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Author | Jun Wan; Yibing Zhao; Shuai Zhou; Isabelle Guyon; Sergio Escalera | ||||
Title | ChaLearn Looking at People RGB-D Isolated and Continuous Datasets for Gesture Recognition | Type | Conference Article | ||
Year | 2016 | Publication | 29th IEEE Conference on Computer Vision and Pattern Recognition Worshops | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | In this paper, we present two large video multi-modal datasets for RGB and RGB-D gesture recognition: the ChaLearn LAP RGB-D Isolated Gesture Dataset (IsoGD)and the Continuous Gesture Dataset (ConGD). Both datasets are derived from the ChaLearn Gesture Dataset
(CGD) that has a total of more than 50000 gestures for the “one-shot-learning” competition. To increase the potential of the old dataset, we designed new well curated datasets composed of 249 gesture labels, and including 47933 gestures manually labeled the begin and end frames in sequences.Using these datasets we will open two competitions on the CodaLab platform so that researchers can test and compare their methods for “user independent” gesture recognition. The first challenge is designed for gesture spotting and recognition in continuous sequences of gestures while the second one is designed for gesture classification from segmented data. The baseline method based on the bag of visual words model is also presented. |
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Address ![]() |
Las Vegas; USA; July 2016 | ||||
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 | CVPRW | ||
Notes | HuPBA;MILAB; | Approved | no | ||
Call Number | Admin @ si @ WZZ2016 | Serial | 2771 | ||
Permanent link to this record | |||||
Author | David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras | ||||
Title | Efficient Object Pixel-Level Categorization using Bag of Features: Advances in Visual Computing | Type | Conference Article | ||
Year | 2009 | Publication | 5th International Symposium on Visual Computing | Abbreviated Journal | |
Volume | 5875 | Issue | Pages | 44–55 | |
Keywords | |||||
Abstract | In this paper we present a pixel-level object categorization method suitable to be applied under real-time constraints. Since pixels are categorized using a bag of features scheme, the major bottleneck of such an approach would be the feature pooling in local histograms of visual words. Therefore, we propose to bypass this time-consuming step and directly obtain the score from a linear Support Vector Machine classifier. This is achieved by creating an integral image of the components of the SVM which can readily obtain the classification score for any image sub-window with only 10 additions and 2 products, regardless of its size. Besides, we evaluated the performance of two efficient feature quantization methods: the Hierarchical K-Means and the Extremely Randomized Forest. All experiments have been done in the Graz02 database, showing comparable, or even better results to related work with a lower computational cost. | ||||
Address ![]() |
Las Vegas, USA | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | 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 | 978-3-642-10330-8 | Medium | |
Area | Expedition | Conference | ISVC | ||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ ATR2009a | Serial | 1246 | ||
Permanent link to this record | |||||
Author | Bogdan Raducanu; Fadi Dornaika | ||||
Title | Natural Facial Expression Recognition Using Dynamic and Static Schemes | Type | Conference Article | ||
Year | 2009 | Publication | 5th International Symposium on Visual Computing | Abbreviated Journal | |
Volume | 5875 | Issue | Pages | 730–739 | |
Keywords | |||||
Abstract | Affective computing is at the core of a new paradigm in HCI and AI represented by human-centered computing. Within this paradigm, it is expected that machines will be enabled with perceiving capabilities, making them aware about users’ affective state. The current paper addresses the problem of facial expression recognition from monocular videos sequences. We propose a dynamic facial expression recognition scheme, which is proven to be very efficient. Furthermore, it is conveniently compared with several static-based systems adopting different magnitude of facial expression. We provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). We also provide performance evaluations using arbitrary test video sequences. | ||||
Address ![]() |
Las Vegas, USA | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-10330-8 | Medium | |
Area | Expedition | Conference | ISVC | ||
Notes | OR;MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ RaD2009 | Serial | 1257 | ||
Permanent link to this record | |||||
Author | Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados | ||||
Title | Automatic Verification of Properly Signed Multi-page Document Images | Type | Conference Article | ||
Year | 2015 | Publication | Proceedings of the Eleventh International Symposium on Visual Computing | Abbreviated Journal | |
Volume | 9475 | Issue | Pages | 327-336 | |
Keywords | Document Image; Manual Inspection; Signature Verification; Rejection Criterion; Document Flow | ||||
