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Author |
Andreas Møgelmose; Chris Bahnsen; Thomas B. Moeslund; Albert Clapes; Sergio Escalera |
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Title |
Tri-modal Person Re-identification with RGB, Depth and Thermal Features |
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Conference Article |
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Year |
2013 |
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9th IEEE Workshop on Perception beyond the visible Spectrum, Computer Vision and Pattern Recognition |
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301-307 |
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Person re-identification is about recognizing people who have passed by a sensor earlier. Previous work is mainly based on RGB data, but in this work we for the first time present a system where we combine RGB, depth, and thermal data for re-identification purposes. First, from each of the three modalities, we obtain some particular features: from RGB data, we model color information from different regions of the body, from depth data, we compute different soft body biometrics, and from thermal data, we extract local structural information. Then, the three information types are combined in a joined classifier. The tri-modal system is evaluated on a new RGB-D-T dataset, showing successful results in re-identification scenarios. |
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Portland; oregon; June 2013 |
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978-0-7695-4990-3 |
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HUPBA;MILAB |
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Admin @ si @ MBM2013 |
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2253 |
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Olivier Penacchio; Xavier Otazu; Laura Dempere-Marco |
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Title |
A Neurodynamical Model of Brightness Induction in V1 |
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Journal Article |
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2013 |
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PloS ONE |
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Plos |
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8 |
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5 |
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e64086 |
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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. |
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no |
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Admin @ si @ POD2013 |
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2242 |
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Alicia Fornes; Xavier Otazu; Josep Llados |
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Title |
Show through cancellation and image enhancement by multiresolution contrast processing |
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Conference Article |
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Year |
2013 |
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12th International Conference on Document Analysis and Recognition |
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200-204 |
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Historical documents suffer from different types of degradation and noise such as background variation, uneven illumination or dark spots. In case of double-sided documents, another common problem is that the back side of the document usually interferes with the front side because of the transparency of the document or ink bleeding. This effect is called the show through phenomenon. Many methods are developed to solve these problems, and in the case of show-through, by scanning and matching both the front and back sides of the document. In contrast, our approach is designed to use only one side of the scanned document. We hypothesize that show-trough are low contrast components, while foreground components are high contrast ones. A Multiresolution Contrast (MC) decomposition is presented in order to estimate the contrast of features at different spatial scales. We cancel the show-through phenomenon by thresholding these low contrast components. This decomposition is also able to enhance the image removing shadowed areas by weighting spatial scales. Results show that the enhanced images improve the readability of the documents, allowing scholars both to recover unreadable words and to solve ambiguities. |
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Washington; USA; August 2013 |
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1520-5363 |
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DAG; 602.006; 600.045; 600.061; 600.052;CIC |
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no |
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Admin @ si @ FOL2013 |
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2241 |
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Author |
Sandra Jimenez; Xavier Otazu; Valero Laparra; Jesus Malo |
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Title |
Chromatic induction and contrast masking: similar models, different goals? |
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Conference Article |
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Year |
2013 |
Publication |
Human Vision and Electronic Imaging XVIII |
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8651 |
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Normalization of signals coming from linear sensors is an ubiquitous mechanism of neural adaptation.1 Local interaction between sensors tuned to a particular feature at certain spatial position and neighbor sensors explains a wide range of psychophysical facts including (1) masking of spatial patterns, (2) non-linearities of motion sensors, (3) adaptation of color perception, (4) brightness and chromatic induction, and (5) image quality assessment. Although the above models have formal and qualitative similarities, it does not necessarily mean that the mechanisms involved are pursuing the same statistical goal. For instance, in the case of chromatic mechanisms (disregarding spatial information), different parameters in the normalization give rise to optimal discrimination or adaptation, and different non-linearities may give rise to error minimization or component independence. In the case of spatial sensors (disregarding color information), a number of studies have pointed out the benefits of masking in statistical independence terms. However, such statistical analysis has not been performed for spatio-chromatic induction models where chromatic perception depends on spatial configuration. In this work we investigate whether successful spatio-chromatic induction models,6 increase component independence similarly as previously reported for masking models. Mutual information analysis suggests that seeking an efficient chromatic representation may explain the prevalence of induction effects in spatially simple images. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only. |
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San Francisco CA; USA; February 2013 |
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HVEI |
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CIC |
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no |
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Admin @ si @ JOL2013 |
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2240 |
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Author |
Santiago Segui; Michal Drozdzal; Ekaterina Zaytseva; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitria |
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Title |
A new image centrality descriptor for wrinkle frame detection in WCE videos |
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Conference Article |
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2013 |
Publication |
13th IAPR Conference on Machine Vision Applications |
