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	Author	Abel Gonzalez-Garcia; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga
	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
	Keywords
	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.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	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	Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados
	Title	Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces			Type	Book Chapter
	Year	2013	Publication	Graph Embedding for Pattern Analysis	Abbreviated Journal
	Volume		Issue		Pages	1-26
	Keywords
	Abstract	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.
	Address
	Corporate Author				Thesis
	Publisher	Springer New York	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-4614-4456-5	Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ LRL2013b			Serial	2271
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	Author	A.S. Coquel; Jean-Pascal Jacob; M. Primet; A. Demarez; Mariella Dimiccoli; T. Julou; L. Moisan; A. Lindner; H. Berry
	Title	Localization of protein aggregation in Escherichia coli is governed by diffusion and nucleoid macromolecular crowding effect			Type	Journal Article
	Year	2013	Publication	Plos Computational Biology	Abbreviated Journal	PCB
	Volume	9	Issue	4	Pages
	Keywords
	Abstract	Aggregates of misfolded proteins are a hallmark of many age-related diseases. Recently, they have been linked to aging of Escherichia coli (E. coli) where protein aggregates accumulate at the old pole region of the aging bacterium. Because of the potential of E. coli as a model organism, elucidating aging and protein aggregation in this bacterium may pave the way to significant advances in our global understanding of aging. A first obstacle along this path is to decipher the mechanisms by which protein aggregates are targeted to specific intercellular locations. Here, using an integrated approach based on individual-based modeling, time-lapse fluorescence microscopy and automated image analysis, we show that the movement of aging-related protein aggregates in E. coli is purely diffusive (Brownian). Using single-particle tracking of protein aggregates in live E. coli cells, we estimated the average size and diffusion constant of the aggregates. Our results provide evidence that the aggregates passively diffuse within the cell, with diffusion constants that depend on their size in agreement with the Stokes-Einstein law. However, the aggregate displacements along the cell long axis are confined to a region that roughly corresponds to the nucleoid-free space in the cell pole, thus confirming the importance of increased macromolecular crowding in the nucleoids. We thus used 3D individual-based modeling to show that these three ingredients (diffusion, aggregation and diffusion hindrance in the nucleoids) are sufficient and necessary to reproduce the available experimental data on aggregate localization in the cells. Taken together, our results strongly support the hypothesis that the localization of aging-related protein aggregates in the poles of E. coli results from the coupling of passive diffusion-aggregation with spatially non-homogeneous macromolecular crowding. They further support the importance of “soft” intracellular structuring (based on macromolecular crowding) in diffusion-based protein localization in E. coli.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor	: Stanislav Shvartsman, Princeton University, United States of America
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Admin @ si @CJP2013			Serial	2786
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	Author	David Vazquez; Jiaolong Xu; Sebastian Ramos; Antonio Lopez; Daniel Ponsa
	Title	Weakly Supervised Automatic Annotation of Pedestrian Bounding Boxes			Type	Conference Article
	Year	2013	Publication	CVPR Workshop on Ground Truth – What is a good dataset?	Abbreviated Journal
	Volume		Issue		Pages	706 - 711
	Keywords	Pedestrian Detection; Domain Adaptation
	Abstract	Among the components of a pedestrian detector, its trained pedestrian classifier is crucial for achieving the desired performance. The initial task of the training process consists in collecting samples of pedestrians and background, which involves tiresome manual annotation of pedestrian bounding boxes (BBs). Thus, recent works have assessed the use of automatically collected samples from photo-realistic virtual worlds. However, learning from virtual-world samples and testing in real-world images may suffer the dataset shift problem. Accordingly, in this paper we assess an strategy to collect samples from the real world and retrain with them, thus avoiding the dataset shift, but in such a way that no BBs of real-world pedestrians have to be provided. In particular, we train a pedestrian classifier based on virtual-world samples (no human annotation required). Then, using such a classifier we collect pedestrian samples from real-world images by detection. After, a human oracle rejects the false detections efficiently (weak annotation). Finally, a new classifier is trained with the accepted detections. We show that this classifier is competitive with respect to the counterpart trained with samples collected by manually annotating hundreds of pedestrian BBs.
