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| Author | Jiaolong Xu; David Vazquez; Sebastian Ramos; Antonio Lopez; Daniel Ponsa | ||||
| Title | Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers | Type | Conference Article | ||
Year  |
2013 | Publication | CVPR Workshop on Ground Truth – What is a good dataset? | Abbreviated Journal | |
| Volume | Issue | Pages | 688 - 693 | ||
| Keywords | Pedestrian Detection; Domain Adaptation | ||||
| Abstract | Training vision-based pedestrian detectors using synthetic datasets (virtual world) is a useful technique to collect automatically the training examples with their pixel-wise ground truth. However, as it is often the case, these detectors must operate in real-world images, experiencing a significant drop of their performance. In fact, this effect also occurs among different real-world datasets, i.e. detectors' accuracy drops when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, in order to avoid this problem, it is required to adapt the detector trained with synthetic data to operate in the real-world scenario. In this paper, we propose a domain adaptation approach based on boosting LDA exemplar classifiers from both virtual and real worlds. We evaluate our proposal on multiple real-world pedestrian detection datasets. The results show that our method can efficiently adapt the exemplar classifiers from virtual to real world, avoiding drops in average precision over the 15%. | ||||
| Address | Portland; oregon; June 2013 | ||||
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| Language | English | Summary Language | English | Original Title | |
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| Area | Expedition | Conference | CVPRW | ||
| Notes | ADAS; 600.054; 600.057; 601.217 | Approved | yes | ||
| Call Number | XVR2013; ADAS @ adas @ xvr2013a | Serial | 2220 | ||
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| Author | Ivet Rafegas | ||||
| Title | Exploring Low-Level Vision Models. Case Study: Saliency Prediction | Type | Report | ||
| Year |
2013 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume | 175 | Issue | Pages | ||
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| Corporate Author | Thesis | Master's thesis | |||
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| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ Raf2013 | Serial | 2409 | ||
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| Author | Francesco Brughi | ||||
| Title | Artistic Heritage Motive Retrieval: an Explorative Study | Type | Report | ||
| Year |
2013 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume | 176 | Issue | Pages | ||
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| Corporate Author | Thesis | Master's thesis | |||
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| Notes | IAM | Approved | no | ||
| Call Number | Admin @ si @ Bru2013 | Serial | 2410 | ||
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| Author | Bhaskar Chakraborty; Jordi Gonzalez; Xavier Roca | ||||
| Title | Large scale continuous visual event recognition using max-margin Hough transformation framework | Type | Journal Article | ||
| Year |
2013 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
| Volume | 117 | Issue | 10 | Pages | 1356–1368 |
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| Abstract | In this paper we propose a novel method for continuous visual event recognition (CVER) on a large scale video dataset using max-margin Hough transformation framework. Due to high scalability, diverse real environmental state and wide scene variability direct application of action recognition/detection methods such as spatio-temporal interest point (STIP)-local feature based technique, on the whole dataset is practically infeasible. To address this problem, we apply a motion region extraction technique which is based on motion segmentation and region clustering to identify possible candidate “event of interest” as a preprocessing step. On these candidate regions a STIP detector is applied and local motion features are computed. For activity representation we use generalized Hough transform framework where each feature point casts a weighted vote for possible activity class centre. A max-margin frame work is applied to learn the feature codebook weight. For activity detection, peaks in the Hough voting space are taken into account and initial event hypothesis is generated using the spatio-temporal information of the participating STIPs. For event recognition a verification Support Vector Machine is used. An extensive evaluation on benchmark large scale video surveillance dataset (VIRAT) and as well on a small scale benchmark dataset (MSR) shows that the proposed method is applicable on a wide range of continuous visual event recognition applications having extremely challenging conditions. | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1077-3142 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ISE | Approved | no | ||
| Call Number | Admin @ si @ CGR2013 | Serial | 2413 | ||
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| Author | Ferran Poveda | ||||
| Title | Computer Graphics and Vision Techniques for the Study of the Muscular Fiber Architecture of the Myocardium | Type | Book Whole | ||
| Year |
2013 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Place of Publication | Editor | Debora Gil;Enric Marti | ||
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| Notes | IAM | Approved | no | ||
| Call Number | Admin @ si @ Pov2013 | Serial | 2417 | ||
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| Author | Miquel Ferrer; I. Bardaji; Ernest Valveny; Dimosthenis Karatzas; Horst Bunke | ||||
| Title | Median Graph Computation by Means of Graph Embedding into Vector Spaces | Type | Book Chapter | ||
| Year |
