| Records |
| Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
| Title |
A Product Graph Based Method for Dual Subgraph Matching Applied to Symbol Spotting |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
|
| Volume |
8746 |
Issue |
|
Pages  |
7-11 |
| Keywords |
Product graph; Dual edge graph; Subgraph matching; Random walks; Graph kernel |
| Abstract |
Product graph has been shown as a way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. Here we focus on the two major limitations of the previous version of the algorithm: (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 edge graph representation on the original graph representing the graphical information and the product graph is computed between the dual edge graphs of the pattern graph and the target graph. The dual edge 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 the pair of similar edges of two operand graphs and exponentiating the adjacency matrix finds similar random walks of greater lengths. Nodes joining similar random walks between two graphs are found by combining different weighted exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
Bart Lamiroy; Jean-Marc Ogier |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
DAG; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ DLB2014 |
Serial |
2698 |
| Permanent link to this record |
| |
|
| |
| Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
| Title |
Pedestrian Candidates Generation using Monocular Cues |
Type |
Conference Article |
| Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
7-12 |
| Keywords |
pedestrian detection |
| Abstract |
Common techniques for pedestrian candidates generation (e.g., sliding window approaches) are based on an exhaustive search over the image. This implies that the number of windows produced is huge, which translates into a significant time consumption in the classification stage. In this paper, we propose a method that significantly reduces the number of windows to be considered by a classifier. Our method is a monocular one that exploits geometric and depth information available on single images. Both representations of the world are fused together to generate pedestrian candidates based on an underlying model which is focused only on objects standing vertically on the ground plane and having certain height, according with their depths on the scene. We evaluate our algorithm on a challenging dataset and demonstrate its application for pedestrian detection, where a considerable reduction in the number of candidate windows is reached. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
IEEE Xplore |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
1931-0587 |
ISBN |
978-1-4673-2119-8 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
IV |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ CPL2012c; ADAS @ adas @ cpl2012d |
Serial |
2013 |
| Permanent link to this record |
| |
|
| |
| Author |
Ivet Rafegas; Maria Vanrell |
| Title |
Color encoding in biologically-inspired convolutional neural networks |
Type |
Journal Article |
| Year |
2018 |
Publication |
Vision Research |
Abbreviated Journal |
VR |
| Volume |
151 |
Issue |
|
Pages |
7-17 |
| Keywords |
Color coding; Computer vision; Deep learning; Convolutional neural networks |
| Abstract |
Convolutional Neural Networks have been proposed as suitable frameworks to model biological vision. Some of these artificial networks showed representational properties that rival primate performances in object recognition. In this paper we explore how color is encoded in a trained artificial network. It is performed by estimating a color selectivity index for each neuron, which allows us to describe the neuron activity to a color input stimuli. The index allows us to classify whether they are color selective or not and if they are of a single or double color. We have determined that all five convolutional layers of the network have a large number of color selective neurons. Color opponency clearly emerges in the first layer, presenting 4 main axes (Black-White, Red-Cyan, Blue-Yellow and Magenta-Green), but this is reduced and rotated as we go deeper into the network. In layer 2 we find a denser hue sampling of color neurons and opponency is reduced almost to one new main axis, the Bluish-Orangish coinciding with the dataset bias. In layers 3, 4 and 5 color neurons are similar amongst themselves, presenting different type of neurons that detect specific colored objects (e.g., orangish faces), specific surrounds (e.g., blue sky) or specific colored or contrasted object-surround configurations (e.g. blue blob in a green surround). Overall, our work concludes that color and shape representation are successively entangled through all the layers of the studied network, revealing certain parallelisms with the reported evidences in primate brains that can provide useful insight into intermediate hierarchical spatio-chromatic representations. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
CIC; 600.051; 600.087 |
Approved |
no |
| Call Number |
Admin @ si @RaV2018 |
Serial |
3114 |
| Permanent link to this record |
| |
|
| |
| Author |
Mohamed Ali Souibgui; Pau Torras; Jialuo Chen; Alicia Fornes |
| Title |
