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| Author | Hassan Ahmed Sial |
 
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| Title | Estimating Light Effects from a Single Image: Deep Architectures and Ground-Truth Generation | Type | Book Whole | |||
| Year | 2021 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | ||
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| Abstract | In this thesis, we explore how to estimate the effects of the light interacting with the scene objects from a single image. To achieve this goal, we focus on recovering intrinsic components like reflectance, shading, or light properties such as color and position using deep architectures. The success of these approaches relies on training on large and diversified image datasets. Therefore, we present several contributions on this such as: (a) a data-augmentation technique; (b) a ground-truth for an existing multi-illuminant dataset; (c) a family of synthetic datasets, SID for Surreal Intrinsic Datasets, with diversified backgrounds and coherent light conditions; and (d) a practical pipeline to create hybrid ground-truths to overcome the complexity of acquiring realistic light conditions in a massive way. In parallel with the creation of datasets, we trained different flexible encoder-decoder deep architectures incorporating physical constraints from the image formation models.
In the last part of the thesis, we apply all the previous experience to two different problems. Firstly, we create a large hybrid Doc3DShade dataset with real shading and synthetic reflectance under complex illumination conditions, that is used to train a two-stage architecture that improves the character recognition task in complex lighting conditions of unwrapped documents. Secondly, we tackle the problem of single image scene relighting by extending both, the SID dataset to present stronger shading and shadows effects, and the deep architectures to use intrinsic components to estimate new relit images. |
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| Address | September 2021 | |||||
| Corporate Author | Thesis | Ph.D. thesis | ||||
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IMPRIMA | Place of Publication | Editor | Maria Vanrell;Ramon Baldrich | ||
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| ISSN | ISBN | 978-84-122714-8-5 | Medium | |||
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| Notes | CIC; | Approved | no | |||
| Call Number | Admin @ si @ Sia2021 | Serial | 3607 | |||
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| Author | Joost Van de Weijer; Robert Benavente; Maria Vanrell; Cordelia Schmid; Ramon Baldrich; Jacob Verbeek; Diane Larlus |
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| Title | Color Naming | Type | Book Chapter | |||
| Year | 2012 | Publication | Color in Computer Vision: Fundamentals and Applications | Abbreviated Journal | ||
| Volume | Issue | 17 | Pages | 287-317 | ||
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John Wiley & Sons, Ltd. | Place of Publication | Editor | Theo Gevers;Arjan Gijsenij;Joost Van de Weijer;Jan-Mark Geusebroek | ||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ WBV2012 | Serial | 2063 | |||
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| Author | Joost Van de Weijer; Shida Beigpour |
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| Title | The Dichromatic Reflection Model: Future Research Directions and Applications | Type | Conference Article | |||
| Year | 2011 | Publication | International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications | Abbreviated Journal | ||
| Volume | Issue | Pages | ||||
| Keywords | dblp | |||||
| Abstract | The dichromatic reflection model (DRM) predicts that color distributions form a parallelogram in color space, whose shape is defined by the body reflectance and the illuminant color. In this paper we resume the assumptions which led to the DRM and shortly recall two of its main applications domains: color image segmentation and photometric invariant feature computation. After having introduced the model we discuss several limitations of the theory, especially those which are raised once working on real-world uncalibrated images. In addition, we summerize recent extensions of the model which allow to handle more complicated light interactions. Finally, we suggest some future research directions which would further extend its applicability. | |||||
| Address | Algarve, Portugal | |||||
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SciTePress | Place of Publication | Editor | Mestetskiy, Leonid and Braz, José | ||
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| ISSN | ISBN | 978-989-8425-47-8 | Medium | |||
| Area | Expedition | Conference | VISIGRAPP | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ WeB2011 | Serial | 1778 | |||
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| Author | Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
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| Title | 3D Texton Spaces for color-texture retrieval | Type | Conference Article | |||
| Year | 2010 | Publication | 7th International Conference on Image Analysis and Recognition | Abbreviated Journal | ||
| Volume | 6111 | Issue | Pages | 354–363 | ||
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| Abstract | Color and texture are visual cues of different nature, their integration in an useful visual descriptor is not an easy problem. One way to combine both features is to compute spatial texture descriptors independently on each color channel. Another way is to do the integration at the descriptor level. In this case the problem of normalizing both cues arises. In this paper we solve the latest problem by fusing color and texture through distances in texton spaces. Textons are the attributes of image blobs and they are responsible for texture discrimination as defined in Julesz’s Texton theory. We describe them in two low-dimensional and uniform spaces, namely, shape and color. The dissimilarity between color texture images is computed by combining the distances in these two spaces. Following this approach, we propose our TCD descriptor which outperforms current state of art methods in the two different approaches mentioned above, early combination with LBP and late combination with MPEG-7. This is done on an image retrieval experiment over a highly diverse texture dataset from Corel. | |||||