Abstract | In this paper we present an industrial application for the automatic screening of incoming multi-page documents in a banking workflow aimed at determining whether these documents are properly signed or not. The proposed method is divided in three main steps. First individual pages are classified in order to identify the pages that should contain a signature. In a second step, we segment within those key pages the location where the signatures should appear. The last step checks whether the signatures are present or not. Our method is tested in a real large-scale environment and we report the results when checking two different types of real multi-page contracts, having in total more than 14,500 pages. | ||||
Address ![]() |
Las Vegas, Nevada, USA; December 2015 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | 9475 | Series Issue | Edition | ||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ISVC | ||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ | Serial | 3189 | ||
Permanent link to this record | |||||
Author | Xavier Soria; Angel Sappa | ||||
Title | Improving Edge Detection in RGB Images by Adding NIR Channel | Type | Conference Article | ||
Year | 2018 | Publication | 14th IEEE International Conference on Signal Image Technology & Internet Based System | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Edge detection; Contour detection; VGG; CNN; RGB-NIR; Near infrared images | ||||
Abstract | The edge detection is yet a critical problem in many computer vision and image processing tasks. The manuscript presents an Holistically-Nested Edge Detection based approach to study the inclusion of Near-Infrared in the Visible spectrum
images. To do so, a Single Sensor based dataset has been acquired in the range of 400nm to 1100nm wavelength spectral band. Prominent results have been obtained even when the ground truth (annotated edge-map) is based in the visible wavelength spectrum. |
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Address ![]() |
Las Palmas de Gran Canaria; November 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 | SITIS | ||
Notes | MSIAU; 600.122 | Approved | no | ||
Call Number | Admin @ si @ SoS2018 | Serial | 3192 | ||
Permanent link to this record | |||||
Author | Patricia Suarez; Angel Sappa; Boris X. Vintimilla | ||||
Title | Cross-spectral image dehaze through a dense stacked conditional GAN based approach | Type | Conference Article | ||
Year | 2018 | Publication | 14th IEEE International Conference on Signal Image Technology & Internet Based System | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Infrared imaging; Dense; Stacked CGAN; Crossspectral; Convolutional networks | ||||
Abstract | This paper proposes a novel approach to remove haze from RGB images using a near infrared images based on a dense stacked conditional Generative Adversarial Network (CGAN). The architecture of the deep network implemented
receives, besides the images with haze, its corresponding image in the near infrared spectrum, which serve to accelerate the learning process of the details of the characteristics of the images. The model uses a triplet layer that allows the independence learning of each channel of the visible spectrum image to remove the haze on each color channel separately. A multiple loss function scheme is proposed, which ensures balanced learning between the colors and the structure of the images. Experimental results have shown that the proposed method effectively removes the haze from the images. Additionally, the proposed approach is compared with a state of the art approach showing better results. |
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Address ![]() |
Las Palmas de Gran Canaria; November 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 | 978-1-5386-9385-8 | Medium | ||
Area | Expedition | Conference | SITIS | ||
Notes | MSIAU; 600.086; 600.130; 600.122 | Approved | no | ||
Call Number | Admin @ si @ SSV2018a | Serial | 3193 | ||
Permanent link to this record | |||||
Author | Jorge Charco; Boris X. Vintimilla; Angel Sappa | ||||
Title | Deep learning based camera pose estimation in multi-view environment | Type | Conference Article | ||
Year | 2018 | Publication | 14th IEEE International Conference on Signal Image Technology & Internet Based System | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Deep learning; Camera pose estimation; Multiview environment; Siamese architecture | ||||
Abstract | This paper proposes to use a deep learning network architecture for relative camera pose estimation on a multi-view environment. The proposed network is a variant architecture of AlexNet to use as regressor for prediction the relative translation and rotation as output. The proposed approach is trained from
scratch on a large data set that takes as input a pair of imagesfrom the same scene. This new architecture is compared with a previous approach using standard metrics, obtaining better results on the relative camera pose. |
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Address ![]() |
Las Palmas de Gran Canaria; November 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 | SITIS | ||
Notes | MSIAU; 600.086; 600.130; 600.122 | Approved | no | ||
Call Number | Admin @ si @ CVS2018 | Serial | 3194 | ||
Permanent link to this record | |||||
Author | Muhammad Anwer Rao; David Vazquez; Antonio Lopez | ||||
Title | Opponent Colors for Human Detection | Type | Conference Article | ||
Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 6669 | Issue | Pages | 363-370 | |
Keywords | Pedestrian Detection; Color; Part Based Models | ||||
Abstract | Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attention in the literature. However, color-based features, which are important in other domains (e.g., image categorization), have received much less attention. In fact, the use of RGB color space has become a kind of choice by default. The focus has been put in developing first and second order features on top of RGB space (e.g., HOG and co-occurrence matrices, resp.). In this paper we evaluate the opponent colors (OPP) space as a biologically inspired alternative for human detection. In particular, by feeding OPP space in the baseline framework of Dalal et al. for human detection (based on RGB, HOG and linear SVM), we will obtain better detection performance than by using RGB space. This is a relevant result since, up to the best of our knowledge, OPP space has not been previously used for human detection. This suggests that in the future it could be worth to compute co-occurrence matrices, self-similarity features, etc., also on top of OPP space, i.e., as we have done with HOG in this paper. | ||||
Address ![]() |
Las Palmas de Gran Canaria. Spain | ||||
Corporate Author | Thesis | ||||
Publisher | Springer | Place of Publication | Berlin Heidelberg | Editor | J. Vitria; J.M. Sanches; M. Hernandez |
Language | English | Summary Language | English | Original Title | Opponent Colors for Human Detection |
Series Editor | Series Title | Lecture Notes on Computer Science | Abbreviated Series Title | LNCS | |
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-21256-7 | Medium | |
Area | Expedition | Conference | IbPRIA | ||
Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ RVL2011a | Serial | 1666 | ||
Permanent link to this record | |||||
Author | Farhan Riaz; Fernando Vilariño; Mario Dinis-Ribeiro; Miguel Coimbraln | ||||
Title | Identifying Potentially Cancerous Tissues in Chromoendoscopy Images | Type | Conference Article | ||
Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 6669 | Issue | Pages | 709-716 | |
Keywords | Endoscopy, Computer Assisted Diagnosis, Gradient. | ||||
Abstract | The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered. | ||||
Address ![]() |
Las Palmas de Gran Canaria. Spain | ||||
Corporate Author | Thesis | ||||
Publisher | Springer | Place of Publication | Berlin | Editor | J. Vitria, J.M. Sanches, and M. Hernandez |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-3-642-21256-7 | Medium | ||
Area | 800 | Expedition | Conference | IbPRIA | |
Notes | MV;SIAI | Approved | no | ||
Call Number | Admin @ si @ RVD2011; IAM @ iam @ RVD2011 | Serial | 1726 | ||
Permanent link to this record | |||||
Author | Jordi Vitria; Joao Sanchez; Miguel Raposo; Mario Hernandez | ||||
Title | Pattern Recognition and Image Analysis | Type | Book Whole | ||
Year | 2011 | Publication | 5th Iberian Conference Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 6669 | Issue | Pages | ||
Keywords | |||||
Abstract | |||||
Address ![]() |
Las Palmas de Gran Canaria. Spain | ||||
Corporate Author | Thesis | ||||
Publisher | Springer-Verlag | Place of Publication | Berlin | Editor | J. Vitrià; J. Sanchez; M. Raposo; M. Hernandez |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-3-642-2125 | Medium | ||
Area | Expedition | Conference | IbPRIA | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ VSR2011 | Serial | 1730 | ||
Permanent link to this record | |||||
Author | Mario Rojas; David Masip; Jordi Vitria | ||||
Title | Automatic Detection of Facial Feature Points via HOGs and Geometric Prior Models | Type | Conference Article | ||
Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 6669 | Issue | Pages | 371-378 | |
Keywords | |||||
Abstract | Most applications dealing with problems involving the face require a robust estimation of the facial salient points. Nevertheless, this estimation is not usually an automated preprocessing step in applications dealing with facial expression recognition. In this paper we present a simple method to detect facial salient points in the face. It is based on a prior Point Distribution Model and a robust object descriptor. The model learns the distribution of the points from the training data, as well as the amount of variation in location each point exhibits. Using this model, we reduce the search areas to look for each point. In addition, we also exploit the global consistency of the points constellation, increasing the detection accuracy. The method was tested on two separate data sets and the results, in some cases, outperform the state of the art. | ||||
Address ![]() |
Las Palmas de Gran Canaria. Spain | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | 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 | 978-3-642-21256-7 | Medium | |
Area | Expedition | Conference | IbPRIA | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ RMV2011a | Serial | 1731 | ||
Permanent link to this record | |||||
Author | Jon Almazan; Ernest Valveny; Alicia Fornes | ||||
Title | Deforming the Blurred Shape Model for Shape Description and Recognition | Type | Conference Article | ||
Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 6669 | Issue | Pages | 1-8 | |
Keywords | |||||
Abstract | This paper presents a new model for the description and recognition of distorted shapes, where the image is represented by a pixel density distribution based on the Blurred Shape Model combined with a non-linear image deformation model. This leads to an adaptive structure able to capture elastic deformations in shapes. This method has been evaluated using thee different datasets where deformations are present, showing the robustness and good performance of the new model. Moreover, we show that incorporating deformation and flexibility, the new model outperforms the BSM approach when classifying shapes with high variability of appearance. | ||||
Address ![]() |
Las Palmas de Gran Canaria. Spain | ||||
Corporate Author | Thesis | ||||
Publisher | Springer-Verlag | Place of Publication | Berlin | Editor | Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | IbPRIA | ||
Notes | DAG; | Approved | no | ||
Call Number | Admin @ si @ AVF2011 | Serial | 1732 | ||
Permanent link to this record | |||||
Author | Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria; Petia Radeva | ||||
Title | Interactive Labeling of WCE Images | Type | Conference Article | ||
Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 6669 | Issue | Pages | 143-150 | |
Keywords | |||||
Abstract | A high quality labeled training set is necessary for any supervised machine learning algorithm. Labeling of the data can be a very expensive process, specially while dealing with data of high variability and complexity. A good example of such data are the videos from Wireless Capsule Endoscopy. Building a representative WCE data set means many videos to be labeled by an expert. The problem that occurs is the data diversity, in the space of the features, from different WCE studies. That means that when new data arrives it is highly probable that it will not be represented in the training set, thus getting a high probability of performing an error when applying machine learning schemes. In this paper an interactive labeling scheme that allows reducing expert effort in the labeling process is presented. It is shown that the number of human interventions can be significantly reduced. The proposed system allows the annotation of informative/non-informative frames of the WCE video with less than 100 clicks | ||||
Address ![]() |
Las Palmas de Gran Canaria. Spain | ||||
Corporate Author | Thesis | ||||
Publisher | Springer | Place of Publication | Editor | Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | IbPRIA | ||
Notes | MILAB;OR;MV | Approved | no | ||
Call Number | Admin @ si @ DSM2011 | Serial | 1734 | ||
Permanent link to this record | |||||
Author | Pierluigi Casale; Oriol Pujol; Petia Radeva | ||||
Title | Human Activity Recognition from Accelerometer Data using a Wearable Device | Type | Conference Article | ||
Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 6669 | Issue | Pages | 289-296 | |
Keywords | |||||
Abstract | Activity Recognition is an emerging field of research, born from the larger fields of ubiquitous computing, context-aware computing and multimedia. Recently, recognizing everyday life activities becomes one of the challenges for pervasive computing. In our work, we developed a novel wearable system easy to use and comfortable to bring. Our wearable system is based on a new set of 20 computationally efficient features and the Random Forest classifier. We obtain very encouraging results with classification accuracy of human activities recognition of up to 94%. | ||||
Address ![]() |
Las Palmas de Gran Canaria. Spain | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-21256-7 | Medium | |
Area | Expedition | Conference | IbPRIA | ||
Notes | MILAB;HuPBA | Approved | no | ||
Call Number | Admin @ si @ CPR2011a | Serial | 1735 | ||
Permanent link to this record | |||||
Author | Lluis Pere de las Heras; Gemma Sanchez | ||||
Title | And-Or Graph Grammar for Architectural Floorplan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model | Type | Conference Article | ||
Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 6669 | Issue | Pages | 17-24 | |
Keywords | |||||
Abstract | This paper presents a syntactic model for architectural floor plan interpretation. A stochastic image grammar over an And-Or graph is inferred to represent the hierarchical, structural and semantic relations between elements of all possible floor plans. This grammar is augmented with three different probabilistic models, learnt from a training set, to account the frequency of that relations. Then, a Bottom-Up/Top-Down parser with a pruning strategy has been used for floor plan recognition. For a given input, the parser generates the most probable parse graph for that document. This graph not only contains the structural and semantic relations of its elements, but also its hierarchical composition, that allows to interpret the floor plan at different levels of abstraction. | ||||
Address ![]() |
Las Palmas de Gran Canaria. Spain | ||||
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 | 978-3-642-21256-7 | Medium | ||
Area | Expedition | Conference | IbPRIA | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ HeS2011 | Serial | 1736 | ||
Permanent link to this record |