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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Impact of Image Preprocessing Methods on Polyp Localization in Colonoscopy Frames |
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Conference Article |
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Year |
2013 |
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35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
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7350 - 7354 |
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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. |
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Osaka; Japan; July 2013 |
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1557-170X |
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800 |
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EMBC |
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MV; 600.047; 600.060;SIAI |
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Admin @ si @ BSV2013 |
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2286 |
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Author |
Carles Fernandez; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca |
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Title |
Towards Ontological Cognitive System |
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Book Chapter |
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Year |
2013 |
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Topics in Medical Image Processing and Computational Vision |
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8 |
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87-99 |
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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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Springer Netherlands |
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2212-9391 |
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978-94-007-0725-2 |
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ISE; 605.203; 302.018; 600.049 |
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Admin @ si @ FGT2013 |
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2287 |
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Jordi Roca; C. Alejandro Parraga; Maria Vanrell |
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Title |
Chromatic settings and the structural color constancy index |
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Journal Article |
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Year |
2013 |
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Journal of Vision |
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JV |
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13 |
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4-3 |
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1-26 |
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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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CIC; 600.052; 600.051; 605.203 |
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Admin @ si @ RPV2013 |
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2288 |
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Author |
Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga |
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Title |
Low-level SpatioChromatic Grouping for Saliency Estimation |
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Journal Article |
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Year |
2013 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
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TPAMI |
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35 |
Issue |
11 |
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2810-2816 |
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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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0162-8828 |
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CIC; 600.051; 600.052; 605.203 |
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Admin @ si @ MVO2013 |
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2289 |
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Author |
Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Apostolos Antonacopoulos; Josep Llados |
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Title |
An interactive appearance-based document retrieval system for historical newspapers |
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Conference Article |
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Year |
2013 |
Publication |
Proceedings of the International Conference on Computer Vision Theory and Applications |
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84-87 |
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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. |
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Barcelona; February 2013 |
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VISAPP |
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DAG; 600.056; 600.045; 605.203 |
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no |
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Admin @ si @ GRK2013a |
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2290 |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
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Title |
Embedding of Graphs with Discrete Attributes Via Label Frequencies |
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Journal Article |
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Year |
2013 |
Publication |
International Journal of Pattern Recognition and Artificial Intelligence |
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IJPRAI |
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27 |
Issue |
3 |
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1360002-1360029 |
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Discrete attributed graphs; graph embedding; graph classification |
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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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DAG |
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no |
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Admin @ si @ GVB2013 |
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2305 |
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Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados |
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Title |
Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces |
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Book Chapter |
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2013 |
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Graph Embedding for Pattern Analysis |
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1-26 |
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Ability to recognize patterns is among the most crucial capabilities of human beings for their survival, which enables them to employ their sophisticated neural and cognitive systems [1], for processing complex audio, visual, smell, touch, and taste signals. Man is the most complex and the best existing system of pattern recognition. Without any explicit thinking, we continuously compare, classify, and identify huge amount of signal data everyday [2], starting from the time we get up in the morning till the last second we fall asleep. This includes recognizing the face of a friend in a crowd, a spoken word embedded in noise, the proper key to lock the door, smell of coffee, the voice of a favorite singer, the recognition of alphabetic characters, and millions of more tasks that we perform on regular basis. |
