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Volume |
27 |
Issue |
10 |
Pages |
1433–1444 |
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Keywords |
Image Sequence Evaluation; High-level processing of monitored scenes; Segmentation and tracking in complex scenes; Event recognition in dynamic scenes; Human motion understanding; Human behaviour interpretation; Natural-language text generation; Realistic demonstrators |
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In this paper, a Cognitive Vision System (CVS) is presented, which explains the human behaviour of monitored scenes using natural-language texts. This cognitive analysis of human movements recorded in image sequences is here referred to as Human Sequence Evaluation (HSE) which defines a set of transformation modules involved in the automatic generation of semantic descriptions from pixel values. In essence, the trajectories of human agents are obtained to generate textual interpretations of their motion, and also to infer the conceptual relationships of each agent w.r.t. its environment. For this purpose, a human behaviour model based on Situation Graph Trees (SGTs) is considered, which permits both bottom-up (hypothesis generation) and top-down (hypothesis refinement) analysis of dynamic scenes. The resulting system prototype interprets different kinds of behaviour and reports textual descriptions in multiple languages. |
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ISE |
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no |
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ISE @ ise @ GRV2009 |
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1211 |
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Author |
Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez |
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Title |
Exploiting Natural Language Generation in Scene Interpretation |
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Book Chapter |
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Year |
2009 |
Publication |
Human–Centric Interfaces for Ambient Intelligence |
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4 |
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71–93 |
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Elsevier Science and Tech |
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ISE |
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no |
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Call Number |
ISE @ ise @ FBR2009 |
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1212 |
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Author |
Ivan Huerta; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez |
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Title |
Detection and Removal of Chromatic Moving Shadows in Surveillance Scenarios |
Type |
Conference Article |
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Year |
2009 |
Publication |
12th International Conference on Computer Vision |
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Pages |
1499 - 1506 |
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Segmentation in the surveillance domain has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects. In this paper we present a novel technique based on gradient and colour models for separating chromatic moving cast shadows from detected moving objects. Firstly, both a chromatic invariant colour cone model and an invariant gradient model are built to perform automatic segmentation while detecting potential shadows. In a second step, regions corresponding to potential shadows are grouped by considering “a bluish effect” and an edge partitioning. Lastly, (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in order to finally identify umbra shadows. Unlike other approaches, our method does not make any a-priori assumptions about camera location, surface geometries, surface textures, shapes and types of shadows, objects, and background. Experimental results show the performance and accuracy of our approach in different shadowed materials and illumination conditions. |
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Kyoto, Japan |
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1550-5499 |
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978-1-4244-4420-5 |
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ICCV |
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no |
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Call Number |
ISE @ ise @ HHM2009 |
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1213 |
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Author |
Marco Pedersoli; Jordi Gonzalez; Juan J. Villanueva |
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Title |
High-Speed Human Detection Using a Multiresolution Cascade of Histograms of Oriented Gradients |
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Conference Article |
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Year |
2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
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Volume |
5524 |
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This paper presents a new method for human detection based on a multiresolution cascade of Histograms of Oriented Gradients (HOG) that can highly reduce the computational cost of the detection search without affecting accuracy. The method consists of a cascade of sliding window detectors. Each detector is a Support Vector Machine (SVM) composed by features at different resolution, from coarse for the first level to fine for the last one.
Considering that the spatial stride of the sliding window search is affected by the HOG features size, unlike previous methods based on Adaboost cascades, we can adopt a spatial stride inversely proportional to the features resolution. This produces that the speed-up of the cascade is not only due to the low number of features that need to be computed in the first levels, but also to the lower number of detection windows that needs to be evaluated.