An Evaluation of Handwritten Text Recognition Methods for Historical Ciphered Manuscripts |
Type |
Conference Article |
| Year |
2023 |
Publication |
7th International Workshop on Historical Document Imaging and Processing |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
7-12 |
| Keywords |
|
| Abstract |
This paper investigates the effectiveness of different deep learning HTR families, including LSTM, Seq2Seq, and transformer-based approaches with self-supervised pretraining, in recognizing ciphered manuscripts from different historical periods and cultures. The goal is to identify the most suitable method or training techniques for recognizing ciphered manuscripts and to provide insights into the challenges and opportunities in this field of research. We evaluate the performance of these models on several datasets of ciphered manuscripts and discuss their results. This study contributes to the development of more accurate and efficient methods for recognizing historical manuscripts for the preservation and dissemination of our cultural heritage. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
HIP |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ STC2023 |
Serial |
3849 |
| Permanent link to this record |
| |
|
| |
| Author |
Helena Muñoz; Fernando Vilariño; Dimosthenis Karatzas |
| Title |
Eye-Movements During Information Extraction from Administrative Documents |
Type |
Conference Article |
| Year |
2019 |
Publication |
International Conference on Document Analysis and Recognition Workshops |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
6-9 |
| Keywords |
|
| Abstract |
A key aspect of digital mailroom processes is the extraction of relevant information from administrative documents. More often than not, the extraction process cannot be fully automated, and there is instead an important amount of manual intervention. In this work we study the human process of information extraction from invoice document images. We explore whether the gaze of human annotators during an manual information extraction process could be exploited towards reducing the manual effort and automating the process. To this end, we perform an eye-tracking experiment replicating real-life interfaces for information extraction. Through this pilot study we demonstrate that relevant areas in the document can be identified reliably through automatic fixation classification, and the obtained models generalize well to new subjects. Our findings indicate that it is in principle possible to integrate the human in the document image analysis loop, making use of the scanpath to automate the extraction process or verify extracted information. |
| Address |
Sydney; Australia; September 2019 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICDARW |
| Notes |
DAG; 600.140; 600.121; 600.129;SIAI |
Approved |
no |
| Call Number |
Admin @ si @ MVK2019 |
Serial |
3336 |
| Permanent link to this record |
| |
|
| |
| Author |
Pau Rodriguez; Jordi Gonzalez; Josep M. Gonfaus; Xavier Roca |
| Title |
Integrating Vision and Language in Social Networks for Identifying Visual Patterns of Personality Traits |
Type |
Journal |
| Year |
2019 |
Publication |
International Journal of Social Science and Humanity |
Abbreviated Journal |
IJSSH |
| Volume |
9 |
Issue |
1 |
Pages |
6-12 |
| Keywords |
|
| Abstract |
Social media, as a major platform for communication and information exchange, is a rich repository of the opinions and sentiments of 2.3 billion users about a vast spectrum of topics. In this sense, user text interactions are widely used to sense the whys of certain social user’s demands and cultural- driven interests. However, the knowledge embedded in the 1.8 billion pictures which are uploaded daily in public profiles has just started to be exploited. Following this trend on visual-based social analysis, we present a novel methodology based on neural networks to build a combined image-and-text based personality trait model, trained with images posted together with words found highly correlated to specific personality traits. So, the key contribution in this work is to explore whether OCEAN personality trait modeling can be addressed based on images, here called MindPics, appearing with certain tags with psychological insights. We found that there is a correlation between posted images and the personality estimated from their accompanying texts. Thus, the experimental results are consistent with previous cyber-psychology results based on texts, suggesting that images could also be used for personality estimation: classification results on some personality traits show that specific and characteristic visual patterns emerge, in essence representing abstract concepts. These results open new avenues of research for further refining the proposed personality model under the supervision of psychology experts, and to further substitute current textual personality questionnaires by image-based ones. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ISE; 600.119 |
Approved |
no |
| Call Number |
Admin @ si @ RGG2019 |
Serial |
3414 |
| Permanent link to this record |
| |
|
| |
| Author |
Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva |
| Title |
Traffic-Sign Recognition Systems |
Type |
Book Whole |
| Year |
2011 |
