| Records |
| Author |
Sandra Jimenez; Xavier Otazu; Valero Laparra; Jesus Malo |
| Title |
Chromatic induction and contrast masking: similar models, different goals? |
Type |
Conference Article |
| Year |
2013 |
Publication |
Human Vision and Electronic Imaging XVIII |
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| Volume |
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 |
| Title |
A new image centrality descriptor for wrinkle frame detection in WCE videos |
Type |
Conference Article |
| Year |
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 |
Serial |
2239 |
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| Author |
Xavier Baro; David Masip; Elena Planas; Julia Minguillon |
| Title |
PeLP: Plataforma para el Aprendizaje de Lenguajes de Programación |
Type |
Miscellaneous |
| Year |
2013 |
Publication |
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 |
| Title |
Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments |
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Conference Article |
| Year |
2013 |
Publication |
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 signi cantly. |
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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 |
Serial |
2238 |
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| Author |
Fadi Dornaika; Bogdan Raducanu |
| Title |
Out-of-Sample Embedding for Manifold Learning Applied to Face Recognition |
Type |
Conference Article |
| Year |
2013 |
Publication |
IEEE International Workshop on Analysis and Modeling of Faces and Gestures |
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Issue |
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Pages |
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. |
| Address |
Portland; USA; June 2013 |
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CVPRW |
| Notes |
OR; 600.046;MV |
Approved |
no |
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Admin @ si @ DoR2013 |
Serial |
2236 |
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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. |
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MILAB |
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no |
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Admin @ si @ ABC2013 |
Serial |
2313 |
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| Author |
Ferran Diego; Joan Serrat; Antonio Lopez |
| Title |
Joint spatio-temporal alignment of sequences |
Type |
Journal Article |
| Year |
2013 |
Publication |
IEEE Transactions on Multimedia |
Abbreviated Journal |
TMM |
| Volume |
15 |
Issue |
6 |
Pages |
1377-1387 |
| Keywords |
video alignment |
| Abstract |
Video alignment is important in different areas of computer vision such as wide baseline matching, action recognition, change detection, video copy detection and frame dropping prevention. Current video alignment methods usually deal with a relatively simple case of fixed or rigidly attached cameras or simultaneous acquisition. Therefore, in this paper we propose a joint video alignment for bringing two video sequences into a spatio-temporal alignment. Specifically, the novelty of the paper is to formulate the video alignment to fold the spatial and temporal alignment into a single alignment framework. This simultaneously satisfies a frame-correspondence and frame-alignment similarity; exploiting the knowledge among neighbor frames by a standard pairwise Markov random field (MRF). This new formulation is able to handle the alignment of sequences recorded at different times by independent moving cameras that follows a similar trajectory, and also generalizes the particular cases that of fixed geometric transformation and/or linear temporal mapping. We conduct experiments on different scenarios such as sequences recorded simultaneously or by moving cameras to validate the robustness of the proposed approach. The proposed method provides the highest video alignment accuracy compared to the state-of-the-art methods on sequences recorded from vehicles driving along the same track at different times. |
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1520-9210 |
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ADAS |
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no |
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Admin @ si @ DSL2013; ADAS @ adas @ |
Serial |
2228 |
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| Author |
German Ros; J. Guerrero; Angel Sappa; Antonio Lopez |
| Title |
VSLAM pose initialization via Lie groups and Lie algebras optimization |
Type |
Conference Article |
| Year |
2013 |
Publication |
Proceedings of IEEE International Conference on Robotics and Automation |
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Pages |
5740 - 5747 |
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SLAM |
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We present a novel technique for estimating initial 3D poses in the context of localization and Visual SLAM problems. The presented approach can deal with noise, outliers and a large amount of input data and still performs in real time in a standard CPU. Our method produces solutions with an accuracy comparable to those produced by RANSAC but can be much faster when the percentage of outliers is high or for large amounts of input data. On the current work we propose to formulate the pose estimation as an optimization problem on Lie groups, considering their manifold structure as well as their associated Lie algebras. This allows us to perform a fast and simple optimization at the same time that conserve all the constraints imposed by the Lie group SE(3). Additionally, we present several key design concepts related with the cost function and its Jacobian; aspects that are critical for the good performance of the algorithm. |
| Address |
Karlsruhe; Germany; May 2013 |
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1050-4729 |
ISBN |
978-1-4673-5641-1 |
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Conference |
ICRA |
| Notes |
ADAS; 600.054; 600.055; 600.057 |
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no |
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Admin @ si @ RGS2013a; ADAS @ adas @ |
Serial |
2225 |
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| Author |
David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados |
| Title |
Integrating Visual and Textual Cues for Query-by-String Word Spotting |
Type |
Conference Article |
| Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
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Pages |
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. |
| Address |
Washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
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DAG; ADAS; 600.045; 600.055; 600.061 |
Approved |
no |
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Admin @ si @ ART2013 |
Serial |
2224 |
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| Author |
Laura Igual; Agata Lapedriza; Ricard Borras |
| Title |
Robust Gait-Based Gender Classification using Depth Cameras |
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Journal Article |
| Year |
2013 |
Publication |
EURASIP Journal on Advances in Signal Processing |
Abbreviated Journal |
EURASIPJ |
| Volume |
37 |
Issue |
1 |
Pages |
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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no |
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Admin @ si @ ILB2013 |
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2144 |
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| Author |
Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva |
| Title |
Adaptable image cuts for motility inspection using WCE |
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Journal Article |