2013 | Publication | Graph Embedding for Pattern Analysis | Abbreviated Journal | |
| Volume | Issue | Pages | 45-72 | ||
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| Abstract | In pattern recognition [8, 14], a key issue to be addressed when designing a system is how to represent input patterns. Feature vectors is a common option. That is, a set of numerical features describing relevant properties of the pattern are computed and arranged in a vector form. The main advantages of this kind of representation are computational simplicity and a well sound mathematical foundation. Thus, a large number of operations are available to work with vectors and a large repository of algorithms for pattern analysis and classification exist. However, the simple structure of feature vectors might not be the best option for complex patterns where nonnumerical features or relations between different parts of the pattern become relevant. | ||||
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| Publisher | Springer New York | Place of Publication | Editor | Yun Fu; Yungian Ma | |
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-4614-4456-5 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ FBV2013 | Serial | 2421 | ||
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| Author | Mirko Arnold; Anarta Ghosh; Glen Doherty; Hugh Mulcahy; Stephen Patchett; Gerard Lacey | ||||
| Title | Towards Automatic Direct Observation of Procedure and Skill (DOPS) in Colonoscopy | Type | Conference Article | ||
| Year |
2013 | Publication | Proceedings of the International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | Issue | Pages | 48-53 | ||
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| Area | 800 | Expedition | Conference | VISIGRAPP | |
| Notes | MV | Approved | no | ||
| Call Number | fernando @ fernando @ | Serial | 2427 | ||
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| Author | Christophe Rigaud; Dimosthenis Karatzas; Jean-Christophe Burie; Jean-Marc Ogier | ||||
| Title | Speech balloon contour classification in comics | Type | Conference Article | ||
| Year |
2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
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| Abstract | Comic books digitization combined with subsequent comic book understanding create a variety of new applications, including mobile reading and data mining. Document understanding in this domain is challenging as comics are semi-structured documents, combining semantically important graphical and textual parts. In this work we detail a novel approach for classifying speech balloon in scanned comics book pages based on their contour time series. | ||||
| Address | Bethlehem; PA; USA; August 2013 | ||||
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| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | GREC | ||
| Notes | DAG; 600.056 | Approved | no | ||
| Call Number | Admin @ si @ RKB2013 | Serial | 2429 | ||
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| Author | J.S. Cope; P.Remagnino; S.Mannan; Katerine Diaz; Francesc J. Ferri; P.Wilkin | ||||
| Title | Reverse Engineering Expert Visual Observations: From Fixations To The Learning Of Spatial Filters With A Neural-Gas Algorithm | Type | Journal Article | ||
| Year |
2013 | Publication | Expert Systems with Applications | Abbreviated Journal | EXWA |
| Volume | 40 | Issue | 17 | Pages | 6707-6712 |
| Keywords | Neural gas; Expert vision; Eye-tracking; Fixations | ||||
| Abstract | Human beings can become experts in performing specific vision tasks, for example, doctors analysing medical images, or botanists studying leaves. With sufficient knowledge and experience, people can become very efficient at such tasks. When attempting to perform these tasks with a machine vision system, it would be highly beneficial to be able to replicate the process which the expert undergoes. Advances in eye-tracking technology can provide data to allow us to discover the manner in which an expert studies an image. This paper presents a first step towards utilizing these data for computer vision purposes. A growing-neural-gas algorithm is used to learn a set of Gabor filters which give high responses to image regions which a human expert fixated on. These filters can then be used to identify regions in other images which are likely to be useful for a given vision task. The algorithm is evaluated by learning filters for locating specific areas of plant leaves. | ||||
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| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0957-4174 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ CRM2013 | Serial | 2438 | ||
| Permanent link to this record | |||||
| Author | Katerine Diaz; Francesc J. Ferri; W. Diaz | ||||
| Title | Fast Approximated Discriminative Common Vectors using rank-one SVD updates | Type | Conference Article | ||
| Year |
2013 | Publication | 20th International Conference On Neural Information Processing | Abbreviated Journal | |
| Volume | 8228 | Issue | III | Pages | 368-375 |
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| Abstract | An efficient incremental approach to the discriminative common vector (DCV) method for dimensionality reduction and classification is presented. The proposal consists of a rank-one update along with an adaptive restriction on the rank of the null space which leads to an approximate but convenient solution. The algorithm can be implemented very efficiently in terms of matrix operations and space complexity, which enables its use in large-scale dynamic application domains. Deep comparative experimentation using publicly available high dimensional image datasets has been carried out in order to properly assess the proposed algorithm against several recent incremental formulations.