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Springer New York |
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978-1-4614-4456-5 |
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DAG |
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no |
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Admin @ si @ LRL2013b |
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2271 |
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Author |
Isabel Guitart; Jordi Conesa; Luis Villarejo; Agata Lapedriza; David Masip; Antoni Perez; Elena Planas |
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Title |
Opinion Mining on Educational Resources at the Open University of Catalonia |
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Conference Article |
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Year |
2013 |
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3rd International Workshop on Adaptive Learning via Interactive, Collaborative and Emotional approaches. In conjunction with CISIS 2013: The 7th International Conference on Complex, Intelligent, and Software Intensive Systems |
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385 - 390 |
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In order to make improvements to teaching, it is vital to know what students think of the way they are taught. With that purpose in mind, exhaustively analyzing the forums associated with the subjects taught at the Universitat Oberta de Cataluya (UOC) would be extremely helpful, as the university's students often post comments on their learning experiences in them. Exploiting the content of such forums is not a simple undertaking. The volume of data involved is very large, and performing the task manually would require a great deal of effort from lecturers. As a first step to solve this problem, we propose a tool to automatically analyze the posts in forums of communities of UOC students and teachers, with a view to systematically mining the opinions they contain. This article defines the architecture of such tool and explains how lexical-semantic and language technology resources can be used to that end. For pilot testing purposes, the tool has been used to identify students' opinions on the UOC's Business Intelligence master's degree course during the last two years. The paper discusses the results of such test. The contribution of this paper is twofold. Firstly, it demonstrates the feasibility of using natural language parsing techniques to help teachers to make decisions. Secondly, it introduces a simple tool that can be refined and adapted to a virtual environment for the purpose in question. |
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978-0-7695-4992-7 |
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ALICE |
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OR;MV |
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GCV2013 |
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2268 |
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Author |
Jose Manuel Alvarez; Theo Gevers; Ferran Diego; Antonio Lopez |
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Title |
Road Geometry Classification by Adaptative Shape Models |
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Journal Article |
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2013 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
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TITS |
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14 |
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1 |
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459-468 |
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road detection |
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Vision-based road detection is important for different applications in transportation, such as autonomous driving, vehicle collision warning, and pedestrian crossing detection. Common approaches to road detection are based on low-level road appearance (e.g., color or texture) and neglect of the scene geometry and context. Hence, using only low-level features makes these algorithms highly depend on structured roads, road homogeneity, and lighting conditions. Therefore, the aim of this paper is to classify road geometries for road detection through the analysis of scene composition and temporal coherence. Road geometry classification is proposed by building corresponding models from training images containing prototypical road geometries. We propose adaptive shape models where spatial pyramids are steered by the inherent spatial structure of road images. To reduce the influence of lighting variations, invariant features are used. Large-scale experiments show that the proposed road geometry classifier yields a high recognition rate of 73.57% ± 13.1, clearly outperforming other state-of-the-art methods. Including road shape information improves road detection results over existing appearance-based methods. Finally, it is shown that invariant features and temporal information provide robustness against disturbing imaging conditions. |
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1524-9050 |
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ADAS;ISE |
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Admin @ si @ AGD2013;; ADAS @ adas @ |
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2269 |
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Abel Gonzalez-Garcia; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga |
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Coloresia: An Interactive Colour Perception Device for the Visually Impaired |
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2013 |
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Multimodal Interaction in Image and Video Applications |
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48 |
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47-66 |
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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 |
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1868-4394 |
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978-3-642-35931-6 |
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CIC; 600.052; 605.203 |
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Admin @ si @ GBP2013 |
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2266 |
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Rahat Khan; Joost Van de Weijer; Dimosthenis Karatzas; Damien Muselet |
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Towards multispectral data acquisition with hand-held devices |
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Conference Article |
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2013 |
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20th IEEE International Conference on Image Processing |
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2053 - 2057 |
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Multispectral; mobile devices; color measurements |
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We propose a method to acquire multispectral data with handheld devices with front-mounted RGB cameras. We propose to use the display of the device as an illuminant while the camera captures images illuminated by the red, green and
blue primaries of the display. Three illuminants and three response functions of the camera lead to nine response values which are used for reflectance estimation. Results are promising and show that the accuracy of the spectral reconstruction improves in the range from 30-40% over the spectral
reconstruction based on a single illuminant. Furthermore, we propose to compute sensor-illuminant aware linear basis by discarding the part of the reflectances that falls in the sensorilluminant null-space. We show experimentally that optimizing reflectance estimation on these new basis functions decreases