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Springer Berlin Heidelberg | Place of Publication | Editor | A.C. Campilho and M.S. Kamel | ||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | |||
| Series Volume | Series Issue | Edition | ||||
| ISSN | 0302-9743 | ISBN | 978-3-642-13771-6 | Medium | ||
| Area | Expedition | Conference | ICIAR | |||
| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ ASV2010a | Serial | 1325 | |||
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| Author | Joost Van de Weijer; Fahad Shahbaz Khan |
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| 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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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 |
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| 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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Springer Berlin Heidelberg | Place of Publication | Editor | Angel Sappa; Jordi Vitria | ||
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| 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 | Abel Gonzalez-Garcia; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga |
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| Title | Coloresia: An Interactive Colour Perception Device for the Visually Impaired | Type | Book Chapter | |||
| Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications | Abbreviated Journal | ||
| Volume | 48 | Issue | Pages | 47-66 | ||
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| Abstract | A significative percentage of the human population suffer from impairments in their capacity to distinguish or even see colours. For them, everyday tasks like navigating through a train or metro network map becomes demanding. We present a novel technique for extracting colour information from everyday natural stimuli and presenting it to visually impaired users as pleasant, non-invasive sound. This technique was implemented inside a Personal Digital Assistant (PDA) portable device. In this implementation, colour information is extracted from the input image and categorised according to how human observers segment the colour space. This information is subsequently converted into sound and sent to the user via speakers or headphones. In the original implementation, it is possible for the user to send its feedback to reconfigure the system, however several features such as these were not implemented because the current technology is limited.We are confident that the full implementation will be possible in the near future as PDA technology improves. | |||||
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Springer Berlin Heidelberg | Place of Publication | Editor | |||
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| ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | ||
| Area | Expedition | Conference | ||||
| Notes | CIC; 600.052; 605.203 | Approved | no | |||
| Call Number | Admin @ si @ GBP2013 | Serial | 2266 | |||
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| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Sadiq Ali; Michael Felsberg |
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| Title | Evaluating the impact of color on texture recognition | Type | Conference Article | |||
| Year | 2013 | Publication | 15th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | ||
| Volume | 8047 | Issue | Pages | 154-162 | ||
| Keywords | Color; Texture; image representation | |||||
| Abstract | State-of-the-art texture descriptors typically operate on grey scale images while ignoring color information. A common way to obtain a joint color-texture representation is to combine the two visual cues at the pixel level. However, such an approach provides sub-optimal results for texture categorisation task.
In this paper we investigate how to optimally exploit color information for texture recognition. We evaluate a variety of color descriptors, popular in image classification, for texture categorisation. In addition we analyze different fusion approaches to combine color and texture cues. Experiments are conducted on the challenging scenes and 10 class texture datasets. Our experiments clearly suggest that in all cases color names provide the best performance. Late fusion is the best strategy to combine color and texture. By selecting the best color descriptor with optimal fusion strategy provides a gain of 5% to 8% compared to texture alone on scenes and texture datasets. |
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| Address | York; UK; August 2013 | |||||
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Springer Berlin Heidelberg | Place of Publication | Editor | |||
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| ISSN | 0302-9743 | ISBN | 978-3-642-40260-9 | Medium | ||
| Area | Expedition | Conference | CAIP | |||
| Notes | CIC; 600.048 | Approved | no | |||
| Call Number | Admin @ si @ KWA2013 | Serial | 2263 | |||
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| Author | Fahad Shahbaz Khan; Shida Beigpour; Joost Van de Weijer; Michael Felsberg |
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| Title | Painting-91: A Large Scale Database for Computational Painting Categorization | Type | Journal Article | |||
| Year | 2014 | Publication | Machine Vision and Applications | Abbreviated Journal | MVAP | |
| Volume | 25 | Issue | 6 | Pages | 1385-1397 | |