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Small bowel motility dysfunctions are a widespread functional disorder characterized by abdominal pain and altered bowel habits in the absence of specific and unique organic pathology. Current methods of diagnosis are complex and can only be conducted at some highly specialized referral centers. Wireless Video Capsule Endoscopy (WCE) could be an interesting diagnostic alternative that presents excellent clinical advantages, since it is non-invasive and can be conducted by non specialists. The purpose of this work is to present a new method for the detection of wrinkle frames in WCE, a critical characteristic to detect one of the main motility events: contractions. The method goes beyond the use of one of the classical image feature, the Histogram |
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Kyoto; Japan; May 2013 |
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MVA |
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OR; MILAB; 600.046;MV |
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no |
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Admin @ si @ SDZ2013 |
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2239 |
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Author |
Xavier Baro; David Masip; Elena Planas; Julia Minguillon |
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Title |
PeLP: Plataforma para el Aprendizaje de Lenguajes de Programación |
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Miscellaneous |
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2013 |
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XV Jornadas de Enseñanza Universitaria de la Informatica |
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JENUI |
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OR;HuPBA;MV |
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no |
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Admin @ si @ BMP2013 |
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2237 |
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Author |
Victor Borjas; Jordi Vitria; Petia Radeva |
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Title |
Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments |
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Conference Article |
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2013 |
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13th IAPR Conference on Machine Vision Applications |
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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. |
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Kyoto; Japan; May 2013 |
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MVA |
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OR; MILAB;MV |
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no |
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BVR2013 |
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2238 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Out-of-Sample Embedding for Manifold Learning Applied to Face Recognition |
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Conference Article |
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2013 |
Publication |
IEEE International Workshop on Analysis and Modeling of Faces and Gestures |
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862-868 |
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Manifold learning techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data---the out-of-sample problem. For the first aspect, the proposed schemes were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only reached for a suitable parameter choice that should be known in advance. In this paper, we demonstrate that sparse coding theory not only serves for automatic graph reconstruction as shown in recent works, but also represents an accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. To evaluate the effectiveness of the proposed out-of-sample embedding, experiments are conducted using the k-nearest neighbor (KNN) and Kernel Support Vector Machines (KSVM) classifiers on four public face databases. The experimental results show that the proposed model is able to achieve high categorization effectiveness as well as high consistency with non-linear embeddings/manifolds obtained in batch modes. |
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Portland; USA; June 2013 |
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OR; 600.046;MV |
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no |
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Admin @ si @ DoR2013 |
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2236 |
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Author |
Michal Drozdzal; Santiago Segui; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria |
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Title |
An Application for Efficient Error-Free Labeling of Medical Images |
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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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1-16 |
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In this chapter we describe an application for efficient error-free labeling of medical images. In this scenario, the compilation of a complete training set for building a realistic model of a given class of samples is not an easy task, making the process tedious and time consuming. For this reason, there is a need for interactive labeling applications that minimize the effort of the user while providing error-free labeling. We propose a new algorithm that is based on data similarity in feature space. This method actively explores data in order to find the best label-aligned clustering and exploits it to reduce the labeler effort, that is measured by the number of “clicks. Moreover, error-free labeling is guaranteed by the fact that all data and their labels proposals are visually revised by en expert. |
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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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MILAB; OR;MV |
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Admin @ si @ DSR2013 |
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2235 |
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Bogdan Raducanu; Fadi Dornaika |
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Texture-independent recognition of facial expressions in image snapshots and videos |
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2013 |
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Machine Vision and Applications |
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MVA |
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24 |
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4 |
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811-820 |
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This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines. |
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Springer-Verlag |
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0932-8092 |
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OR; 600.046; 605.203;MV |
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Admin @ si @ RaD2013 |
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2230 |
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David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados |
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Integrating Visual and Textual Cues for Query-by-String Word Spotting |
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2013 |
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12th International Conference on Document Analysis and Recognition |
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511 - 515 |
