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| Author | Jaume Garcia; Debora Gil; Luis Badiella; Aura Hernandez-Sabate; Francesc Carreras; Sandra Pujades; Enric Marti | ||||
| Title | A Normalized Framework for the Design of Feature Spaces Assessing the Left Ventricular Function | Type | Journal Article | ||
| Year | 2010 | Publication | IEEE Transactions on Medical Imaging | Abbreviated Journal | TMI |
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29 | Issue | 3 | Pages | 733-745 |
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| Abstract | A through description of the left ventricle functionality requires combining complementary regional scores. A main limitation is the lack of multiparametric normality models oriented to the assessment of regional wall motion abnormalities (RWMA). This paper covers two main topics involved in RWMA assessment. We propose a general framework allowing the fusion and comparison across subjects of different regional scores. Our framework is used to explore which combination of regional scores (including 2-D motion and strains) is better suited for RWMA detection. Our statistical analysis indicates that for a proper (within interobserver variability) identification of RWMA, models should consider motion and extreme strains. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0278-0062 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ GGH2010b | Serial | 1507 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
| Title | An Iterative Multiresolution Scheme for SFM with Missing Data: single and multiple object scenes | Type | Journal Article | ||
| Year | 2010 | Publication | Image and Vision Computing | Abbreviated Journal | IMAVIS |
| Volume |
28 | Issue | 1 | Pages | 164-176 |
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| Abstract | Most of the techniques proposed for tackling the Structure from Motion problem (SFM) cannot deal with high percentages of missing data in the matrix of trajectories. Furthermore, an additional problem should be faced up when working with multiple object scenes: the rank of the matrix of trajectories should be estimated. This paper presents an iterative multiresolution scheme for SFM with missing data to be used in both the single and multiple object cases. The proposed scheme aims at recovering missing entries in the original input matrix. The objective is to improve the results by applying a factorization technique to the partially or totally filled in matrix instead of to the original input one. Experimental results obtained with synthetic and real data sequences, containing single and multiple objects, are presented to show the viability of the proposed approach. | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0262-8856 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ JSL2010 | Serial | 1278 | ||
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| Author | Bogdan Raducanu; Jordi Vitria; Ales Leonardis | ||||
| Title | Online pattern recognition and machine learning techniques for computer-vision: Theory and applications | Type | Journal Article | ||
| Year | 2010 | Publication | Image and Vision Computing | Abbreviated Journal | IMAVIS |
| Volume |
28 | Issue | 7 | Pages | 1063–1064 |
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| Abstract | (Editorial for the Special Issue on Online pattern recognition and machine learning techniques)
In real life, visual learning is supposed to be a continuous process. This paradigm has found its way also in artificial vision systems. There is an increasing trend in pattern recognition represented by online learning approaches, which aims at continuously updating the data representation when new information arrives. Starting with a minimal dataset, the initial knowledge is expanded by incorporating incoming instances, which may have not been previously available or foreseen at the system’s design stage. An interesting characteristic of this strategy is that the train and test phases take place simultaneously. Given the increasing interest in this subject, the aim of this special issue is to be a landmark event in the development of online learning techniques and their applications with the hope that it will capture the interest of a wider audience and will attract even more researchers. We received 19 contributions, of which 9 have been accepted for publication, after having been subjected to usual peer review process. |
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| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0262-8856 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RVL2010 | Serial | 1280 | ||
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| Author | Eduard Vazquez; Theo Gevers; M. Lucassen; Joost Van de Weijer; Ramon Baldrich | ||||
| Title | Saliency of Color Image Derivatives: A Comparison between Computational Models and Human Perception | Type | Journal Article | ||
| Year | 2010 | Publication | Journal of the Optical Society of America A | Abbreviated Journal | JOSA A |
| Volume |
27 | Issue | 3 | Pages | 613–621 |
