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| Author | Jaume Amores | ||||
| Title | Vocabulary-based Approaches for Multiple-Instance Data: a Comparative Study | Type | Conference Article | ||
| Year | 2010 | Publication | 20th International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 4246–4250 | ||
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Abstract  |
Multiple Instance Learning (MIL) has become a hot topic and many different algorithms have been proposed in the last years. Despite this fact, there is a lack of comparative studies that shed light into the characteristics of the different methods and their behavior in different scenarios. In this paper we provide such an analysis. We include methods from different families, and pay special attention to vocabulary-based approaches, a new family of methods that has not received much attention in the MIL literature. The empirical comparison includes seven databases from four heterogeneous domains, implementations of eight popular MIL methods, and a study of the behavior under synthetic conditions. Based on this analysis, we show that, with an appropriate implementation, vocabulary-based approaches outperform other MIL methods in most of the cases, showing in general a more consistent performance. | ||||
| Address | Istanbul, Turkey | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1051-4651 | ISBN | 978-1-4244-7542-1 | Medium | |
| Area | Expedition | Conference | ICPR | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ Amo2010 | Serial | 1295 | ||
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| Author | Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
| Title | Reduction of Pattern Search Area in Colonoscopy Images by Merging Non-Informative Regions | Type | Conference Article | ||
| Year | 2010 | Publication | 28th Congreso Anual de la Sociedad Española de Ingeniería Biomédica | Abbreviated Journal | |
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| Abstract |
One of the first usual steps in pattern recognition schemas is image segmentation, in order to reduce the dimensionality of the problem and manage smaller quantity of data. In our case as we are pursuing real-time colon cancer polyp detection, this step is crucial. In this paper we present a non-informative region estimation algorithm that will let us discard some parts of the image where we will not expect to find colon cancer polyps. The performance of our approach will be measured in terms of both non-informative areas elimination and polyps’ areas preserving. The results obtained show the importance of having correct non- informative region estimation in order to fasten the whole recognition process. | ||||
| Address | Madrid (Spain) | ||||
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| Area | 800 | Expedition | Conference | CASEIB | |
| Notes | MV;SIAI | Approved | no | ||
| Call Number | Admin @ si @ BSV2010 | Serial | 1469 | ||
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| Author | Alicia Fornes; Josep Llados; Gemma Sanchez; Dimosthenis Karatzas | ||||
| Title | Rotation Invariant Hand-Drawn Symbol Recognition based on a Dynamic Time Warping Model | Type | Journal Article | ||
| Year | 2010 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
| Volume | 13 | Issue | 3 | Pages | 229–241 |
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| Abstract |
One of the major difficulties of handwriting symbol recognition is the high variability among symbols because of the different writer styles. In this paper, we introduce a robust approach for describing and recognizing hand-drawn symbols tolerant to these writer style differences. This method, which is invariant to scale and rotation, is based on the dynamic time warping (DTW) algorithm. The symbols are described by vector sequences, a variation of the DTW distance is used for computing the matching distance, and K-Nearest Neighbor is used to classify them. Our approach has been evaluated in two benchmarking scenarios consisting of hand-drawn symbols. Compared with state-of-the-art methods for symbol recognition, our method shows higher tolerance to the irregular deformations induced by hand-drawn strokes. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1433-2833 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; IF 2009: 1,213 | Approved | no | ||
| Call Number | DAG @ dag @ FLS2010a | Serial | 1288 | ||
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| Author | Naila Murray; Eduard Vazquez | ||||
| Title | Lacuna Restoration: How to choose a neutral colour? | Type | Conference Article | ||
| Year | 2010 | Publication | Proceedings of The CREATE 2010 Conference | Abbreviated Journal | |
| Volume | Issue | Pages | 248–252 | ||
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| Abstract |
Painting restoration which involves filling in material loss (called lacuna) is a complex process. Several standard techniques exist to tackle lacuna restoration,
and this article focuses on those techniques that employ a “neutral” colour to mask the defect. Restoration experts often disagree on the choice of such a colour and in fact, the concept of a neutral colour is controversial. We posit that a neutral colour is one that attracts relatively little visual attention for a specific lacuna. We conducted an eye tracking experiment to compare two common neutral colour selection methods, specifically the most common local colour and the mean local colour. Results obtained demonstrate that the most common local colour triggers less visual attention in general. Notwithstanding, we have observed instances in which the most common colour triggers a significant amount of attention when subjects spent time resolving their confusion about whether or not a lacuna was part of the painting. |
