| Records |
| Author |
Sergio Escalera |
| Title |
Multi-Modal Human Behaviour Analysis from Visual Data Sources |
Type |
Journal |
| Year |
2013 |
Publication |
ERCIM News journal |
Abbreviated Journal |
ERCIM |
| Volume |
95 |
Issue |
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Pages |
21-22 |
| Keywords |
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| Abstract |
The Human Pose Recovery and Behaviour Analysis group (HuPBA), University of Barcelona, is developing a line of research on multi-modal analysis of humans in visual data. The novel technology is being applied in several scenarios with high social impact, including sign language recognition, assisted technology and supported diagnosis for the elderly and people with mental/physical disabilities, fitness conditioning, and Human Computer Interaction. |
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Edition |
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| ISSN |
0926-4981 |
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Conference |
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| Notes |
HuPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ Esc2013 |
Serial |
2361 |
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| Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
| Title |
Near Convex Region Adjacency Graph and Approximate Neighborhood String Matching for Symbol Spotting in Graphical Documents |
Type |
Conference Article |
| Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1078-1082 |
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| Abstract |
This paper deals with a subgraph matching problem in Region Adjacency Graph (RAG) applied to symbol spotting in graphical documents. RAG is a very important, efficient and natural way of representing graphical information with a graph but this is limited to cases where the information is well defined with perfectly delineated regions. What if the information we are interested in is not confined within well defined regions? This paper addresses this particular problem and solves it by defining near convex grouping of oriented line segments which results in near convex regions. Pure convexity imposes hard constraints and can not handle all the cases efficiently. Hence to solve this problem we have defined a new type of convexity of regions, which allows convex regions to have concavity to some extend. We call this kind of regions Near Convex Regions (NCRs). These NCRs are then used to create the Near Convex Region Adjacency Graph (NCRAG) and with this representation we have formulated the problem of symbol spotting in graphical documents as a subgraph matching problem. For subgraph matching we have used the Approximate Edit Distance Algorithm (AEDA) on the neighborhood string, which starts working after finding a key node in the input or target graph and iteratively identifies similar nodes of the query graph in the neighborhood of the key node. The experiments are performed on artificial, real and distorted datasets. |
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Washington; USA; August 2013 |
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Edition |
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| ISSN |
1520-5363 |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG; 600.045; 600.056; 600.061; 601.152 |
Approved |
no |
| Call Number |
Admin @ si @ DLB2013a |
Serial |
2358 |
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| Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
| Title |
A Product graph based method for dual subgraph matching applied to symbol spotting |
Type |
Conference Article |
| Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Abstract |
Product graph has been shown to be an efficient way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. This paper focuses on the two major limitations of the previous version of product graph: (1) Spurious nodes and edges in the graph representation and (2) Inefficient node and edge attributes. To deal with noisy information of vectorized graphical documents, we consider a dual graph representation on the original graph representing the graphical information and the product graph is computed between the dual graphs of the query graphs and the input graph.
The dual graph with redundant edges is helpful for efficient and tolerating encoding of the structural information of the graphical documents. The adjacency matrix of the product graph locates similar path information of two graphs and exponentiating the adjacency matrix finds similar paths of greater lengths. Nodes joining similar paths between two graphs are found by combining different exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging. |
| Address |
Bethlehem; PA; USA; August 2013 |
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Conference |
GREC |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ DLB2013b |
Serial |
2359 |
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| Author |
Ivan Huerta; Ariel Amato; Xavier Roca; Jordi Gonzalez |
| Title |
Exploiting Multiple Cues in Motion Segmentation Based on Background Subtraction |
Type |
Journal Article |
| Year |
2013 |
Publication |
Neurocomputing |
Abbreviated Journal |
NEUCOM |
| Volume |
100 |
Issue |
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Pages |
183–196 |
| Keywords |
Motion segmentation; Shadow suppression; Colour segmentation; Edge segmentation; Ghost detection; Background subtraction |
| Abstract |
This paper presents a novel algorithm for mobile-object segmentation from static background scenes, which is both robust and accurate under most of the common problems found in motionsegmentation. In our first contribution, a case analysis of motionsegmentation errors is presented taking into account the inaccuracies associated with different cues, namely colour, edge and intensity. Our second contribution is an hybrid architecture which copes with the main issues observed in the case analysis by fusing the knowledge from the aforementioned three cues and a temporal difference algorithm. On one hand, we enhance the colour and edge models to solve not only global and local illumination changes (i.e. shadows and highlights) but also the camouflage in intensity. In addition, local information is also exploited to solve the camouflage in chroma. On the other hand, the intensity cue is applied when colour and edge cues are not available because their values are beyond the dynamic range. Additionally, temporal difference scheme is included to segment motion where those three cues cannot be reliably computed, for example in those background regions not visible during the training period. Lastly, our approach is extended for handling ghost detection. The proposed method obtains very accurate and robust motionsegmentation results in multiple indoor and outdoor scenarios, while outperforming the most-referred state-of-art approaches. |