K. Diaz-Chito, F.J. Ferri, W. Diaz |
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| Address | Daegu; Korea; November 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-42050-4 | Medium | |
| Area | Expedition | Conference | ICONIP | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ DFD2013 | Serial | 2439 | ||
| Permanent link to this record | |||||
| Author | Katerine Diaz; Francesc J. Ferri | ||||
| Title | Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes | Type | Book Whole | ||
| Year |
2013 | Publication | Extensiones del método de vectores comunes discriminantes Aplicadas a la clasificación de imágenes | Abbreviated Journal | |
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| Abstract | Los métodos basados en subespacios son una herramienta muy utilizada en aplicaciones de visión por computador. Aquí se presentan y validan algunos algoritmos que hemos propuesto en este campo de investigación. El primer algoritmo está relacionado con una extensión del método de vectores comunes discriminantes con kernel, que reinterpreta el espacio nulo de la matriz de dispersión intra-clase del conjunto de entrenamiento para obtener las características discriminantes. Dentro de los métodos basados en subespacios existen diferentes tipos de entrenamiento. Uno de los más populares, pero no por ello uno de los más eficientes, es el aprendizaje por lotes. En este tipo de aprendizaje, todas las muestras del conjunto de entrenamiento tienen que estar disponibles desde el inicio. De este modo, cuando nuevas muestras se ponen a disposición del algoritmo, el sistema tiene que ser reentrenado de nuevo desde cero. Una alternativa a este tipo de entrenamiento es el aprendizaje incremental. Aquí se proponen diferentes algoritmos incrementales del método de vectores comunes discriminantes. | ||||
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| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-639-55339-0 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ DiF2013 | Serial | 2440 | ||
| Permanent link to this record | |||||
| Author | Naveen Onkarappa | ||||
| Title | Optical Flow in Driver Assistance Systems | Type | Book Whole | ||
| Year |
2013 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Motion perception is one of the most important attributes of the human brain. Visual motion perception consists in inferring speed and direction of elements in a scene based on visual inputs. Analogously, computer vision is assisted by motion cues in the scene. Motion detection in computer vision is useful in solving problems such as segmentation, depth from motion, structure from motion, compression, navigation and many others. These problems are common in several applications, for instance, video surveillance, robot navigation and advanced driver assistance systems (ADAS). One of the most widely used techniques for motion detection is the optical flow estimation. The work in this thesis attempts to make optical flow suitable for the requirements and conditions of driving scenarios. In this context, a novel space-variant representation called reverse log-polar representation is proposed that is shown to be better than the traditional log-polar space-variant representation for ADAS. The space-variant representations reduce the amount of data to be processed. Another major contribution in this research is related to the analysis of the influence of specific characteristics from driving scenarios on the optical flow accuracy. Characteristics such as vehicle speed and
road texture are considered in the aforementioned analysis. From this study, it is inferred that the regularization weight has to be adapted according to the required error measure and for different speeds and road textures. It is also shown that polar represented optical flow suits driving scenarios where predominant motion is translation. Due to the requirements of such a study and by the lack of needed datasets a new synthetic dataset is presented; it contains: i) sequences of different speeds and road textures in an urban scenario; ii) sequences with complex motion of an on-board camera; and iii) sequences with additional moving vehicles in the scene. The ground-truth optical flow is generated by the ray-tracing technique. Further, few applications of optical flow in ADAS are shown. Firstly, a robust RANSAC based technique to estimate horizon line is proposed. Then, an egomotion estimation is presented to compare the proposed space-variant representation with the classical one. As a final contribution, a modification in the regularization term is proposed that notably improves the results in the ADAS applications. This adaptation is evaluated using a state of the art optical flow technique. The experiments on a public dataset (KITTI) validate the advantages of using the proposed modification. |