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| Address | Gjovik, Norway | ||||
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| Area | Expedition | Conference | CREATE | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ MuV2010 | Serial | 1297 | ||
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| Author | Sergio Escalera; Oriol Pujol; Eric Laciar; Jordi Vitria; Esther Pueyo; Petia Radeva | ||||
| Title | Classification of Coronary Damage in Chronic Chagasic Patients | Type | Book Chapter | ||
| Year | 2010 | Publication | Intelligent Systems – From Theory to Practice. Studies in Computational Intelligence | Abbreviated Journal | |
| Volume | 299 | Issue | Pages | 461-478 | |
| Keywords | Chagas disease; Error-Correcting Output Codes; High resolution ECG; Decoding | ||||
| Abstract |
Post Conference IEEE-IS 2008
The Chagas’ disease is endemic in all Latin America, affecting millions of people in the continent. In order to diagnose and treat the chagas’ disease, it is important to detect and measure the coronary damage of the patient. In this paper, we analyze and categorize patients into different groups based on the coronary damage produced by the disease. Based on the features of the heart cycle extracted using high resolution ECG, a multi-class scheme of Error-Correcting Output Codes (ECOC)is formulated and successfully applied. The results show that the proposed scheme obtains significant performance improvements compared to previous works and state-of-the-art ECOC designs. |
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| Publisher | Springer-Verlag | Place of Publication | Editor | V. Sgurev, M. Hadjiski (eds) | |
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| Notes | OR;MILAB;HUPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPL2010 | Serial | 1452 | ||
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| Author | Maurizio Mencuccini; Jordi Martinez-Vilalta; Josep Piñol; Lasse Loepfe; Mireia Burnat ; Xavier Alvarez; Juan Camacho; Debora Gil | ||||
| Title | A quantitative and statistically robust method for the determination of xylem conduit spatial distribution | Type | Journal Article | ||
| Year | 2010 | Publication | American Journal of Botany | Abbreviated Journal | AJB |
| Volume | 97 | Issue | 8 | Pages | 1247-1259 |
| Keywords | Geyer; hydraulic conductivity; point pattern analysis; Ripley; Spatstat; vessel clusters; xylem anatomy; xylem network | ||||
| Abstract |
Premise of the study: Because of their limited length, xylem conduits need to connect to each other to maintain water transport from roots to leaves. Conduit spatial distribution in a cross section plays an important role in aiding this connectivity. While indices of conduit spatial distribution already exist, they are not well defined statistically. * Methods: We used point pattern analysis to derive new spatial indices. One hundred and five cross-sectional images from different species were transformed into binary images. The resulting point patterns, based on the locations of the conduit centers-of-area, were analyzed to determine whether they departed from randomness. Conduit distribution was then modeled using a spatially explicit stochastic model. * Key results: The presence of conduit randomness, uniformity, or aggregation depended on the spatial scale of the analysis. The large majority of the images showed patterns significantly different from randomness at least at one spatial scale. A strong phylogenetic signal was detected in the spatial variables. * Conclusions: Conduit spatial arrangement has been largely conserved during evolution, especially at small spatial scales. Species in which conduits were aggregated in clusters had a lower conduit density compared to those with uniform distribution. Statistically sound spatial indices must be employed as an aid in the characterization of distributional patterns across species and in models of xylem water transport. Point pattern analysis is a very useful tool in identifying spatial patterns. | ||||
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| Notes | IAM; | Approved | no | ||
| Call Number | IAM @ iam @ MMG2010 | Serial | 1623 | ||
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| Author | Francisco Javier Orozco | ||||
| Title | Human Emotion Evaluation on Facial Image Sequences | Type | Book Whole | ||
| Year | 2010 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract |
Psychological evidence has emphasized the importance of affective behaviour understanding due to its high impact in nowadays interaction humans and computers. All
type of affective and behavioural patterns such as gestures, emotions and mental states are highly displayed through the face, head and body. Therefore, this thesis is focused to analyse affective behaviours on head and face. To this end, head and facial movements are encoded by using appearance based tracking methods. Specifically, a wise combination of deformable models captures rigid and non-rigid movements of different kinematics; 3D head pose, eyebrows, mouth, eyelids and irises are taken into account as basis for extracting features from databases of video sequences. This approach combines the strengths of adaptive appearance models, optimization methods and backtracking techniques. For about thirty years, computer sciences have addressed the investigation on human emotions to the automatic recognition of six prototypic emotions suggested by Darwin and systematized by Paul Ekman in the seventies. The Facial Action Coding System (FACS) which uses discrete movements of the face (called Action units or AUs) to code the six facial emotions named anger, disgust, fear, happy-Joy, sadness and surprise. However, human emotions are much complex patterns that have not received the same attention from computer scientists. Simon