Records |
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 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 |
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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Abstract |
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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CVPRW |
Notes |
OR; 600.046;MV |
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no |
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Admin @ si @ DoR2013 |
Serial |
2236 |
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Author |
Michal Drozdzal; Santiago Segui; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria |
Title |
An Application for Efficient Error-Free Labeling of Medical Images |
Type |
Book Chapter |
Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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Volume |
48 |
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Pages |
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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no |
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Admin @ si @ DSR2013 |
Serial |
2235 |
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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 |
Bogdan Raducanu; Fadi Dornaika |
Title |
Texture-independent recognition of facial expressions in image snapshots and videos |
Type |
Journal Article |
Year |
2013 |
Publication |
Machine Vision and Applications |
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MVA |
Volume |
24 |
Issue |
4 |
Pages |
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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Notes |
OR; 600.046; 605.203;MV |
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no |
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Admin @ si @ RaD2013 |
Serial |
2230 |
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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 |
Call Number |
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. |
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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 |
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Conference Article |
Year |
2013 |
Publication |
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. |
Address |
Washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
Notes |
DAG; ADAS; 600.045; 600.055; 600.061 |
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no |
Call Number |
Admin @ si @ ART2013 |
Serial |
2224 |
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Author |
Marc Castello; Jordi Gonzalez; Ariel Amato; Pau Baiget; Carles Fernandez; Josep M. Gonfaus; Ramon Mollineda; Marco Pedersoli; Nicolas Perez de la Blanca; Xavier Roca |
Title |
Exploiting Multimodal Interaction Techniques for Video-Surveillance |
Type |
Book Chapter |
Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications Intelligent Systems Reference Library |
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48 |
Issue |
8 |
Pages |
135-151 |
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Abstract |
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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Notes |
ISE; 605.203; 600.049 |
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CGA2013 |
Serial |
2222 |
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Author |
Francisco Javier Orozco; Ognjen Rudovic; Jordi Gonzalez; Maja Pantic |
Title |
Hierarchical On-line Appearance-Based Tracking for 3D Head Pose, Eyebrows, Lips, Eyelids and Irises |
Type |
Journal Article |
Year |
2013 |
Publication |
Image and Vision Computing |
Abbreviated Journal |
IMAVIS |
Volume |
31 |
Issue |
4 |
Pages |
322-340 |
Keywords |
On-line appearance models; Levenberg–Marquardt algorithm; Line-search optimization; 3D face tracking; Facial action tracking; Eyelid tracking; Iris tracking |
Abstract |
In this paper, we propose an On-line Appearance-Based Tracker (OABT) for simultaneous tracking of 3D head pose, lips, eyebrows, eyelids and irises in monocular video sequences. In contrast to previously proposed tracking approaches, which deal with face and gaze tracking separately, our OABT can also be used for eyelid and iris tracking, as well as 3D head pose, lips and eyebrows facial actions tracking. Furthermore, our approach applies an on-line learning of changes in the appearance of the tracked target. Hence, the prior training of appearance models, which usually requires a large amount of labeled facial images, is avoided. Moreover, the proposed method is built upon a hierarchical combination of three OABTs, which are optimized using a Levenberg–Marquardt Algorithm (LMA) enhanced with line-search procedures. This, in turn, makes the proposed method robust to changes in lighting conditions, occlusions and translucent textures, as evidenced by our experiments. Finally, the proposed method achieves head and facial actions tracking in real-time. |
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Elsevier |
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ISE; 605.203; 302.012; 302.018; 600.049 |
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ORG2013 |
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2221 |
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Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados; Thierry Brouard |
Title |
Fuzzy Multilevel Graph Embedding |
Type |
Journal Article |
Year |
2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
Volume |
46 |
Issue |
2 |
Pages |
551-565 |
Keywords |
Pattern recognition; Graphics recognition; Graph clustering; Graph classification; Explicit graph embedding; Fuzzy logic |
Abstract |
Structural pattern recognition approaches offer the most expressive, convenient, powerful but computational expensive representations of underlying relational information. To benefit from mature, less expensive and efficient state-of-the-art machine learning models of statistical pattern recognition they must be mapped to a low-dimensional vector space. Our method of explicit graph embedding bridges the gap between structural and statistical pattern recognition. We extract the topological, structural and attribute information from a graph and encode numeric details by fuzzy histograms and symbolic details by crisp histograms. The histograms are concatenated to achieve a simple and straightforward embedding of graph into a low-dimensional numeric feature vector. Experimentation on standard public graph datasets shows that our method outperforms the state-of-the-art methods of graph embedding for richly attributed graphs. |
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Elsevier |
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0031-3203 |
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DAG; 600.042; 600.045; 605.203 |
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Admin @ si @ LRL2013a |
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2270 |
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Author |
Anjan Dutta; Josep Llados; Umapada Pal |
Title |
A symbol spotting approach in graphical documents by hashing serialized graphs |
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Journal Article |
Year |
2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
Volume |
46 |
Issue |
3 |
Pages |
752-768 |
Keywords |
Symbol spotting; Graphics recognition; Graph matching; Graph serialization; Graph factorization; Graph paths; Hashing |
Abstract |
In this paper we propose a symbol spotting technique in graphical documents. Graphs are used to represent the documents and a (sub)graph matching technique is used to detect the symbols in them. We propose a graph serialization to reduce the usual computational complexity of graph matching. Serialization of graphs is performed by computing acyclic graph paths between each pair of connected nodes. Graph paths are one-dimensional structures of graphs which are less expensive in terms of computation. At the same time they enable robust localization even in the presence of noise and distortion. Indexing in large graph databases involves a computational burden as well. We propose a graph factorization approach to tackle this problem. Factorization is intended to create a unified indexed structure over the database of graphical documents. Once graph paths are extracted, the entire database of graphical documents is indexed in hash tables by locality sensitive hashing (LSH) of shape descriptors of the paths. The hashing data structure aims to execute an approximate k-NN search in a sub-linear time. We have performed detailed experiments with various datasets of line drawings and compared our method with the state-of-the-art works. The results demonstrate the effectiveness and efficiency of our technique. |
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Elsevier |
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0031-3203 |
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DAG; 600.042; 600.045; 605.203; 601.152 |
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no |
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Admin @ si @ DLP2012 |
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2127 |
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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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Abstract |
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 |
Serial |
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 |
Type |
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 |
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2151 |
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