Experimental results shows that our method permits a detection rate comparable with the state of the art, but at the same time a gain in the speed of the detection search of 10-20 times depending on the cascade configuration. |
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Póvoa de Varzim, Portugal |
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Springer Berlin Heidelberg |
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LNCS |
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0302-9743 |
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978-3-642-02171-8 |
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IbPRIA |
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ISE |
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no |
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Call Number |
ISE @ ise @ PGV2009 |
Serial |
1214 |
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Author |
Bhaskar Chakraborty; Andrew Bagdanov; Jordi Gonzalez |
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Title |
Towards Real-Time Human Action Recognition |
Type |
Conference Article |
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Year |
2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
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5524 |
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This work presents a novel approach to human detection based action-recognition in real-time. To realize this goal our method first detects humans in different poses using a correlation-based approach. Recognition of actions is done afterward based on the change of the angular values subtended by various body parts. Real-time human detection and action recognition are very challenging, and most state-of-the-art approaches employ complex feature extraction and classification techniques, which ultimately becomes a handicap for real-time recognition. Our correlation-based method, on the other hand, is computationally efficient and uses very simple gradient-based features. For action recognition angular features of body parts are extracted using a skeleton technique. Results for action recognition are comparable with the present state-of-the-art. |
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Póvoa de Varzim, Portugal |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-02171-8 |
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IbPRIA |
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ISE |
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no |
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DAG @ dag @ CBG2009 |
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1215 |
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Author |
Murad Al Haj; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca |
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Title |
Robust and Efficient Multipose Face Detection Using Skin Color Segmentation |
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Conference Article |
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Year |
2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
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5524 |
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In this paper we describe an efficient technique for detecting faces in arbitrary images and video sequences. The approach is based on segmentation of images or video frames into skin-colored blobs using a pixel-based heuristic. Scale and translation invariant features are then computed from these segmented blobs which are used to perform statistical discrimination between face and non-face classes. We train and evaluate our method on a standard, publicly available database of face images and analyze its performance over a range of statistical pattern classifiers. The generalization of our approach is illustrated by testing on an independent sequence of frames containing many faces and non-faces. These experiments indicate that our proposed approach obtains false positive rates comparable to more complex, state-of-the-art techniques, and that it generalizes better to new data. Furthermore, the use of skin blobs and invariant features requires fewer training samples since significantly fewer non-face candidate regions must be considered when compared to AdaBoost-based approaches. |
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Springer Berlin Heidelberg |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-02171-8 |
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IbPRIA |
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ISE |
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no |
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Call Number |
DAG @ dag @ ABG2009 |
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1216 |
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Author |
D. Jayagopi; Bogdan Raducanu; D. Gatica-Perez |
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Title |
Characterizing conversational group dynamics using nonverbal behaviour |
Type |
Conference Article |
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Year |
2009 |
Publication |
10th IEEE International Conference on Multimedia and Expo |
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370–373 |
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This paper addresses the novel problem of characterizing conversational group dynamics. It is well documented in social psychology that depending on the objectives a group, the dynamics are different. For example, a competitive meeting has a different objective from that of a collaborative meeting. We propose a method to characterize group dynamics based on the joint description of a group members' aggregated acoustical nonverbal behaviour to classify two meeting datasets (one being cooperative-type and the other being competitive-type). We use 4.5 hours of real behavioural multi-party data and show that our methodology can achieve a classification rate of upto 100%. |
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New York, USA |
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ISSN |
1945-7871 |
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978-1-4244-4290-4 |
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ICME |
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OR;MV |
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no |
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BCNPCL @ bcnpcl @ JRG2009 |
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1217 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Title |
Three-Dimensional Face Pose Detection and Tracking Using Monocular Videos: Tool and Application |
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Journal Article |
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Year |
2009 |
Publication |
IEEE Transactions on Systems, Man and Cybernetics part B |
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TSMCB |
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39 |
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4 |
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935–944 |
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Recently, we have proposed a real-time tracker that simultaneously tracks the 3-D head pose and facial actions in monocular video sequences that can be provided by low quality cameras. This paper has two main contributions. First, we propose an automatic 3-D face pose initialization scheme for the real-time tracker by adopting a 2-D face detector and an eigenface system. Second, we use the proposed methods-the initialization and tracking-for enhancing the human-machine interaction functionality of an AIBO robot. More precisely, we show how the orientation of the robot's camera (or any active vision system) can be controlled through the estimation of the user's head pose. Applications based on head-pose imitation such as telepresence, virtual reality, and video games can directly exploit the proposed techniques. Experiments on real videos confirm the robustness and usefulness of the proposed methods. |
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OR;MV |