Baron-Cohen proposed a new taxonomy of emotions and mental states without a system coding of the facial actions. These 426 affective behaviours are more challenging for the understanding of human emotions. Beyond of classically classifying the six basic facial expressions, more subtle gestures, facial actions and spontaneous emotions are considered here. By assessing confidence on the recognition results, exploring spatial and temporal relationships of the features, some methods are combined and enhanced for developing new taxonomy of expressions and emotions. The objective of this dissertation is to develop a computer vision system, including both facial feature extraction, expression recognition and emotion understanding by building a bottom-up reasoning process. Building a detailed taxonomy of human affective behaviours is an interesting challenge for head-face-based image analysis methods. In this paper, we exploit the strengths of Canonical Correlation Analysis (CCA) to enhance an on-line head-face tracker. A relationship between head pose and local facial movements is studied according to their cognitive interpretation on affective expressions and emotions. Active Shape Models are synthesized for AAMs based on CCA-regression. Head pose and facial actions are fused into a maximally correlated space in order to assess expressiveness, confidence and classification in a CBR system. The CBR solutions are also correlated to the cognitive features, which allow avoiding exhaustive search when recognizing new head-face features. Subsequently, Support Vector Machines (SVMs) and Bayesian Networks are applied for learning the spatial relationships of facial expressions. Similarly, the temporal evolution of facial expressions, emotion and mental states are analysed based on Factorized Dynamic Bayesian Networks (FaDBN). As results, the bottom-up system recognizes six facial expressions, six basic emotions and six mental states, plus enhancing this categorization with confidence assessment at each level, intensity of expressions and a complete taxonomy |
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| Address | |||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Gonzalez;Xavier Roca | |
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-936529-3-7 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | Admin @ si @ Oro2010 | Serial | 1335 | ||
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| Author | Simone Balocco; O. Camara; E. Vivas; T. Sola; L. Guimaraens; H. A. van Andel; C. B. Majoie; J. M. Pozo; B. H. Bijnens; Alejandro F. Frangi | ||||
| Title | Feasibility of Estimating Regional Mechanical Properties of Cerebral Aneurysms In Vivo | Type | Journal Article | ||
| Year | 2010 | Publication | Medical Physics | Abbreviated Journal | MEDPHYS |
| Volume | 37 | Issue | 4 | Pages | 1689–1706 |
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| Abstract |
PURPOSE:
In this article, the authors studied the feasibility of estimating regional mechanical properties in cerebral aneurysms, integrating information extracted from imaging and physiological data with generic computational models of the arterial wall behavior. METHODS: A data assimilation framework was developed to incorporate patient-specific geometries into a given biomechanical model, whereas wall motion estimates were obtained from applying registration techniques to a pair of simulated MR images and guided the mechanical parameter estimation. A simple incompressible linear and isotropic Hookean model coupled with computational fluid-dynamics was employed as a first approximation for computational purposes. Additionally, an automatic clustering technique was developed to reduce the number of parameters to assimilate at the optimization stage and it considerably accelerated the convergence of the simulations. Several in silico experiments were designed to assess the influence of aneurysm geometrical characteristics and the accuracy of wall motion estimates on the mechanical property estimates. Hence, the proposed methodology was applied to six real cerebral aneurysms and tested against a varying number of regions with different elasticity, different mesh discretization, imaging resolution, and registration configurations. RESULTS: Several in silico experiments were conducted to investigate the feasibility of the proposed workflow, results found suggesting that the estimation of the mechanical properties was mainly influenced by the image spatial resolution and the chosen registration configuration. According to the in silico experiments, the minimal spatial resolution needed to extract wall pulsation measurements with enough accuracy to guide the proposed data assimilation framework was of 0.1 mm. CONCLUSIONS: Current routine imaging modalities do not have such a high spatial resolution and therefore the proposed data assimilation framework cannot currently be used on in vivo data to reliably estimate regional properties in cerebral aneurysms. Besides, it was observed that the incorporation of fluid-structure interaction in a biomechanical model with linear and isotropic material properties did not have a substantial influence in the final results. |
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| Area | Expedition | Conference | |||
| Notes | MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ BCV2010 | Serial | 1313 | ||
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| Author | Ignasi Rius | ||||
| Title | Motion Priors for Efficient Bayesian Tracking in Human Sequence Evaluation | Type | Book Whole | ||
| Year | 2010 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract |
Recovering human motion by visual analysis is a challenging computer vision research