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In this paper, we present a word spotting framework that follows the query-by-string paradigm where word images are represented both by textual and visual representations. The textual representation is formulated in terms of character $n$-grams while the visual one is based on the bag-of-visual-words scheme. These two representations are merged together and projected to a sub-vector space. This transform allows to, given a textual query, retrieve word instances that were only represented by the visual modality. Moreover, this statistical representation can be used together with state-of-the-art indexation structures in order to deal with large-scale scenarios. The proposed method is evaluated using a collection of historical documents outperforming state-of-the-art performances. |
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Washington; USA; August 2013 |
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1520-5363 |
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DAG; ADAS; 600.045; 600.055; 600.061 |
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Admin @ si @ ART2013 |
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2224 |
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Marc Castello; Jordi Gonzalez; Ariel Amato; Pau Baiget; Carles Fernandez; Josep M. Gonfaus; Ramon Mollineda; Marco Pedersoli; Nicolas Perez de la Blanca; Xavier Roca |
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Exploiting Multimodal Interaction Techniques for Video-Surveillance |
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2013 |
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Multimodal Interaction in Image and Video Applications Intelligent Systems Reference Library |
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48 |
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8 |
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135-151 |
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In this paper we present an example of a video surveillance application that exploits Multimodal Interactive (MI) technologies. The main objective of the so-called VID-Hum prototype was to develop a cognitive artificial system for both the detection and description of a particular set of human behaviours arising from real-world events. The main procedure of the prototype described in this chapter entails: (i) adaptation, since the system adapts itself to the most common behaviours (qualitative data) inferred from tracking (quantitative data) thus being able to recognize abnormal behaviors; (ii) feedback, since an advanced interface based on Natural Language understanding allows end-users the communicationwith the prototype by means of conceptual sentences; and (iii) multimodality, since a virtual avatar has been designed to describe what is happening in the scene, based on those textual interpretations generated by the prototype. Thus, the MI methodology has provided an adequate framework for all these cooperating processes. |
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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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ISE; 605.203; 600.049 |
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CGA2013 |
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2222 |
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Author |
Laura Igual; Agata Lapedriza; Ricard Borras |
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Robust Gait-Based Gender Classification using Depth Cameras |
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Journal Article |
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2013 |
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EURASIP Journal on Advances in Signal Processing |
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EURASIPJ |
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37 |
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1 |
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72-80 |
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This article presents a new approach for gait-based gender recognition using depth cameras, that can run in real time. The main contribution of this study is a new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle. For each frame, these points are aligned according to their centroid and grouped. After that, they are projected into their PCA plane, obtaining a representation of the cycle particularly robust against view changes. Then, final discriminative features are computed by first making a histogram of the projected points and then using linear discriminant analysis. To test the method we have used the DGait database, which is currently the only publicly available database for gait analysis that includes depth information. We have performed experiments on manually labeled cycles and over whole video sequences, and the results show that our method improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information. Furthermore, our approach is insensitive to illumination changes, given that it discards the RGB information. That makes the method especially suitable for real applications, as illustrated in the last part of the experiments section. |
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MILAB; OR;MV |
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Admin @ si @ ILB2013 |
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2144 |
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Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva |
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Adaptable image cuts for motility inspection using WCE |
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2013 |
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Computerized Medical Imaging and Graphics |
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CMIG |
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37 |
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1 |
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72-80 |
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The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE. |
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MILAB; OR; 600.046; 605.203 |
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Admin @ si @ DSM2012 |
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2151 |
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David Roche; Debora Gil; Jesus Giraldo |
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Multiple active receptor conformation, agonist efficacy and maximum effect of the system: the conformation-based operational model of agonism, |
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2013 |
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Drug Discovery Today |
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DDT |
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18 |
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7-8 |
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365-371 |
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The operational model of agonism assumes that the maximum effect a particular receptor system can achieve (the Em parameter) is fixed. Em estimates are above but close to the asymptotic maximum effects of endogenous agonists. The concept of Em is contradicted by superagonists and those positive allosteric modulators that significantly increase the maximum effect of endogenous agonists. An extension of the operational model is proposed that assumes that the Em parameter does not necessarily have a single value for a receptor system but has multiple values associated to multiple active receptor conformations. The model provides a mechanistic link between active receptor conformation and agonist efficacy, which can be useful for the analysis of agonist response under different receptor scenarios. |
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Elsevier |
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IAM; 600.057; 600.054 |
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IAM @ iam @ RGG2013a |
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2190 |
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