	Address	Portland; Oregon; June 2013
	Corporate Author				Thesis
	Publisher	IEEE	Place of Publication		Editor
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	CVPRW
	Notes	ADAS; 600.054; 600.057; 601.217			Approved	no
	Call Number	ADAS @ adas @ VXR2013a			Serial	2219
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	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
	Keywords
	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
	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
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	Author	Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny
	Title	Notation-invariant patch-based wall detector in architectural floor plans			Type	Book Chapter
	Year	2013	Publication	Graphics Recognition. New Trends and Challenges	Abbreviated Journal
	Volume	7423	Issue		Pages	79--88
	Keywords
	Abstract	Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper.
	Address
	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	978-3-642-36823-3	Medium
	Area		Expedition		Conference
	Notes	DAG; 600.045; 600.056; 605.203			Approved	no
	Call Number	Admin @ si @ HMS2013			Serial	2322
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	Author	Patricia Marquez; Debora Gil; Aura Hernandez-Sabate
	Title	Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality			Type	Conference Article
	Year	2013	Publication	ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars	Abbreviated Journal
	Volume		Issue		Pages	624-631
	Keywords
	Abstract	Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field.
	Address	Sydney; Australia; December 2013
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	CVTT:E2M
	Notes	IAM; ADAS; 600.044; 600.057; 601.145			Approved	no
	Call Number	Admin @ si @ MGH2013b			Serial	2351
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	Author	Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades
	Title	Document noise removal using sparse representations over learned dictionary			Type	Conference Article
	Year	2013	Publication	Symposium on Document engineering	Abbreviated Journal
	Volume		Issue		Pages	161-168
	Keywords
	Abstract	best paper award In this paper, we propose an algorithm for denoising document images using sparse representations. Following a training set, this algorithm is able to learn the main document characteristics and also, the kind of noise included into the documents. In this perspective, we propose to model the noise energy based on the normalized cross-correlation between pairs of noisy and non-noisy documents. Experimental results on several datasets demonstrate the robustness of our method compared with the state-of-the-art.
	Address	Barcelona; October 2013
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-4503-1789-4	Medium
	Area		Expedition		Conference	ACM-DocEng
	Notes	DAG; 600.061			Approved	no
	Call Number	Admin @ si @ DTR2013a			Serial	2330
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	Author	Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
	Title	Logo recognition Based on the Dempster-Shafer Fusion of Multiple Classifiers			Type	Conference Article
	Year	2013	Publication	26th Canadian Conference on Artificial Intelligence	Abbreviated Journal
	Volume	7884	Issue		Pages	1-12
	Keywords	Logo recognition; ensemble classification; Dempster-Shafer fusion; Zernike moments; generic Fourier descriptor; shape signature
	Abstract	Best paper award The performance of different feature extraction and shape description methods in trademark image recognition systems have been studied by several researchers. However, the potential improvement in classification through feature fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of three classifiers, each trained on different feature sets. Three promising shape description techniques, including Zernike moments, generic Fourier descriptors, and shape signature are used to extract informative features from logo images, and each set of features is fed into an individual classifier. In order to reduce recognition error, a powerful combination strategy based on the Dempster-Shafer theory is utilized to fuse the three classifiers trained on different sources of information. This combination strategy can effectively make use of diversity of base learners generated with different set of features. The recognition results of the individual classifiers are compared with those obtained from fusing the classifiers’ output, showing significant performance improvements of the proposed methodology.