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| Address | Bellaterra | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Angel Sappa | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-940902-1-9 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ Nav2013 | Serial | 2447 | ||
| Permanent link to this record | |||||
| Author | Marcelo D. Pistarelli; Angel Sappa; Ricardo Toledo | ||||
| Title | Multispectral Stereo Image Correspondence | Type | Conference Article | ||
| Year |
2013 | Publication | 15th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | |
| Volume | 8048 | Issue | Pages | 217-224 | |
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| Abstract | This paper presents a novel multispectral stereo image correspondence approach. It is evaluated using a stereo rig constructed with a visible spectrum camera and a long wave infrared spectrum camera. The novelty of the proposed approach lies on the usage of Hough space as a correspondence search domain. In this way it avoids searching for correspondence in the original multispectral image domains, where information is low correlated, and a common domain is used. The proposed approach is intended to be used in outdoor urban scenarios, where images contain large amount of edges. These edges are used as distinctive characteristics for the matching in the Hough space. Experimental results are provided showing the validity of the proposed approach. | ||||
| Address | York; uk; August 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-40245-6 | Medium | |
| Area | Expedition | Conference | CAIP | ||
| Notes | ADAS; 600.055 | Approved | no | ||
| Call Number | Admin @ si @ PST2013 | Serial | 2561 | ||
| Permanent link to this record | |||||
| Author | Gioacchino Vino; Angel Sappa | ||||
| Title | Revisiting Harris Corner Detector Algorithm: a Gradual Thresholding Approach | Type | Conference Article | ||
| Year |
2013 | Publication | 10th International Conference on Image Analysis and Recognition | Abbreviated Journal | |
| Volume | 7950 | Issue | Pages | 354-363 | |
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| Abstract | This paper presents an adaptive thresholding approach intended to increase the number of detected corners, while reducing the amount of those ones corresponding to noisy data. The proposed approach works by using the classical Harris corner detector algorithm and overcome the difficulty in finding a general threshold that work well for all the images in a given data set by proposing a novel adaptive thresholding scheme. Initially, two thresholds are used to discern between strong corners and flat regions. Then, a region based criteria is used to discriminate between weak corners and noisy points in the midway interval. Experimental results show that the proposed approach has a better capability to reject false corners and, at the same time, to detect weak ones. Comparisons with the state of the art are provided showing the validity of the proposed approach. | ||||
| Address | Póvoa de Varzim; Portugal; June 2013 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-39093-7 | Medium | |
| Area | Expedition | Conference | ICIAR | ||
| Notes | ADAS; 600.055 | Approved | no | ||
| Call Number | Admin @ si @ ViS2013 | Serial | 2562 | ||
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| Author | Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez | ||||
| Title | DA-DPM Pedestrian Detection | Type | Conference Article | ||
| Year |
2013 | Publication | ICCV Workshop on Reconstruction meets Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Domain Adaptation; Pedestrian Detection | ||||
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| Area | Expedition | Conference | ICCVW-RR | ||
| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ XRV2013 | Serial | 2569 | ||
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