the RMSE significantly over basis functions that are independent to sensor-illuminant. We conclude that, multispectral data acquisition is potentially possible with consumer hand-held devices such as tablets, mobiles, and laptops, opening up applications which are currently considered to be unrealistic. |
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Melbourne; Australia; September 2013 |
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ICIP |
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CIC; DAG; 600.048 |
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Admin @ si @ KWK2013b |
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2265 |
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Shida Beigpour; Marc Serra; Joost Van de Weijer; Robert Benavente; Maria Vanrell; Olivier Penacchio; Dimitris Samaras |
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Title |
Intrinsic Image Evaluation On Synthetic Complex Scenes |
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Conference Article |
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2013 |
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20th IEEE International Conference on Image Processing |
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285 - 289 |
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Scene decomposition into its illuminant, shading, and reflectance intrinsic images is an essential step for scene understanding. Collecting intrinsic image groundtruth data is a laborious task. The assumptions on which the ground-truth
procedures are based limit their application to simple scenes with a single object taken in the absence of indirect lighting and interreflections. We investigate synthetic data for intrinsic image research since the extraction of ground truth is straightforward, and it allows for scenes in more realistic situations (e.g, multiple illuminants and interreflections). With this dataset we aim to motivate researchers to further explore intrinsic image decomposition in complex scenes. |
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Melbourne; Australia; September 2013 |
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CIC; 600.048; 600.052; 600.051 |
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no |
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Admin @ si @ BSW2013 |
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2264 |
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Author |
Rahat Khan; Joost Van de Weijer; Fahad Shahbaz Khan; Damien Muselet; christophe Ducottet; Cecile Barat |
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Title |
Discriminative Color Descriptors |
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Conference Article |
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2013 |
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IEEE Conference on Computer Vision and Pattern Recognition |
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2866 - 2873 |
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Abstract |
Color description is a challenging task because of large variations in RGB values which occur due to scene accidental events, such as shadows, shading, specularities, illuminant color changes, and changes in viewing geometry. Traditionally, this challenge has been addressed by capturing the variations in physics-based models, and deriving invariants for the undesired variations. The drawback of this approach is that sets of distinguishable colors in the original color space are mapped to the same value in the photometric invariant space. This results in a drop of discriminative power of the color description. In this paper we take an information theoretic approach to color description. We cluster color values together based on their discriminative power in a classification problem. The clustering has the explicit objective to minimize the drop of mutual information of the final representation. We show that such a color description automatically learns a certain degree of photometric invariance. We also show that a universal color representation, which is based on other data sets than the one at hand, can obtain competing performance. Experiments show that the proposed descriptor outperforms existing photometric invariants. Furthermore, we show that combined with shape description these color descriptors obtain excellent results on four challenging datasets, namely, PASCAL VOC 2007, Flowers-102, Stanford dogs-120 and Birds-200. |
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Portland; Oregon; June 2013 |
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1063-6919 |
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CVPR |
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CIC; 600.048 |
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Admin @ si @ KWK2013a |
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2262 |
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Author |
Fahad Shahbaz Khan; Joost Van de Weijer; Sadiq Ali; Michael Felsberg |
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Evaluating the impact of color on texture recognition |
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Conference Article |
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2013 |
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15th International Conference on Computer Analysis of Images and Patterns |
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8047 |
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154-162 |
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Color; Texture; image representation |
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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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York; UK; August 2013 |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-40260-9 |
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CAIP |
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CIC; 600.048 |
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Admin @ si @ KWA2013 |
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2263 |
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Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier |
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Automatic text localisation in scanned comic books |
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2013 |
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Proceedings of the International Conference on Computer Vision Theory and Applications |
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814-819 |
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Text localization; comics; text/graphic separation; complex background; unstructured document |
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Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent document understanding enable direct content-based search as opposed to metadata only search (e.g. album title or author name). Few studies have been done in this direction. In this work we detail a novel approach for the automatic text localization in scanned comics book pages, an essential step towards a fully automatic comics book understanding. We focus on speech text as it is semantically important and represents the majority of the text present in comics. The approach is compared with existing methods of text localization found in the literature and results are presented. |
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Barcelona; February 2013 |
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VISAPP |
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DAG; CIC; 600.056 |
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Admin @ si @ RKW2013b |
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2261 |
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