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| Author | David Roche; Debora Gil; Jesus Giraldo | ||||
| Title | Detecting loss of diversity for an efficient termination of EAs | Type | Conference Article | ||
| Year | 2013 | Publication | 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing | Abbreviated Journal | |
| Volume | Issue | Pages | 561 - 566 | ||
| Keywords | EA termination; EA population diversity; EA steady state | ||||
| Abstract | Termination of Evolutionary Algorithms (EA) at its steady state so that useless iterations are not performed is a main point for its efficient application to black-box problems. Many EA algorithms evolve while there is still diversity in their population and, thus, they could be terminated by analyzing the behavior some measures of EA population diversity. This paper presents a numeric approximation to steady states that can be used to detect the moment EA population has lost its diversity for EA termination. Our condition has been applied to 3 EA paradigms based on diversity and a selection of functions
covering the properties most relevant for EA convergence. Experiments show that our condition works regardless of the search space dimension and function landscape. |
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| Address | Timisoara; Rumania; | ||||
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| ISSN | ISBN | 978-1-4799-3035-7 | Medium | ||
| Area | Expedition | Conference | SYNASC | ||
| Notes | IAM; 600.044; 600.060; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ RGG2013c | Serial | 2299 | ||
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| Author | Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados; Tomokazu Sato; Masakazu Iwamura; Koichi Kise | ||||
| Title | Key-region detection for document images -applications to administrative document retrieval | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 230-234 | ||
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| Abstract | In this paper we argue that a key-region detector designed to take into account the special characteristics of document images can result in the detection of less and more meaningful key-regions. We propose a fast key-region detector able to capture aspects of the structural information of the document, and demonstrate its efficiency by comparing against standard detectors in an administrative document retrieval scenario. We show that using the proposed detector results to a smaller number of detected key-regions and higher performance without any drop in speed compared to standard state of the art detectors. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.056; 600.045 | Approved | no | ||
| Call Number | Admin @ si @ GRK2013b | Serial | 2293 | ||
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| Author | Andreas Fischer; Volkmar Frinken; Horst Bunke; Ching Y. Suen | ||||
| Title | Improving HMM-Based Keyword Spotting with Character Language Models | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 506-510 | ||
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| Abstract | Facing high error rates and slow recognition speed for full text transcription of unconstrained handwriting images, keyword spotting is a promising alternative to locate specific search terms within scanned document images. We have previously proposed a learning-based method for keyword spotting using character hidden Markov models that showed a high performance when compared with traditional template image matching. In the lexicon-free approach pursued, only the text appearance was taken into account for recognition. In this paper, we integrate character n-gram language models into the spotting system in order to provide an additional language context. On the modern IAM database as well as the historical George Washington database, we demonstrate that character language models significantly improve the spotting performance. | ||||
| Address | Washington; USA; August 2013 | ||||
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| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.045; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ FFB2013 | Serial | 2295 | ||
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| Author | Volkmar Frinken; Andreas Fischer; Carlos David Martinez Hinarejos | ||||
| Title | Handwriting Recognition in Historical Documents using Very Large Vocabularies | Type | Conference Article | ||
| Year | 2013 | Publication | 2nd International Workshop on Historical Document Imaging and Processing | Abbreviated Journal | |
| Volume | Issue | Pages | 67-72 | ||
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| Abstract | Language models are used in automatic transcription system to resolve ambiguities. This is done by limiting the vocabulary of words that can be recognized as well as estimating the n-gram probability of the words in the given text. In the context of historical documents, a non-unified spelling and the limited amount of written text pose a substantial problem for the selection of the recognizable vocabulary as well as the computation of the word probabilities. In this paper we propose for the transcription of historical Spanish text to keep the corpus for the n-gram limited to a sample of the target text, but expand the vocabulary with words gathered from external resources. We analyze the performance of such a transcription system with different sizes of external vocabularies and demonstrate the applicability and the significant increase in recognition accuracy of using up to 300 thousand external words. | ||||
| Address | Washington; USA; August 2013 | ||||
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| ISSN | ISBN | 978-1-4503-2115-0 | Medium | ||
| Area | Expedition | Conference | HIP | ||
| Notes | DAG; 600.056; 600.045; 600.061; 602.006; 602.101 | Approved | no | ||
| Call Number | Admin @ si @ FFM2013 | Serial | 2296 | ||
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| Author | Joost Van de Weijer; Fahad Shahbaz Khan | ||||
| Title | Fusing Color and Shape for Bag-of-Words Based Object Recognition | Type | Conference Article | ||
| Year | 2013 | Publication | 4th Computational Color Imaging Workshop | Abbreviated Journal | |
| Volume | 7786 | Issue | Pages | 25-34 | |
| Keywords | Object Recognition; color features; bag-of-words; image classification | ||||
| Abstract | In this article we provide an analysis of existing methods for the incorporation of color in bag-of-words based image representations. We propose a list of desired properties on which bases fusing methods can be compared. We discuss existing methods and indicate shortcomings of the two well-known fusing methods, namely early and late fusion. Several recent works have addressed these shortcomings by exploiting top-down information in the bag-of-words pipeline: color attention which is motivated from human vision, and Portmanteau vocabularies which are based on information theoretic compression of product vocabularies. We point out several remaining challenges in cue fusion and provide directions for future research. | ||||