area with a lot of potential applications. Model-based tracking approaches, and in particular particle lters, formulate the problem as a Bayesian inference task whose aim is to sequentially estimate the distribution of the parameters of a human body model over time. These approaches strongly rely on good dynamical and observation models to predict and update con gurations of the human body according to measurements from the image data. However, it is very di cult to design observation models which extract useful and reliable information from image sequences robustly. This results specially challenging in monocular tracking given that only one viewpoint from the scene is available. Therefore, to overcome these limitations strong motion priors are needed to guide the exploration of the state space. The work presented in this Thesis is aimed to retrieve the 3D motion parameters of a human body model from incomplete and noisy measurements of a monocular image sequence. These measurements consist of the 2D positions of a reduced set of joints in the image plane. Towards this end, we present a novel action-speci c model of human motion which is trained from several databases of real motion-captured performances of an action, and is used as a priori knowledge within a particle ltering scheme. Body postures are represented by means of a simple and compact stick gure model which uses direction cosines to represent the direction of body limbs in the 3D Cartesian space. Then, for a given action, Principal Component Analysis is applied to the training data to perform dimensionality reduction over the highly correlated input data. Before the learning stage of the action model, the input motion performances are synchronized by means of a novel dense matching algorithm based on Dynamic Programming. The algorithm synchronizes all the motion sequences of the same action class, nding an optimal solution in real-time. Then, a probabilistic action model is learnt, based on the synchronized motion examples, which captures the variability and temporal evolution of full-body motion within a speci c action. In particular, for each action, the parameters learnt are: a representative manifold for the action consisting of its mean performance, the standard deviation from the mean performance, the mean observed direction vectors from each motion subsequence of a given length and the expected error at a given time instant. Subsequently, the action-speci c model is used as a priori knowledge on human motion which improves the e ciency and robustness of the overall particle filtering tracking framework. First, the dynamic model guides the particles according to similar situations previously learnt. Then, the state space is constrained so only feasible human postures are accepted as valid solutions at each time step. As a result, the state space is explored more e ciently as the particle set covers the most probable body postures. Finally, experiments are carried out using test sequences from several motion databases. Results point out that our tracker scheme is able to estimate the rough 3D con guration of a full-body model providing only the 2D positions of a reduced set of joints. Separate tests on the sequence synchronization method and the subsequence probabilistic matching technique are also provided. |
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Gonzalez;Xavier Roca | |
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-937261-9-5 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | Approved | no | |||
| Call Number | Admin @ si @ Riu2010 | Serial | 1331 | ||
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| Author | Sergio Vera | ||||
| Title | Finger joint modelling from hand X-ray images for assessing rheumatoid arthritis | Type | Report | ||
| Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume | 164 | Issue | Pages | ||
| Keywords | Rheumatoid arthritis; joint detection; X-ray; Van der Heijde score | ||||
| Abstract |
Rheumatoid arthritis is an autoimmune, systemic, inflammatory disorder that mainly af- fects bone joints. While there is no cure for this disease, continuous advances on palliative treatments require frequent verification of patient’s illness evolution. Such evolution is mea- sured through several available semi-quantitative methods that require evaluation of hand and foot X-ray images. Accurate assessment is a time consuming task that requires highly trained personnel. This hinders a generalized use in clinical practice for early diagnose and disease follow-up. In the context of the automatization of such evaluation methods we present a method for detection and characterization of finger joints in hand radiography images. Several measures for assessing the reduction of joint space width are proposed. We compare for the first time such measures to the Van der Heijde score, the gold standard method for rheumatoid arthritis assessment. The proposed method outperforms existing strategies with a detection rate above 95%. Our comparison to Van der Heijde index shows a promising correlation that encourages further research. | ||||
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| Corporate Author | Thesis | Master's thesis | |||
| Publisher | Place of Publication | Bellaterra 01893, Barcelona, Spain | Editor | ||
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| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ Ver2010 | Serial | 1661 | ||
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| Author | Jose Manuel Alvarez; Felipe Lumbreras; Theo Gevers; Antonio Lopez | ||||
| Title | Geographic Information for vision-based Road Detection | Type | Conference Article | ||
| Year | 2010 | Publication | IEEE Intelligent Vehicles Symposium | Abbreviated Journal | |
| Volume | Issue | Pages | 621–626 | ||
| Keywords | road detection | ||||
| Abstract |