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Elsevier |
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ISE |
Approved |
no |
| Call Number |
Admin @ si @ HAR2013 |
Serial |
1808 |
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| Author |
Bhaskar Chakraborty; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca |
| Title |
Human Action Recognition Using an Ensemble of Body-Part Detectors |
Type |
Journal Article |
| Year |
2013 |
Publication |
Expert Systems |
Abbreviated Journal |
EXSY |
| Volume |
30 |
Issue |
2 |
Pages |
101-114 |
| Keywords |
Human action recognition;body-part detection;hidden Markov model |
| Abstract |
This paper describes an approach to human action recognition based on a probabilistic optimization model of body parts using hidden Markov model (HMM). Our method is able to distinguish between similar actions by only considering the body parts having major contribution to the actions, for example, legs for walking, jogging and running; arms for boxing, waving and clapping. We apply HMMs to model the stochastic movement of the body parts for action recognition. The HMM construction uses an ensemble of body-part detectors, followed by grouping of part detections, to perform human identification. Three example-based body-part detectors are trained to detect three components of the human body: the head, legs and arms. These detectors cope with viewpoint changes and self-occlusions through the use of ten sub-classifiers that detect body parts over a specific range of viewpoints. Each sub-classifier is a support vector machine trained on features selected for the discriminative power for each particular part/viewpoint combination. Grouping of these detections is performed using a simple geometric constraint model that yields a viewpoint-invariant human detector. We test our approach on three publicly available action datasets: the KTH dataset, Weizmann dataset and HumanEva dataset. Our results illustrate that with a simple and compact representation we can achieve robust recognition of human actions comparable to the most complex, state-of-the-art methods. |
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ISE |
Approved |
no |
| Call Number |
Admin @ si @ CBG2013 |
Serial |
1809 |
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| Author |
Kaida Xiao; Chenyang Fu; D.Mylonas; Dimosthenis Karatzas; S. Wuerger |
| Title |
Unique Hue Data for Colour Appearance Models. Part ii: Chromatic Adaptation Transform |
Type |
Journal Article |
| Year |
2013 |
Publication |
Color Research & Application |
Abbreviated Journal |
CRA |
| Volume |
38 |
Issue |
1 |
Pages |
22-29 |
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| Abstract |
Unique hue settings of 185 observers under three room-lighting conditions were used to evaluate the accuracy of full and mixed chromatic adaptation transform models of CIECAM02 in terms of unique hue reproduction. Perceptual hue shifts in CIECAM02 were evaluated for both models with no clear difference using the current Commission Internationale de l'Éclairage (CIE) recommendation for mixed chromatic adaptation ratio. Using our large dataset of unique hue data as a benchmark, an optimised parameter is proposed for chromatic adaptation under mixed illumination conditions that produces more accurate results in unique hue reproduction. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013 |
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| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ XFM2013 |
Serial |
1822 |
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| Author |
Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers |
| Title |
Adapting Pedestrian Detection from Synthetic to Far Infrared Images |
Type |
Conference Article |
| Year |
2013 |
Publication |
ICCV Workshop on Visual Domain Adaptation and Dataset Bias |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
Domain Adaptation; Far Infrared; Pedestrian Detection |
| Abstract |
We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes. |
| Address |
Sydney; Australia; December 2013 |
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Place of Publication |
Sydney, Australy |
Editor |
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| Language |
English |
Summary Language |
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Conference |
ICCVW-VisDA |
| Notes |
ADAS; 600.054; 600.055; 600.057; 601.217;ISE |
Approved |
no |
| Call Number |
ADAS @ adas @ SRV2013 |
Serial |
2334 |
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| Author |
V.C.Kieu; Alicia Fornes; M. Visani; N.Journet ; Anjan Dutta |
| Title |
The ICDAR/GREC 2013 Music Scores Competition on Staff Removal |
Type |
Conference Article |
| Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
Competition; Music scores; Staff Removal |
| Abstract |
The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we propose a staff removal competition where we simulate old music scores. Thus, we have created a new set of images, which contain noise and 3D distortions. This paper describes the distortion methods, metrics, the participant’s methods and the obtained results. |
| Address |
Bethlehem; PA; USA; August 2013 |
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Expedition |
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Conference |
GREC |
| Notes |
DAG; 600.045; 600.061 |
Approved |
no |
| Call Number |
Admin @ si @ KFV2013 |
Serial |
2337 |
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| Author |
M. Visani; V.C.Kieu; Alicia Fornes; N.Journet |
| Title |
The ICDAR 2013 Music Scores Competition: Staff Removal |
Type |
Conference Article |
| Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1439-1443 |
| Keywords |
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| Abstract |
The first competition on music scores that was organized at ICDAR in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario: old music scores. For this purpose, we have generated a new set of images using two kinds of degradations: local noise and 3D distortions. This paper describes the dataset, distortion methods, evaluation metrics, the participant's methods and the obtained results. |
| Address |
Washington; USA; August 2013 |
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Edition |
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1520-5363 |
ISBN |
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Conference |
ICDAR |
| Notes |