| Address | Chiba; Japan; March 2013 | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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| ISSN | 0302-9743 | ISBN | 978-3-642-36699-4 | Medium | |
| Area | Expedition | Conference | CCIW | ||
| Notes | CIC; 600.048 | Approved | no | ||
| Call Number | Admin @ si @ WeK2013 | Serial | 2283 | ||
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| Author | Joost Van de Weijer; Fahad Shahbaz Khan; Marc Masana | ||||
| Title | Interactive Visual and Semantic Image Retrieval | Type | Book Chapter | ||
| Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications | Abbreviated Journal | |
| Volume | 48 | Issue | Pages | 31-35 | |
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| Abstract | One direct consequence of recent advances in digital visual data generation and the direct availability of this information through the World-Wide Web, is a urgent demand for efficient image retrieval systems. The objective of image retrieval is to allow users to efficiently browse through this abundance of images. Due to the non-expert nature of the majority of the internet users, such systems should be user friendly, and therefore avoid complex user interfaces. In this chapter we investigate how high-level information provided by recently developed object recognition techniques can improve interactive image retrieval. Wel apply a bagof- word based image representation method to automatically classify images in a number of categories. These additional labels are then applied to improve the image retrieval system. Next to these high-level semantic labels, we also apply a low-level image description to describe the composition and color scheme of the scene. Both descriptions are incorporated in a user feedback image retrieval setting. The main objective is to show that automatic labeling of images with semantic labels can improve image retrieval results. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Angel Sappa; Jordi Vitria | |
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
| Area | Expedition | Conference | |||
| Notes | CIC; 605.203; 600.048 | Approved | no | ||
| Call Number | Admin @ si @ WKC2013 | Serial | 2284 | ||
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| Author | Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg | ||||
| Title | Coloring Action Recognition in Still Images | Type | Journal Article | ||
| Year | 2013 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
| Volume | 105 | Issue | 3 | Pages | 205-221 |
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| Abstract | In this article we investigate the problem of human action recognition in static images. By action recognition we intend a class of problems which includes both action classification and action detection (i.e. simultaneous localization and classification). Bag-of-words image representations yield promising results for action classification, and deformable part models perform very well object detection. The representations for action recognition typically use only shape cues and ignore color information. Inspired by the recent success of color in image classification and object detection, we investigate the potential of color for action classification and detection in static images. We perform a comprehensive evaluation of color descriptors and fusion approaches for action recognition. Experiments were conducted on the three datasets most used for benchmarking action recognition in still images: Willow, PASCAL VOC 2010 and Stanford-40. Our experiments demonstrate that incorporating color information considerably improves recognition performance, and that a descriptor based on color names outperforms pure color descriptors. Our experiments demonstrate that late fusion of color and shape information outperforms other approaches on action recognition. Finally, we show that the different color–shape fusion approaches result in complementary information and combining them yields state-of-the-art performance for action classification. | ||||
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| Publisher | Springer US | Place of Publication | Editor | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0920-5691 | ISBN | Medium | ||
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| Notes | CIC; ADAS; 600.057; 600.048 | Approved | no | ||
| Call Number | Admin @ si @ KRW2013 | Serial | 2285 | ||
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| Author | Jorge Bernal; F. Javier Sanchez; Fernando Vilariño | ||||
| Title | Impact of Image Preprocessing Methods on Polyp Localization in Colonoscopy Frames | Type | Conference Article | ||
| Year | 2013 | Publication | 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society | Abbreviated Journal | |
| Volume | Issue | Pages | 7350 - 7354 | ||
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| Abstract | In this paper we present our image preprocessing methods as a key part of our automatic polyp localization scheme. These methods are used to assess the impact of different endoluminal scene elements when characterizing polyps. More precisely we tackle the influence of specular highlights, blood vessels and black mask surrounding the scene. Experimental results prove that the appropriate handling of these elements leads to a great improvement in polyp localization results. | ||||
| Address | Osaka; Japan; July 2013 | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1557-170X | ISBN | Medium | ||
| Area | 800 | Expedition | Conference | EMBC | |
| Notes | MV; 600.047; 600.060;SIAI | Approved | no | ||
| Call Number | Admin @ si @ BSV2013 | Serial | 2286 | ||
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| Author | Carles Fernandez; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca | ||||
| Title | Towards Ontological Cognitive System | Type | Book Chapter | ||
| Year | 2013 | Publication | Topics in Medical Image Processing and Computational Vision | Abbreviated Journal | |
| Volume | 8 | Issue | Pages | 87-99 | |
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| Abstract | The increasing ubiquitousness of digital information in our daily lives has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance footage. This raises a series of technological demands for automatic video understanding and management, which together with the compromising attentional limitations of human operators, have motivated the research community to guide its steps towards a better attainment of such capabilities. As a result, current trends on cognitive vision promise to recognize complex events and self-adapt to different environments, while managing and integrating several types of knowledge. Future directions suggest to reinforce the multi-modal fusion of information sources and the communication with end-users. | ||||
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| Publisher | Springer Netherlands | Place of Publication | Editor | ||