Publication |
SpringerBriefs in Computer Science |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
5-13 |
| Keywords |
|
| Abstract |
|
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer London |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
978-1-4471-2244-9 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
MILAB; OR;HuPBA;MV |
Approved |
no |
| Call Number |
Admin @ si @ EBP2011 |
Serial |
1801 |
| Permanent link to this record |
| |
|
| |
| Author |
Q. Xue; Laura Igual; A. Berenguel; M. Guerrieri; L. Garrido |
| Title |
Active Contour Segmentation with Affine Coordinate-Based Parametrization |
Type |
Conference Article |
| Year |
2014 |
Publication |
9th International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
|
| Volume |
1 |
Issue |
|
Pages |
5-14 |
| Keywords |
Active Contours; Affine Coordinates; Mean Value Coordinates |
| Abstract |
In this paper, we present a new framework for image segmentation based on parametrized active contours. The contour and the points of the image space are parametrized using a set of reduced control points that have to form a closed polygon in two dimensional problems and a closed surface in three dimensional problems. By moving the control points, the active contour evolves. We use mean value coordinates as the parametrization tool for the interface, which allows to parametrize any point of the space, inside or outside the closed polygon
or surface. Region-based energies such as the one proposed by Chan and Vese can be easily implemented in both two and three dimensional segmentation problems. We show the usefulness of our approach with several experiments. |
| Address |
Lisboa; January 2014 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
VISAPP |
| Notes |
OR;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ XIB2014 |
Serial |
2452 |
| Permanent link to this record |
| |
|
| |
| Author |
Arnau Baro; Pau Riba; Alicia Fornes |
| Title |
A Starting Point for Handwritten Music Recognition |
Type |
Conference Article |
| Year |
2018 |
Publication |
1st International Workshop on Reading Music Systems |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
5-6 |
| Keywords |
Optical Music Recognition; Long Short-Term Memory; Convolutional Neural Networks; MUSCIMA++; CVCMUSCIMA |
| Abstract |
In the last years, the interest in Optical Music Recognition (OMR) has reawakened, especially since the appearance of deep learning. However, there are very few works addressing handwritten scores. In this work we describe a full OMR pipeline for handwritten music scores by using Convolutional and Recurrent Neural Networks that could serve as a baseline for the research community. |
| Address |
Paris; France; September 2018 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
WORMS |
| Notes |
DAG; 600.097; 601.302; 601.330; 600.121 |
Approved |
no |
| Call Number |
Admin @ si @ BRF2018 |
Serial |
3223 |
| Permanent link to this record |
| |
|
| |
| Author |
Josep Llados; J. Lopez-Krahe; D. Archambault |
| Title |
Special Issue on Information Technologies for Visually Impaired People |
Type |
Journal |
| Year |
2007 |
Publication |
Novatica |
Abbreviated Journal |
|
| Volume |
186 |
Issue |
|
Pages |
4-7 |
| Keywords |
|
| Abstract |
|
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Guest Editors |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ LLA2007a |
Serial |
903 |
| Permanent link to this record |
| |
|
| |
| Author |
Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman |
| Title |
A Performance Characterization Algorithm for Symbol Localization |
Type |
Conference Article |
| Year |
2009 |
Publication |
8th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
3-11 |
| Keywords |
|
| Abstract |
In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols). |
| Address |
La Rochelle; July 2009 |
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
GREC |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ DRV2009 |
Serial |
1443 |
| Permanent link to this record |
| |
|
| |
| Author |
Alex Pardo; Albert Clapes; Sergio Escalera; Oriol Pujol |
| Title |
Actions in Context: System for people with Dementia |
Type |
Conference Article |
| Year |
2013 |
Publication |
2nd International Workshop on Citizen Sensor Networks (Citisen2013) at the European Conference on Complex Systems |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
3-14 |
| Keywords |
Multi-modal data Fusion; Computer vision; Wearable sensors; Gesture recognition; Dementia |
| Abstract |
In the next forty years, the number of people living with dementia is expected to triple. In the last stages, people affected by this disease become dependent. This hinders the autonomy of the patient and has a huge social impact in time, money and effort. Given this scenario, we propose an ubiquitous system capable of recognizing daily specific actions. The system fuses and synchronizes data obtained from two complementary modalities – ambient and egocentric. The ambient approach consists in a fixed RGB-Depth camera for user and object recognition and user-object interaction, whereas the egocentric point of view is given by a personal area network (PAN) formed by a few wearable sensors and a smartphone, used for gesture recognition. The system processes multi-modal data in real-time, performing paralleled task recognition and modality synchronization, showing high performance recognizing subjects, objects, and interactions, showing its reliability to be applied in real case scenarios. |