DAG; 600.045; 600.061 |
Approved |
no |
| Call Number |
Admin @ si @ VKF2013 |
Serial |
2338 |
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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 |
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| Volume |
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Issue |
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Pages |
624-631 |
| Keywords |
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| 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 |
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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 |
Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados |
| Title |
Classification of Administrative Document Images by Logo Identification |
Type |
Conference Article |
| Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
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Issue |
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Pages |
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This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents. |
| Address |
Bethlehem; PA; USA; August 2013 |
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Conference |
GREC |
| Notes |
DAG; 600.056; 600.045; 605.203 |
Approved |
no |
| Call Number |
Admin @ si @ |
Serial |
2348 |
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| Author |
Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
| Title |
Spotting Graphical Symbols in Camera-Acquired Documents in Real Time |
Type |
Conference Article |
| Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
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Issue |
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Pages |
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In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time. |
| Address |
Bethlehem; PA; USA; August 2013 |
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GREC |
| Notes |
DAG; 600.045; 600.055; 600.061; 602.101 |
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no |
| Call Number |
Admin @ si @ RKL2013 |
Serial |
2347 |
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| Author |
Marçal Rusiñol; T.Benkhelfallah; V. Poulain d'Andecy |
| Title |
Field Extraction from Administrative Documents by Incremental Structural Templates |
Type |
Conference Article |
| Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1100 - 1104 |
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| Abstract |
In this paper we present an incremental framework aimed at extracting field information from administrative document images in the context of a Digital Mail-room scenario. Given a single training sample in which the user has marked which fields have to be extracted from a particular document class, a document model representing structural relationships among words is built. This model is incrementally refined as the system processes more and more documents from the same class. A reformulation of the tf-idf statistic scheme allows to adjust the importance weights of the structural relationships among words. We report in the experimental section our results obtained with a large dataset of real invoices. |
| Address |
Washington; USA; August 2013 |
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1520-5363 |
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Conference |
ICDAR |
| Notes |
DAG; 600.56; 600.045; 605.203; 602.101 |
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no |
| Call Number |
Admin @ si @ RBP2013 |
Serial |
2346 |
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| Author |
Albert Gordo; Marçal Rusiñol; Dimosthenis Karatzas; Andrew Bagdanov |
| Title |
Document Classification and Page Stream Segmentation for Digital Mailroom Applications |
Type |
Conference Article |
| Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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Issue |
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Pages |
621-625 |
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| Abstract |
In this paper we present a method for the segmentation of continuous page streams into multipage documents and the simultaneous classification of the resulting documents. We first present an approach to combine the multiple pages of a document into a single feature vector that represents the whole document. Despite its simplicity and low computational cost, the proposed representation yields results comparable to more complex methods in multipage document classification tasks. We then exploit this representation in the context of page stream segmentation. The most plausible segmentation of a page stream into a sequence of multipage documents is obtained by optimizing a statistical model that represents the probability of each segmented multipage document belonging to a particular class. Experimental results are reported on a large sample of real administrative multipage documents. |
| Address |
Washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
| Notes |
DAG; 600.056; 602.101 |
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no |
| Call Number |
Admin @ si @ GRK2013c |
Serial |
2345 |
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| Author |
L. Rothacker; Marçal Rusiñol; G.A. Fink |
| Title |
Bag-of-Features HMMs for segmentation-free word spotting in handwritten documents |
Type |
Conference Article |
| Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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Issue |
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Pages |
1305 - 1309 |
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| Abstract |
Recent HMM-based approaches to handwritten word spotting require large amounts of learning samples and mostly rely on a prior segmentation of the document. We propose to use Bag-of-Features HMMs in a patch-based segmentation-free framework that are estimated by a single sample. Bag-of-Features HMMs use statistics of local image feature representatives. Therefore they can be considered as a variant of discrete HMMs allowing to model the observation of a number of features at a point in time. The discrete nature enables us to estimate a query model with only a single example of the query provided by the user. This makes our method very flexible with respect to the availability of training data. Furthermore, we are able to outperform state-of-the-art results on the George Washington dataset. |
| Address |
Washington; USA; August 2013 |
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Series Issue |
|
Edition |
|
| ISSN |
1520-5363 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ RRF2013 |
Serial |
2344 |
| Permanent link to this record |