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| ISSN | 2212-9391 | ISBN | 978-94-007-0725-2 | Medium | |
| Area | Expedition | Conference | |||
| Notes | ISE; 605.203; 302.018; 600.049 | Approved | no | ||
| Call Number | Admin @ si @ FGT2013 | Serial | 2287 | ||
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| Author | Jordi Roca; C. Alejandro Parraga; Maria Vanrell | ||||
| Title | Chromatic settings and the structural color constancy index | Type | Journal Article | ||
| Year | 2013 | Publication | Journal of Vision | Abbreviated Journal | JV |
| Volume | 13 | Issue | 4-3 | Pages | 1-26 |
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| Abstract | Color constancy is usually measured by achromatic setting, asymmetric matching, or color naming paradigms, whose results are interpreted in terms of indexes and models that arguably do not capture the full complexity of the phenomenon. Here we propose a new paradigm, chromatic setting, which allows a more comprehensive characterization of color constancy through the measurement of multiple points in color space under immersive adaptation. We demonstrated its feasibility by assessing the consistency of subjects' responses over time. The paradigm was applied to two-dimensional (2-D) Mondrian stimuli under three different illuminants, and the results were used to fit a set of linear color constancy models. The use of multiple colors improved the precision of more complex linear models compared to the popular diagonal model computed from gray. Our results show that a diagonal plus translation matrix that models mechanisms other than cone gain might be best suited to explain the phenomenon. Additionally, we calculated a number of color constancy indices for several points in color space, and our results suggest that interrelations among colors are not as uniform as previously believed. To account for this variability, we developed a new structural color constancy index that takes into account the magnitude and orientation of the chromatic shift in addition to the interrelations among colors and memory effects. | ||||
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| Notes | CIC; 600.052; 600.051; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ RPV2013 | Serial | 2288 | ||
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| Author | Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga | ||||
| Title | Low-level SpatioChromatic Grouping for Saliency Estimation | Type | Journal Article | ||
| Year | 2013 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 35 | Issue | 11 | Pages | 2810-2816 |
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| Abstract | We propose a saliency model termed SIM (saliency by induction mechanisms), which is based on a low-level spatiochromatic model that has successfully predicted chromatic induction phenomena. In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient. Moreover, SIM adds geometrical grouplets to enhance complex low-level features such as corners, and suppress relatively simpler features such as edges. Since our model has been fitted on psychophysical chromatic induction data, it is largely nonparametric. SIM outperforms state-of-the-art methods in predicting eye fixations on two datasets and using two metrics. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0162-8828 | ISBN | Medium | ||
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| Notes | CIC; 600.051; 600.052; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ MVO2013 | Serial | 2289 | ||
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| Author | Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Apostolos Antonacopoulos; Josep Llados | ||||
| Title | An interactive appearance-based document retrieval system for historical newspapers | Type | Conference Article | ||
| Year | 2013 | Publication | Proceedings of the International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | Issue | Pages | 84-87 | ||
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| Abstract | In this paper we present a retrieval-based application aimed at assisting a user to semi-automatically segment an incoming flow of historical newspaper images by automatically detecting a particular type of pages based on their appearance. A visual descriptor is used to assess page similarity while a relevance feedback process allow refining the results iteratively. The application is tested on a large dataset of digitised historic newspapers. | ||||
| Address | Barcelona; February 2013 | ||||
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| Area | Expedition | Conference | VISAPP | ||
| Notes | DAG; 600.056; 600.045; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ GRK2013a | Serial | 2290 | ||
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| Author | Jaume Gibert; Ernest Valveny; Horst Bunke | ||||
| Title | Embedding of Graphs with Discrete Attributes Via Label Frequencies | Type | Journal Article | ||
| Year | 2013 | Publication | International Journal of Pattern Recognition and Artificial Intelligence | Abbreviated Journal | IJPRAI |
| Volume | 27 | Issue | 3 | Pages | 1360002-1360029 |
| Keywords | Discrete attributed graphs; graph embedding; graph classification | ||||
| Abstract | Graph-based representations of patterns are very flexible and powerful, but they are not easily processed due to the lack of learning algorithms in the domain of graphs. Embedding a graph into a vector space solves this problem since graphs are turned into feature vectors and thus all the statistical learning machinery becomes available for graph input patterns. In this work we present a new way of embedding discrete attributed graphs into vector spaces using node and edge label frequencies. The methodology is experimentally tested on graph classification problems, using patterns of different nature, and it is shown to be competitive to state-of-the-art classification algorithms for graphs, while being computationally much more efficient. | ||||
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| Notes | DAG | Approved | no | ||
| Call Number | Admin @ si @ GVB2013 | Serial | 2305 | ||
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| Author | Muhammad Anwer Rao | ||||
| Title | Color for Object Detection and Action Recognition | Type | Book Whole | ||
| Year | 2013 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Recognizing object categories in real world images is a challenging problem in computer vision. The deformable part based framework is currently the most successful approach for object detection. Generally, HOG are used for image representation within the part-based framework. For action recognition, the bag-of-word framework has shown to provide promising results. Within the bag-of-words framework, local image patches are described by SIFT descriptor. Contrary to object detection and action recognition, combining color and shape has shown to provide the best performance for object and scene recognition.