Road detection is a vital task for the development of autonomous vehicles. The knowledge of the free road surface ahead of the target vehicle can be used for autonomous driving, road departure warning, as well as to support advanced driver assistance systems like vehicle or pedestrian detection. Using vision to detect the road has several advantages in front of other sensors: richness of features, easy integration, low cost or low power consumption. Common vision-based road detection approaches use low-level features (such as color or texture) as visual cues to group pixels exhibiting similar properties. However, it is difficult to foresee a perfect clustering algorithm since roads are in outdoor scenarios being imaged from a mobile platform. In this paper, we propose a novel high-level approach to vision-based road detection based on geographical information. The key idea of the algorithm is exploiting geographical information to provide a rough detection of the road. Then, this segmentation is refined at low-level using color information to provide the final result. The results presented show the validity of our approach. | ||||
| Address | San Diego; CA; USA | ||||
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| Area | Expedition | Conference | IV | ||
| Notes | ADAS;ISE | Approved | no | ||
| Call Number | ADAS @ adas @ ALG2010 | Serial | 1428 | ||
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| Author | Jose Manuel Alvarez | ||||
| Title | Combining Context and Appearance for Road Detection | Type | Book Whole | ||
| Year | 2010 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract |
Road traffic crashes have become a major cause of death and injury throughout the world.
Hence, in order to improve road safety, the automobile manufacture is moving towards the development of vehicles with autonomous functionalities such as keeping in the right lane, safe distance keeping between vehicles or regulating the speed of the vehicle according to the traffic conditions. A key component of these systems is vision–based road detection that aims to detect the free road surface ahead the moving vehicle. Detecting the road using a monocular vision system is very challenging since the road is an outdoor scenario imaged from a mobile platform. Hence, the detection algorithm must be able to deal with continuously changing imaging conditions such as the presence ofdifferent objects (vehicles, pedestrians), different environments (urban, highways, off–road), different road types (shape, color), and different imaging conditions (varying illumination, different viewpoints and changing weather conditions). Therefore, in this thesis, we focus on vision–based road detection using a single color camera. More precisely, we first focus on analyzing and grouping pixels according to their low–level properties. In this way, two different approaches are presented to exploit color and photometric invariance. Then, we focus the research of the thesis on exploiting context information. This information provides relevant knowledge about the road not using pixel features from road regions but semantic information from the analysis of the scene. In this way, we present two different approaches to infer the geometry of the road ahead the moving vehicle. Finally, we focus on combining these context and appearance (color) approaches to improve the overall performance of road detection algorithms. The qualitative and quantitative results presented in this thesis on real–world driving sequences show that the proposed method is robust to varying imaging conditions, road types and scenarios going beyond the state–of–the–art. |
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Antonio Lopez;Theo Gevers | |
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-937261-8-8 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ Alv2010 | Serial | 1454 | ||
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| Author | Eloi Puertas; Sergio Escalera; Oriol Pujol | ||||
| Title | Classifying Objects at Different Sizes with Multi-Scale Stacked Sequential Learning | Type | Conference Article | ||
| Year | 2010 | Publication | 13th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 220 | Issue | Pages | 193–200 | |
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| Abstract |
Sequential learning is that discipline of machine learning that deals with dependent data. In this paper, we use the Multi-scale Stacked Sequential Learning approach (MSSL) to solve the task of pixel-wise classification based on contextual information. The main contribution of this work is a shifting technique applied during the testing phase that makes possible, thanks to template images, to classify objects at different sizes. The results show that the proposed method robustly classifies such objects capturing their spatial relationships. | ||||
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| Publisher | Place of Publication | Editor | R. Alquezar, A. Moreno, J. Aguilar | ||
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| ISSN | ISBN | 978-1-60750-642-3 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | HUPBA;MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PEP2010 | Serial | 1448 | ||
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| Author | Alicia Fornes; Sergio Escalera; Josep Llados; Ernest Valveny | ||||
| Title | Symbol Classification using Dynamic Aligned Shape Descriptor | Type | Conference Article | ||
| Year | 2010 | Publication | 20th International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1957–1960 | ||
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| Abstract |
Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we propose a new descriptor and distance computation for coping with the problem of symbol recognition in the domain of Graphical Document Image Analysis. The proposed D-Shape descriptor encodes the arrangement information of object parts in a circular structure, allowing different levels of distortion. The classification is performed using a cyclic Dynamic Time Warping based method, allowing distortions and rotation. The methodology has been validated on different data sets, showing very high recognition rates. | ||||
| Address | Istanbul (Turkey) | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1051-4651 | ISBN | 978-1-4244-7542-1 | Medium | |
| Area | Expedition | Conference | ICPR | ||
| Notes | DAG; HUPBA; MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ FEL2010 | Serial | 1421 | ||
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| Author | Joan Mas | ||||
| Title | A Syntactic Pattern Recognition Approach based on a Distribution Tolerant Adjacency Grammar and a Spatial Indexed Parser. Application to Sketched Document Recognition | Type | Book Whole | ||
| Year | 2010 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract |
Sketch recognition is a discipline which has gained an increasing interest in the last
20 years. This is due to the appearance of new devices such as PDA, Tablet PC’s or digital pen & paper protocols. From the wide range of sketched documents we focus on those that represent structured documents such as: architectural floor-plans, engineering drawing, UML diagrams, etc. To recognize and understand these kinds of documents, first we have to recognize the different compounding symbols and then we have to identify the relations between these elements. From the way that a sketch is captured, there are two categories: on-line and off-line. On-line input modes refer to draw directly on a PDA or a Tablet PC’s while off-line input modes refer to scan a previously drawn sketch. This thesis is an overlapping of three different areas on Computer Science: Pattern Recognition, Document Analysis and Human-Computer Interaction. The aim of this thesis is to interpret sketched documents independently on whether they are captured on-line or off-line. For this reason, the proposed approach should contain the following features. First, as we are working with sketches the elements present in our input contain distortions. Second, as we would work in on-line or off-line input modes, the order in the input of the primitives is indifferent. Finally, the proposed method should be applied in real scenarios, its response time must be slow. To interpret a sketched document we propose a syntactic approach. A syntactic approach is composed of two correlated components: a grammar and a parser. The grammar allows describing the different elements on the document as well as their relations. The parser, given a document checks whether it belongs to the language generated by the grammar or not. Thus, the grammar should be able to cope with the distortions appearing on the instances of the elements. Moreover, it would be necessary to define a symbol independently of the order of their primitives. Concerning to the parser when analyzing 2D sentences, it does not assume an order in the primitives. Then, at each new primitive in the input, the parser searches among the previous analyzed symbols candidates to produce a valid reduction. Taking into account these features, we have proposed a grammar based on Adjacency Grammars. This kind of grammars defines their productions as a multiset of symbols rather than a list. This allows describing a symbol without an order in their components. To cope with distortion we have proposed a distortion model. This distortion model is an attributed estimated over the constraints of the grammar and passed through the productions. This measure gives an idea on how far is the symbol from its ideal model. In addition to the distortion on the constraints other distortions appear when working with sketches. These distortions are: overtracing, overlapping, gaps or spurious strokes. Some grammatical productions have been defined to cope with these errors. Concerning the recognition, we have proposed an incremental parser with an indexation mechanism. Incremental parsers analyze the input symbol by symbol given a response to the user when a primitive is analyzed. This makes incremental parser suitable to work in on-line as well as off-line input modes. The parser has been adapted with an indexation mechanism based on a spatial division. This indexation mechanism allows setting the primitives in the space and reducing the search to a neighbourhood. A third contribution is a grammatical inference algorithm. This method given a set of symbols captures the production describing it. In the field of formal languages, different approaches has been proposed but in the graphical domain not so much work is done in this field. The proposed method is able to capture the production from a set of symbol although they are drawn in different order. A matching step based on the Haussdorff distance and the Hungarian method has been proposed to match the primitives of the different symbols. In addition the proposed approach is able to capture the variability in the parameters of the constraints. From the experimental results, we may conclude that we have proposed a robust approach to describe and recognize sketches. Moreover, the addition of new symbols to the alphabet is not restricted to an expert. Finally, the proposed approach has been used in two real scenarios obtaining a good performance. |
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| Address | |||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Gemma Sanchez;Josep Llados | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-937261-4-0 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ Mas2010 | Serial | 1334 | ||
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