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| Abstract | Computer analysis of visual art, especially paintings, is an interesting cross-disciplinary research domain. Most of the research in the analysis of paintings involve medium to small range datasets with own specific settings. Interestingly, significant progress has been made in the field of object and scene recognition lately. A key factor in this success is the introduction and availability of benchmark datasets for evaluation. Surprisingly, such a benchmark setup is still missing in the area of computational painting categorization. In this work, we propose a novel large scale dataset of digital paintings. The dataset consists of paintings from 91 different painters. We further show three applications of our dataset namely: artist categorization, style classification and saliency detection. We investigate how local and global features popular in image classification perform for the tasks of artist and style categorization. For both categorization tasks, our experimental results suggest that combining multiple features significantly improves the final performance. We show that state-of-the-art computer vision methods can correctly classify 50 % of unseen paintings to its painter in a large dataset and correctly attribute its artistic style in over 60 % of the cases. Additionally, we explore the task of saliency detection on paintings and show experimental findings using state-of-the-art saliency estimation algorithms. | |||||
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Springer Berlin Heidelberg | Place of Publication | Editor | |||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 0932-8092 | ISBN | Medium | |||
| Area | Expedition | Conference | ||||
| Notes | CIC; LAMP; 600.074; 600.079 | Approved | no | |||
| Call Number | Admin @ si @ KBW2014 | Serial | 2510 | |||
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| Author | Aleksandr Setkov; Fabio Martinez Carillo; Michele Gouiffes; Christian Jacquemin; Maria Vanrell; Ramon Baldrich |
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| Title | DAcImPro: A Novel Database of Acquired Image Projections and Its Application to Object Recognition | Type | Conference Article | |||
| Year | 2015 | Publication | Advances in Visual Computing. Proceedings of 11th International Symposium, ISVC 2015 Part II | Abbreviated Journal | ||
| Volume | 9475 | Issue | Pages | 463-473 | ||
| Keywords | Projector-camera systems; Feature descriptors; Object recognition | |||||
| Abstract | Projector-camera systems are designed to improve the projection quality by comparing original images with their captured projections, which is usually complicated due to high photometric and geometric variations. Many research works address this problem using their own test data which makes it extremely difficult to compare different proposals. This paper has two main contributions. Firstly, we introduce a new database of acquired image projections (DAcImPro) that, covering photometric and geometric conditions and providing data for ground-truth computation, can serve to evaluate different algorithms in projector-camera systems. Secondly, a new object recognition scenario from acquired projections is presented, which could be of a great interest in such domains, as home video projections and public presentations. We show that the task is more challenging than the classical recognition problem and thus requires additional pre-processing, such as color compensation or projection area selection. | |||||
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Springer International Publishing | 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 | 978-3-319-27862-9 | Medium | ||
| Area | Expedition | Conference | ISVC | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ SMG2015 | Serial | 2736 | |||
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| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
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| Title | Modulating Shape Features by Color Attention for Object Recognition | Type | Journal Article | |||
| Year | 2012 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV | |
| Volume | 98 | Issue | 1 | Pages | 49-64 | |
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| Abstract | Bag-of-words based image representation is a successful approach for object recognition. Generally, the subsequent stages of the process: feature detection,feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, it was found that the combination of different image cues, such as shape and color, often obtains below expected results. This paper presents a novel method for recognizing object categories when using ultiple cues by separately processing the shape and color cues and combining them by modulating the shape features by category specific color attention. Color is used to compute bottom up and top-down attention maps. Subsequently, these color attention maps are used to modulate the weights of the shape features. In regions with higher attention shape features are given more weight than in regions with low attention. We compare our approach with existing methods that combine color and shape cues on five data sets containing varied importance of both cues, namely, Soccer (color predominance), Flower (color and hape parity), PASCAL VOC 2007 and 2009 (shape predominance) and Caltech-101 (color co-interference). The experiments clearly demonstrate that in all five data sets our proposed framework significantly outperforms existing methods for combining color and shape information. | |||||
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Springer Netherlands | Place of Publication | Editor | |||
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| ISSN | 0920-5691 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ KWV2012 | Serial | 1864 | |||
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| Author | Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg |
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| 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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Springer US | Place of Publication | Editor | |||
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| 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 | Francesc Tous; Agnes Borras; Robert Benavente; Ramon Baldrich; Maria Vanrell; Josep Llados |
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| Title | Textual Descriptions for Browsing People by Visual Apperance. | Type | Book Chapter | |||
| Year | 2002 | Publication | Lecture Notes in Artificial Intelligence | Abbreviated Journal | ||
| Volume | 2504 | Issue | Pages | 419-429 | ||
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| Abstract | This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building | |||||
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Springer Verlag | Place of Publication | Editor | |||
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| Notes | DAG;CIC | Approved | no | |||
| Call Number | CAT @ cat @ TBB2002b | Serial | 319 | |||
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| Author | Alicia Fornes; Josep Llados; Gemma Sanchez; Xavier Otazu; Horst Bunke |
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| 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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Springer-Verlag | Place of Publication | Editor | |||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 1433-2833 | ISBN | Medium | |||
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| Notes | DAG; CAT;CIC | Approved | no | |||
| Call Number | FLS2010b | Serial | 1319 | |||
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| Author | Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich |
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| Title | Perception Based Representations for Computational Colour | Type | Conference Article | |||
| Year | 2011 | Publication | 3rd International Workshop on Computational Color Imaging | Abbreviated Journal | ||
| Volume | 6626 | Issue | Pages | 16-30 | ||
| Keywords | colour perception, induction, naming, psychophysical data, saliency, segmentation | |||||
| Abstract | The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space. | |||||
| Address | Milan, Italy | |||||
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Springer-Verlag | Place of Publication | Editor | Raimondo Schettini, Shoji Tominaga, Alain Trémeau | ||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | |||
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| ISSN | ISBN | 978-3-642-20403-6 | Medium | |||
| Area | Expedition | Conference | CCIW | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ VMB2011 | Serial | 1733 | |||
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| Author | C. Alejandro Parraga |
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| Title | Color Vision, Computational Methods for | Type | Book Chapter | |||
| Year | 2014 | Publication | Encyclopedia of Computational Neuroscience | Abbreviated Journal | ||
| Volume | Issue | Pages | 1-11 | |||
| Keywords | Color computational vision; Computational neuroscience of color | |||||
| Abstract | The study of color vision has been aided by a whole battery of computational methods that attempt to describe the mechanisms that lead to our perception of colors in terms of the information-processing properties of the visual system. Their scope is highly interdisciplinary, linking apparently dissimilar disciplines such as mathematics, physics, computer science, neuroscience, cognitive science, and psychology. Since the sensation of color is a feature of our brains, computational approaches usually include biological features of neural systems in their descriptions, from retinal light-receptor interaction to subcortical color opponency, cortical signal decoding, and color categorization. They produce hypotheses that are usually tested by behavioral or psychophysical experiments. | |||||
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Springer-Verlag Berlin Heidelberg | Place of Publication | Editor | Dieter Jaeger; Ranu Jung | ||
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| ISSN | ISBN | 978-1-4614-7320-6 | Medium | |||
| Area | Expedition | Conference | ||||
| Notes | CIC; 600.074 | Approved | no | |||
| Call Number | Admin @ si @ Par2014 | Serial | 2512 | |||
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| Author | Olivier Penacchio |
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| Title | Mixed Hodge Structures and Equivariant Sheaves on the Projective Plane | Type | Journal Article | |||
| Year | 2011 | Publication | Mathematische Nachrichten | Abbreviated Journal | MN | |
| Volume | 284 | Issue | 4 | Pages | 526-542 | |
| Keywords | Mixed Hodge structures, equivariant sheaves, MSC (2010) Primary: 14C30, Secondary: 14F05, 14M25 | |||||
| Abstract | We describe an equivalence of categories between the category of mixed Hodge structures and a category of equivariant vector bundles on a toric model of the complex projective plane which verify some semistability condition. We then apply this correspondence to define an invariant which generalizes the notion of R-split mixed Hodge structure and give calculations for the first group of cohomology of possibly non smooth or non-complete curves of genus 0 and 1. Finally, we describe some extension groups of mixed Hodge structures in terms of equivariant extensions of coherent sheaves. © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim | |||||
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| Publisher |
WILEY-VCH Verlag | Place of Publication | Editor | R. Mennicken | ||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | 1522-2616 | ISBN | Medium | |||
| Area | Expedition | Conference | ||||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ Pen2011 | Serial | 1721 | |||
| Permanent link to this record | ||||||