In the first part of this thesis, we analyze the problem of person detection in still images. Standard person detection approaches rely on intensity based features for image representation while ignoring the color. Channel based descriptors is one of the most commonly used approaches in object recognition. This inspires us to evaluate incorporating color information using the channel based fusion approach for the task of person detection. In the second part of the thesis, we investigate the problem of object detection in still images. Due to high dimensionality, channel based fusion increases the computational cost. Moreover, channel based fusion has been found to obtain inferior results for object category where one of the visual varies significantly. On the other hand, late fusion is known to provide improved results for a wide range of object categories. A consequence of late fusion strategy is the need of a pure color descriptor. Therefore, we propose to use Color attributes as an explicit color representation for object detection. Color attributes are compact and computationally efficient. Consequently color attributes are combined with traditional shape features providing excellent results for object detection task. Finally, we focus on the problem of action detection and classification in still images. We investigate the potential of color for action classification and detection in still images. We also evaluate different fusion approaches for combining color and shape information for action recognition. Additionally, an analysis is performed to validate the contribution of color for action recognition. Our results clearly demonstrate that combining color and shape information significantly improve the performance of both action classification and detection in still images. |
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| Address | Barcelona | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Antonio Lopez;Joost Van de Weijer | |
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ Rao2013 | Serial | 2281 | ||
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| Author | Javier Marin | ||||
| Title | Pedestrian Detection Based on Local Experts | Type | Book Whole | ||
| Year | 2013 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | During the last decade vision-based human detection systems have started to play a key rolein multiple applications linked to driver assistance, surveillance, robot sensing and home automation.
Detecting humans is by far one of the most challenging tasks in Computer Vision. This is mainly due to the high degree of variability in the human appearanceassociated to the clothing, pose, shape and size. Besides, other factors such as cluttered scenarios, partial occlusions, or environmental conditions can make the detection task even harder. Most promising methods of the state-of-the-art rely on discriminative learning paradigms which are fed with positive and negative examples. The training data is one of the most relevant elements in order to build a robust detector as it has to cope the large variability of the target. In order to create this dataset human supervision is required. The drawback at this point is the arduous effort of annotating as well as looking for such claimed variability. In this PhD thesis we address two recurrent problems in the literature. In the first stage,we aim to reduce the consuming task of annotating, namely, by using computer graphics. More concretely, we develop a virtual urban scenario for later generating a pedestrian dataset. Then, we train a detector using this dataset, and finally we assess if this detector can be successfully applied in a real scenario. In the second stage, we focus on increasing the robustness of our pedestrian detectors under partial occlusions. In particular, we present a novel occlusion handling approach to increase the performance of block-based holistic methods under partial occlusions. For this purpose, we make use of local experts via a RandomSubspaceMethod (RSM) to handle these cases. If the method infers a possible partial occlusion, then the RSM, based on performance statistics obtained from partially occluded data, is applied. The last objective of this thesis is to propose a robust pedestrian detector based on an ensemble of local experts. To achieve this goal, we use the random forest paradigm, where the trees act as ensembles an their nodesare the local experts. In particular, each expert focus on performing a robust classification ofa pedestrian body patch. This approach offers computational efficiency and far less design complexity when compared to other state-of-the-artmethods, while reaching better accuracy |
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| Address | Barcelona | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Antonio Lopez;Jaume Amores | |
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ Mar2013 | Serial | 2280 | ||
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