| Address |
Barcelona; September 2013 |
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-319-04177-3 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ECCS |
| Notes |
HUPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ PCE2013 |
Serial |
2354 |
| Permanent link to this record |
| |
|
| |
| Author |
Alejandro Gonzalez Alzate; Sebastian Ramos; David Vazquez; Antonio Lopez; Jaume Amores |
| Title |
Spatiotemporal Stacked Sequential Learning for Pedestrian Detection |
Type |
Conference Article |
| Year |
2015 |
Publication |
Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
3-12 |
| Keywords |
SSL; Pedestrian Detection |
| Abstract |
Pedestrian classifiers decide which image windows contain a pedestrian. In practice, such classifiers provide a relatively high response at neighbor windows overlapping a pedestrian, while the responses around potential false positives are expected to be lower. An analogous reasoning applies for image sequences. If there is a pedestrian located within a frame, the same pedestrian is expected to appear close to the same location in neighbor frames. Therefore, such a location has chances of receiving high classification scores during several frames, while false positives are expected to be more spurious. In this paper we propose to exploit such correlations for improving the accuracy of base pedestrian classifiers. In particular, we propose to use two-stage classifiers which not only rely on the image descriptors required by the base classifiers but also on the response of such base classifiers in a given spatiotemporal neighborhood. More specifically, we train pedestrian classifiers using a stacked sequential learning (SSL) paradigm. We use a new pedestrian dataset we have acquired from a car to evaluate our proposal at different frame rates. We also test on a well known dataset: Caltech. The obtained results show that our SSL proposal boosts detection accuracy significantly with a minimal impact on the computational cost. Interestingly, SSL improves more the accuracy at the most dangerous situations, i.e. when a pedestrian is close to the camera. |
| Address |
Santiago de Compostela; España; June 2015 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
ACDC |
Expedition |
|
Conference |
IbPRIA |
| Notes |
ADAS; 600.057; 600.054; 600.076 |
Approved |
no |
| Call Number |
GRV2015; ADAS @ adas @ GRV2015 |
Serial |
2454 |
| Permanent link to this record |
| |
|
| |
| Author |
Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
| Title |
Spotting Graphical Symbols in Camera-Acquired Documents in Real Time |
Type |
Book Chapter |
| Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
|
| Volume |
8746 |
Issue |
|
Pages |
3-10 |
| Keywords |
|
| Abstract |
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 |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
Bart Lamiroy; Jean-Marc Ogier |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
DAG; 600.045; 600.055; 600.061; 600.077 |
Approved |
no |
| Call Number |
Admin @ si @ RKL2014 |
Serial |
2700 |
| Permanent link to this record |
| |
|
| |
| Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera |
| Title |
Action Recognition by Pairwise Proximity Function Support Vector Machines with Dynamic Time Warping Kernels |
Type |
Conference Article |
| Year |
2016 |
Publication |
29th Canadian Conference on Artificial Intelligence |
Abbreviated Journal |
|
| Volume |
9673 |
Issue |
|
Pages |
3-14 |
| Keywords |
|
| Abstract |
In the context of human action recognition using skeleton data, the 3D trajectories of joint points may be considered as multi-dimensional time series. The traditional recognition technique in the literature is based on time series dis(similarity) measures (such as Dynamic Time Warping). For these general dis(similarity) measures, k-nearest neighbor algorithms are a natural choice. However, k-NN classifiers are known to be sensitive to noise and outliers. In this paper, a new class of Support Vector Machine that is applicable to trajectory classification, such as action recognition, is developed by incorporating an efficient time-series distances measure into the kernel function. More specifically, the derivative of Dynamic Time Warping (DTW) distance measure is employed as the SVM kernel. In addition, the pairwise proximity learning strategy is utilized in order to make use of non-positive semi-definite (PSD) kernels in the SVM formulation. The recognition results of the proposed technique on two action recognition datasets demonstrates the ourperformance of our methodology compared to the state-of-the-art methods. Remarkably, we obtained 89 % accuracy on the well-known MSRAction3D dataset using only 3D trajectories of body joints obtained by Kinect |
| Address |
Victoria; Canada; May 2016 |
| Corporate Author |
|
Thesis |
|
| Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
AI |
| Notes |
HuPBA;MILAB; |
Approved |
no |
| Call Number |
Admin @ si @ BGE2016b |
Serial |
2770 |
| Permanent link to this record |