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| Abstract | In this paper, computational methods are proposed to compute color edge saliency based on the information content of color edges. The computational methods are evaluated on bottom-up saliency in a psychophysical experiment, and on a more complex task of salient object detection in real-world images. The psychophysical experiment demonstrates the relevance of using information theory as a saliency processing model and that the proposed methods are significantly better in predicting color saliency (with a human-method correspondence up to 74.75% and an observer agreement of 86.8%) than state-of-the-art models. Furthermore, results from salient object detection confirm that an early fusion of color and contrast provide accurate performance to compute visual saliency with a hit rate up to 95.2%. | ||||
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| Notes | ISE;CIC | Approved | no | ||
| Call Number | CAT @ cat @ VGL2010 | Serial | 1275 | ||
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| Author | Francesco Ciompi; Oriol Pujol; Carlo Gatta; Oriol Rodriguez-Leor; J. Mauri; Petia Radeva | ||||
| Title | Fusing in-vitro and in-vivo intravascular ultrasound data for plaque characterization | Type | Journal Article | ||
| Year | 2010 | Publication | International Journal of Cardiovascular Imaging | Abbreviated Journal | IJCI |
| Volume |
26 | Issue | 7 | Pages | 763–779 |
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| Abstract | Accurate detection of in-vivo vulnerable plaque in coronary arteries is still an open problem. Recent studies show that it is highly related to tissue structure and composition. Intravascular Ultrasound (IVUS) is a powerful imaging technique that gives a detailed cross-sectional image of the vessel, allowing to explore arteries morphology. IVUS data validation is usually performed by comparing post-mortem (in-vitro) IVUS data and corresponding histological analysis of the tissue. The main drawback of this method is the few number of available case studies and validated data due to the complex procedure of histological analysis of the tissue. On the other hand, IVUS data from in-vivo cases is easy to obtain but it can not be histologically validated. In this work, we propose to enhance the in-vitro training data set by selectively including examples from in-vivo plaques. For this purpose, a Sequential Floating Forward Selection method is reformulated in the context of plaque characterization. The enhanced classifier performance is validated on in-vitro data set, yielding an overall accuracy of 91.59% in discriminating among fibrotic, lipidic and calcified plaques, while reducing the gap between in-vivo and in-vitro data analysis. Experimental results suggest that the obtained classifier could be properly applied on in-vivo plaque characterization and also demonstrate that the common hypothesis of assuming the difference between in-vivo and in-vitro as negligible is incorrect. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1569-5794 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB;HUPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPG2010 | Serial | 1305 | ||
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| Author | Dani Rowe; Jordi Gonzalez; Marco Pedersoli; Juan J. Villanueva | ||||
| Title | On Tracking Inside Groups | Type | Journal Article | ||
| Year | 2010 | Publication | Machine Vision and Applications | Abbreviated Journal | MVA |
| Volume |
21 | Issue | 2 | Pages | 113–127 |
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| Abstract | This work develops a new architecture for multiple-target tracking in unconstrained dynamic scenes, which consists of a detection level which feeds a two-stage tracking system. A remarkable characteristic of the system is its ability to track several targets while they group and split, without using 3D information. Thus, special attention is given to the feature-selection and appearance-computation modules, and to those modules involved in tracking through groups. The system aims to work as a stand-alone application in complex and dynamic scenarios. No a-priori knowledge about either the scene or the targets, based on a previous training period, is used. Hence, the scenario is completely unknown beforehand. Successful tracking has been demonstrated in well-known databases of both indoor and outdoor scenarios. Accurate and robust localisations have been yielded during long-term target merging and occlusions. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0932-8092 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ISE | Approved | no | ||
| Call Number | ISE @ ise @ RGP2010 | Serial | 1158 | ||
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| Author | Sergio Escalera; Oriol Pujol; Petia Radeva | ||||
| Title | Traffic sign recognition system with β -correction | Type | Journal Article | ||
| Year | 2010 | Publication | Machine Vision and Applications | Abbreviated Journal | MVA |
| Volume |
21 | Issue | 2 | Pages | 99–111 |
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| Abstract | Traffic sign classification represents a classical application of multi-object recognition processing in uncontrolled adverse environments. Lack of visibility, illumination changes, and partial occlusions are just a few problems. In this paper, we introduce a novel system for multi-class classification of traffic signs based on error correcting output codes (ECOC). ECOC is based on an ensemble of binary classifiers that are trained on bi-partition of classes. We classify a wide set of traffic signs types using robust error correcting codings. Moreover, we introduce the novel β-correction decoding strategy that outperforms the state-of-the-art decoding techniques, classifying a high number of classes with great success. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0932-8092 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB;HUPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPR2010a | Serial | 1276 | ||