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no |
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BCNPCL @ bcnpcl @ DoR2009a |
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1218 |
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Author |
Miquel Ferrer; Ernest Valveny; F. Serratosa; I. Bardaji; Horst Bunke |
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Graph-based k-means clustering: A comparison of the set versus the generalized median graph |
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Conference Article |
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Year |
2009 |
Publication |
13th International Conference on Computer Analysis of Images and Patterns |
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5702 |
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342–350 |
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In this paper we propose the application of the generalized median graph in a graph-based k-means clustering algorithm. In the graph-based k-means algorithm, the centers of the clusters have been traditionally represented using the set median graph. We propose an approximate method for the generalized median graph computation that allows to use it to represent the centers of the clusters. Experiments on three databases show that using the generalized median graph as the clusters representative yields better results than the set median graph. |
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Münster, Germany |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-03766-5 |
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CAIP |
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DAG |
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no |
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DAG @ dag @ FVS2009d |
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1219 |
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Author |
Oriol Ramos Terrades; Ernest Valveny; Salvatore Tabbone |
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Title |
Optimal Classifier Fusion in a Non-Bayesian Probabilistic Framework |
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Journal Article |
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Year |
2009 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
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TPAMI |
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31 |
Issue |
9 |
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1630–1644 |
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The combination of the output of classifiers has been one of the strategies used to improve classification rates in general purpose classification systems. Some of the most common approaches can be explained using the Bayes' formula. In this paper, we tackle the problem of the combination of classifiers using a non-Bayesian probabilistic framework. This approach permits us to derive two linear combination rules that minimize misclassification rates under some constraints on the distribution of classifiers. In order to show the validity of this approach we have compared it with other popular combination rules from a theoretical viewpoint using a synthetic data set, and experimentally using two standard databases: the MNIST handwritten digit database and the GREC symbol database. Results on the synthetic data set show the validity of the theoretical approach. Indeed, results on real data show that the proposed methods outperform other common combination schemes. |
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0162-8828 |
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DAG |
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no |
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DAG @ dag @ RVT2009 |
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1220 |
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Author |
Ricard Coll; Alicia Fornes; Josep Llados |
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Title |
Graphological Analysis of Handwritten Text Documents for Human Resources Recruitment |
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Conference Article |
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2009 |
Publication |
10th International Conference on Document Analysis and Recognition |
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1081–1085 |
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The use of graphology in recruitment processes has become a popular tool in many human resources companies. This paper presents a model that links features from handwritten images to a number of personality characteristics used to measure applicant aptitudes for the job in a particular hiring scenario. In particular we propose a model of measuring active personality and leadership of the writer. Graphological features that define such a profile are measured in terms of document and script attributes like layout configuration, letter size, shape, slant and skew angle of lines, etc. After the extraction, data is classified using a neural network. An experimental framework with real samples has been constructed to illustrate the performance of the approach. |
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Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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DAG @ dag @ CFL2009 |
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1221 |
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Author |
Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke |
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Title |
Symbol-independent writer identification in old handwritten music scores |
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Conference Article |
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2009 |
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In proceedings of 8th IAPR International Workshop on Graphics Recognition |
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186–197 |
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La Rochelle, France |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-13727-3 |
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GREC |
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DAG @ dag @ FLS2009a |
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1222 |
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Author |
Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke |
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On the use of textural features for writer identification in old handwritten music scores |
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Conference Article |
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2009 |
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10th International Conference on Document Analysis and Recognition |
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996 - 1000 |
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Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores which uses only music notation to determine the author. The steps of the proposed system are the following. First of all, the music sheet is preprocessed for obtaining a music score without the staff lines. Afterwards, four different methods for generating texture images from music symbols are applied. Every approach uses a different spatial variation when combining the music symbols to generate the textures. Finally, Gabor filters and Grey-scale Co-ocurrence matrices are used to obtain the features. The classification is performed using a k-NN classifier based on Euclidean distance. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving encouraging identification rates. |
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Barcelona |
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1520-5363 |
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978-1-4244-4500-4 |
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DAG @ dag @ FLS2009b |
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1223 |
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