| Year |
2013 |
Publication |
Computerized Medical Imaging and Graphics |
Abbreviated Journal |
CMIG |
| Volume |
37 |
Issue |
1 |
Pages |
72-80 |
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| Abstract |
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 |
Serial |
2151 |
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| Author |
David Geronimo; Joan Serrat; Antonio Lopez; Ramon Baldrich |
| Title |
Traffic sign recognition for computer vision project-based learning |
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Journal Article |
| Year |
2013 |
Publication |
IEEE Transactions on Education |
Abbreviated Journal |
T-EDUC |
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56 |
Issue |
3 |
Pages |
364-371 |
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traffic signs |
| Abstract |
This paper presents a graduate course project on computer vision. The aim of the project is to detect and recognize traffic signs in video sequences recorded by an on-board vehicle camera. This is a demanding problem, given that traffic sign recognition is one of the most challenging problems for driving assistance systems. Equally, it is motivating for the students given that it is a real-life problem. Furthermore, it gives them the opportunity to appreciate the difficulty of real-world vision problems and to assess the extent to which this problem can be solved by modern computer vision and pattern classification techniques taught in the classroom. The learning objectives of the course are introduced, as are the constraints imposed on its design, such as the diversity of students' background and the amount of time they and their instructors dedicate to the course. The paper also describes the course contents, schedule, and how the project-based learning approach is applied. The outcomes of the course are discussed, including both the students' marks and their personal feedback. |
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0018-9359 |
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ADAS; CIC |
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no |
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Admin @ si @ GSL2013; ADAS @ adas @ |
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2160 |
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| Author |
Mikhail Mozerov |
| Title |
Constrained Optical Flow Estimation as a Matching Problem |
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Journal Article |
| Year |
2013 |
Publication |
IEEE Transactions on Image Processing |
Abbreviated Journal |
TIP |
| Volume |
22 |
Issue |
5 |
Pages |
2044-2055 |
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In general, discretization in the motion vector domain yields an intractable number of labels. In this paper we propose an approach that can reduce general optical flow to the constrained matching problem by pre-estimating a 2D disparity labeling map of the desired discrete motion vector function. One of the goals of the proposed paper is estimating coarse distribution of motion vectors and then utilizing this distribution as global constraints for discrete optical flow estimation. This pre-estimation is done with a simple frame-to-frame correlation technique also known as the digital symmetric-phase-only-filter (SPOF). We discover a strong correlation between the output of the SPOF and the motion vector distribution of the related optical flow. The two step matching paradigm for optical flow estimation is applied: pixel accuracy (integer flow), and subpixel accuracy estimation. The matching problem is solved by global optimization. Experiments on the Middlebury optical flow datasets confirm our intuitive assumptions about strong correlation between motion vector distribution of optical flow and maximal peaks of SPOF outputs. The overall performance of the proposed method is promising and achieves state-of-the-art results on the Middlebury benchmark. |
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1057-7149 |
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ISE |
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no |
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Admin @ si @ Moz2013 |
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2191 |
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| Author |
Gemma Roig; Xavier Boix; R. de Nijs; Sebastian Ramos; K. Kühnlenz; Luc Van Gool |
| Title |
Active MAP Inference in CRFs for Efficient Semantic Segmentation |
Type |
Conference Article |
| Year |
2013 |
Publication |
15th IEEE International Conference on Computer Vision |
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Issue |
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Pages |
2312 - 2319 |
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Semantic Segmentation |
| Abstract |
Most MAP inference algorithms for CRFs optimize an energy function knowing all the potentials. In this paper, we focus on CRFs where the computational cost of instantiating the potentials is orders of magnitude higher than MAP inference. This is often the case in semantic image segmentation, where most potentials are instantiated by slow classifiers fed with costly features. We introduce Active MAP inference 1) to on-the-fly select a subset of potentials to be instantiated in the energy function, leaving the rest of the parameters of the potentials unknown, and 2) to estimate the MAP labeling from such incomplete energy function. Results for semantic segmentation benchmarks, namely PASCAL VOC 2010 [5] and MSRC-21 [19], show that Active MAP inference achieves similar levels of accuracy but with major efficiency gains. |
| Address |
Sydney; Australia; December 2013 |
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1550-5499 |
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ICCV |
| Notes |
ADAS; 600.057 |
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no |
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ADAS @ adas @ RBN2013 |
Serial |
2377 |
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| Author |
David Roche; Debora Gil; Jesus Giraldo |
| Title |
Mechanistic analysis of the function of agonists and allosteric modulators: Reconciling two-state and operational models |
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Journal Article |
| Year |
2013 |
Publication |
British Journal of Pharmacology |
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BJP |
| Volume |
169 |
Issue |
6 |
Pages |
1189-202 |
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| Abstract |
Two-state and operational models of both agonism and allosterism are compared to identify and characterize common pharmacological parameters. To account for the receptor-dependent basal response, constitutive receptor activity is considered in the operational models. By arranging two-state models as the fraction of active receptors and operational models as the fractional response relative to the maximum effect of the system, a one-by-one correspondence between parameters is found. The comparative analysis allows a better understanding of complex allosteric interactions. In particular, the inclusion of constitutive receptor activity in the operational model of allosterism allows the characterization of modulators able to lower the basal response of the system; that is, allosteric modulators with negative intrinsic efficacy. Theoretical simulations and overall goodness of fit of the models to simulated data suggest that it is feasible to apply the models to experimental data and constitute one step forward in receptor theory formalism. |
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| Notes |
IAM; 600.044; 605.203 |
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| Call Number |
IAM @ iam @ RGG2013b |
Serial |
2195 |
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