	Address	Canada; May 2013
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-38456-1	Medium
	Area		Expedition		Conference	AI
	Notes	HuPBA;MILAB			Approved	no
	Call Number	Admin @ si @ BGE2013b			Serial	2249
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	Author	Victor Borjas; Jordi Vitria; Petia Radeva
	Title	Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments			Type	Conference Article
	Year	2013	Publication	13th IAPR Conference on Machine Vision Applications	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Best Poster AwardOne of the big challenges of today person detectors is the decreasing of the false positive rate. In this paper, we propose a novel framework to customize person detectors in static camera scenarios in order to reduce this rate. This scheme includes background modeling for subtraction based on gradient histograms and Mean-Shift clustering. Our experiments show that the detection improved compared to using only the output from the pedestrian detector reducing 87% of the false positives and therefore the overall precision of the detection was increased signicantly.
	Address	Kyoto; Japan; May 2013
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	MVA
	Notes	OR; MILAB;MV			Approved	no
	Call Number	BVR2013			Serial	2238
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	Author	Angel Sappa; Jordi Vitria
	Title	Multimodal Interaction in Image and Video Applications			Type	Book Whole
	Year	2013	Publication	Multimodal Interaction in Image and Video Applications	Abbreviated Journal
	Volume	48	Issue		Pages
	Keywords
	Abstract	Book Series Intelligent Systems Reference Library
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1868-4394	ISBN	978-3-642-35931-6	Medium
	Area		Expedition		Conference
	Notes	ADAS; OR;MV			Approved	no
	Call Number	Admin @ si @ SaV2013			Serial	2199
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	Author	Olivier Penacchio; Xavier Otazu; Laura Dempere-Marco
	Title	A Neurodynamical Model of Brightness Induction in V1			Type	Journal Article
	Year	2013	Publication	PloS ONE	Abbreviated Journal	Plos
	Volume	8	Issue	5	Pages	e64086
	Keywords
	Abstract	Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent neurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the more common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate possible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is presented. The proposed computational model successfully accounts for well known psychophysical effects for static contexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas. This work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and reveals how a common general architecture may account for several different fundamental processes, such as visual saliency and brightness induction, which emerge early in the visual processing pathway.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	CIC			Approved	no
	Call Number	Admin @ si @ POD2013			Serial	2242
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	Author	Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva
	Title	Automatic non-rigid temporal alignment of IVUS sequences: method and quantitative validation			Type	Journal Article
	Year	2013	Publication	Ultrasound in Medicine and Biology	Abbreviated Journal	UMB
	Volume	39	Issue	9	Pages	1698-712
	Keywords	Intravascular ultrasound; Dynamic time warping; Non-rigid alignment; Sequence matching; Partial overlapping strategy
	Abstract	Clinical studies on atherosclerosis regression/progression performed by intravascular ultrasound analysis would benefit from accurate alignment of sequences of the same patient before and after clinical interventions and at follow-up. In this article, a methodology for automatic alignment of intravascular ultrasound sequences based on the dynamic time warping technique is proposed. The non-rigid alignment is adapted to the specific task by applying it to multidimensional signals describing the morphologic content of the vessel. Moreover, dynamic time warping is embedded into a framework comprising a strategy to address partial overlapping between acquisitions and a term that regularizes non-physiologic temporal compression/expansion of the sequences. Extensive validation is performed on both synthetic and in vivo data. The proposed method reaches alignment errors of approximately 0.43 mm for pairs of sequences acquired during the same intervention phase and 0.77 mm for pairs of sequences acquired at successive intervention stages.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ ABC2013			Serial	2313
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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
	Keywords
	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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	CIC; 600.052; 600.051; 605.203			Approved	no
	Call Number	Admin @ si @ RPV2013			Serial	2288
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	Author	Rahat Khan; Joost Van de Weijer; Fahad Shahbaz Khan; Damien Muselet; christophe Ducottet; Cecile Barat
	Title	Discriminative Color Descriptors			Type	Conference Article
	Year	2013	Publication	IEEE Conference on Computer Vision and Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	2866 - 2873
	Keywords
	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.
	Address	Portland; Oregon; June 2013
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1063-6919	ISBN		Medium
	Area		Expedition		Conference	CVPR
	Notes	CIC; 600.048			Approved	no
	Call Number	Admin @ si @ KWK2013a			Serial	2262
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