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| Author | Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados | ||||
| Title | A Content Spotting System For Line Drawing Graphic Document Images | Type | Conference Article | ||
| Year | 2010 | Publication | 20th International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume |
20 | Issue | Pages | 3420–3423 | |
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| Abstract | We present a content spotting system for line drawing graphic document images. The proposed system is sufficiently domain independent and takes the keyword based information retrieval for graphic documents, one step forward, to Query By Example (QBE) and focused retrieval. During offline learning mode: we vectorize the documents in the repository, represent them by attributed relational graphs, extract regions of interest (ROIs) from them, convert each ROI to a fuzzy structural signature, cluster similar signatures to form ROI classes and build an index for the repository. During online querying mode: a Bayesian network classifier recognizes the ROIs in the query image and the corresponding documents are fetched by looking up in the repository index. Experimental results are presented for synthetic images of architectural and electronic documents. | ||||
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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 | Approved | no | ||
| Call Number | DAG @ dag @ LBR2010b | Serial | 1460 | ||
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| Author | David Rotger; Petia Radeva; N. Bruining | ||||
| Title | Automatic Detection of Bioabsorbable Coronary Stents in IVUS Images using a Cascade of Classifiers | Type | Journal Article | ||
| Year | 2010 | Publication | IEEE Transactions on Information Technology in Biomedicine | Abbreviated Journal | TITB |
| Volume |
14 | Issue | 2 | Pages | 535 – 537 |
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| Abstract | Bioabsorbable drug-eluting coronary stents present a very promising improvement to the common metallic ones solving some of the most important problems of stent implantation: the late restenosis. These stents made of poly-L-lactic acid cause a very subtle acoustic shadow (compared to the metallic ones) making difficult the automatic detection and measurements in images. In this paper, we propose a novel approach based on a cascade of GentleBoost classifiers to detect the stent struts using structural features to code the information of the different subregions of the struts. A stochastic gradient descent method is applied to optimize the overall performance of the detector. Validation results of struts detection are very encouraging with an average F-measure of 81%. | ||||
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| Area | Expedition | Conference | |||
| Notes | MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RRB2010 | Serial | 1287 | ||
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| Author | Marçal Rusiñol; Josep Llados; Gemma Sanchez | ||||
| Title | Symbol Spotting in Vectorized Technical Drawings Through a Lookup Table of Region Strings | Type | Journal Article | ||
| Year | 2010 | Publication | Pattern Analysis and Applications | Abbreviated Journal | PAA |
| Volume |
13 | Issue | 3 | Pages | 321-331 |
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| Abstract | In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1433-7541 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ RLS2010 | Serial | 1165 | ||
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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 | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| 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 | Mathieu Nicolas Delalandre; Ernest Valveny; Tony Pridmore; Dimosthenis Karatzas | ||||
| Title | Generation of Synthetic Documents for Performance Evaluation of Symbol Recognition & Spotting Systems | Type | Journal Article | ||
| Year | 2010 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
| Volume |
13 | Issue | 3 | Pages | 187-207 |
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| Abstract | This paper deals with the topic of performance evaluation of symbol recognition & spotting systems. We propose here a new approach to the generation of synthetic graphics documents containing non-isolated symbols in a real context. This approach is based on the definition of a set of constraints that permit us to place the symbols on a pre-defined background according to the properties of a particular domain (architecture, electronics, engineering, etc.). In this way, we can obtain a large amount of images resembling real documents by simply defining the set of constraints and providing a few pre-defined backgrounds. As documents are synthetically generated, the groundtruth (the location and the label of every symbol) becomes automatically available. We have applied this approach to the generation of a large database of architectural drawings and electronic diagrams, which shows the flexibility of the system. Performance evaluation experiments of a symbol localization system show that our approach permits to generate documents with different features that are reflected in variation of localization results. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1433-2833 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ DVP2010 | Serial | 1289 | ||
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| Author | Alicia Fornes; Josep Llados; Gemma Sanchez; Xavier Otazu; Horst Bunke | ||||
| Title | A Combination of Features for Symbol-Independent Writer Identification in Old Music Scores | Type | Journal Article | ||
| Year | 2010 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
| Volume |
13 | Issue | 4 | Pages | 243-259 |
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| Abstract | The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper, we present an architecture for writer identification in old handwritten music scores. Even though an important amount of music compositions contain handwritten text, the aim of our work is to use only music notation to determine the author. The main contribution is therefore the use of features extracted from graphical alphabets. Our proposal consists in combining the identification results of two different approaches, based on line and textural features. The steps of the ensemble architecture are the following. First of all, the music sheet is preprocessed for removing the staff lines. Then, music lines and texture images are generated for computing line features and textural features. Finally, the classification results are combined for identifying the writer. The proposed method has been tested on a database of old music scores from the seventeenth to nineteenth centuries, achieving a recognition rate of about 92% with 20 writers. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1433-2833 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; CAT;CIC | Approved | no | ||
| Call Number | FLS2010b | Serial | 1319 | ||
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| Author | Sergio Escalera; Oriol Pujol; Petia Radeva | ||||
| Title | Error-Correcting Output Codes Library | Type | Journal Article | ||
| Year | 2010 | Publication | Journal of Machine Learning Research | Abbreviated Journal | JMLR |
| Volume |
11 | Issue | Pages | 661-664 | |
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| Abstract | (Feb):661−664
In this paper, we present an open source Error-Correcting Output Codes (ECOC) library. The ECOC framework is a powerful tool to deal with multi-class categorization problems. This library contains both state-of-the-art coding (one-versus-one, one-versus-all, dense random, sparse random, DECOC, forest-ECOC, and ECOC-ONE) and decoding designs (hamming, euclidean, inverse hamming, laplacian, β-density, attenuated, loss-based, probabilistic kernel-based, and loss-weighted) with the parameters defined by the authors, as well as the option to include your own coding, decoding, and base classifier. |
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1532-4435 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | MILAB;HUPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPR2010c | Serial | 1286 | ||
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| Author | Antonio Lopez; Joan Serrat; Cristina Cañero; Felipe Lumbreras; T. Graf | ||||
| Title | Robust lane markings detection and road geometry computation | Type | Journal Article | ||
| Year | 2010 | Publication | International Journal of Automotive Technology | Abbreviated Journal | IJAT |
| Volume |
11 | Issue | 3 | Pages | 395–407 |
| Keywords | lane markings | ||||
| Abstract | Detection of lane markings based on a camera sensor can be a low-cost solution to lane departure and curve-over-speed warnings. A number of methods and implementations have been reported in the literature. However, reliable detection is still an issue because of cast shadows, worn and occluded markings, variable ambient lighting conditions, for example. We focus on increasing detection reliability in two ways. First, we employed an image feature other than the commonly used edges: ridges, which we claim addresses this problem better. Second, we adapted RANSAC, a generic robust estimation method, to fit a parametric model of a pair of lane lines to the image features, based on both ridgeness and ridge orientation. In addition, the model was fitted for the left and right lane lines simultaneously to enforce a consistent result. Four measures of interest for driver assistance applications were directly computed from the fitted parametric model at each frame: lane width, lane curvature, and vehicle yaw angle and lateral offset with regard the lane medial axis. We qualitatively assessed our method in video sequences captured on several road types and under very different lighting conditions. We also quantitatively assessed it on synthetic but realistic video sequences for which road geometry and vehicle trajectory ground truth are known. | ||||
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| Publisher | The Korean Society of Automotive Engineers | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1229-9138 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ LSC2010 | Serial | 1300 | ||
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