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| Author | Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier | ||||
| Title | Normalisation et validation d'images de documents capturées en mobilité | Type | Conference Article | ||
| Year | 2014 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
| Volume | Issue | Pages | 109-124 | ||
| Keywords | mobile document image acquisition; perspective correction; illumination correction; quality assessment; focus measure; OCR accuracy prediction | ||||
| Abstract | Mobile document image acquisition integrates many distortions which must be corrected or detected on the device, before the document becomes unavailable or paying data transmission fees. In this paper, we propose a system to correct perspective and illumination issues, and estimate the sharpness of the image for OCR recognition. The correction step relies on fast and accurate border detection followed by illumination normalization. Its evaluation on a private dataset shows a clear improvement on OCR accuracy. The quality assessment
step relies on a combination of focus measures. Its evaluation on a public dataset shows that this simple method compares well to state of the art, learning-based methods which cannot be embedded on a mobile, and outperforms metric-based methods. |
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| Address | Nancy; France; March 2014 | ||||
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| Area | Expedition | Conference | CIFED | ||
| Notes | DAG; 601.223; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ RCO2014b | Serial | 2546 | ||
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| Author | Frederic Sampedro; Anna Domenech; Sergio Escalera | ||||
| Title | Static and dynamic computational cancer spread quantification in whole body FDG-PET/CT scans | Type | Journal Article | ||
| Year | 2014 | Publication | Journal of Medical Imaging and Health Informatics | Abbreviated Journal | JMIHI |
| Volume | 4 | Issue | 6 | Pages | 825-831 |
| Keywords | CANCER SPREAD; COMPUTER AIDED DIAGNOSIS; MEDICAL IMAGING; TUMOR QUANTIFICATION | ||||
| Abstract | In this work we address the computational cancer spread quantification scenario in whole body FDG-PET/CT scans. At the static level, this setting can be modeled as a clustering problem on the set of 3D connected components of the whole body PET tumoral segmentation mask carried out by nuclear medicine physicians. At the dynamic level, and ad-hoc algorithm is proposed in order to quantify the cancer spread time evolution which, when combined with other existing indicators, gives rise to the metabolic tumor volume-aggressiveness-spread time evolution chart, a novel tool that we claim that would prove useful in nuclear medicine and oncological clinical or research scenarios. Good performance results of the proposed methodologies both at the clinical and technological level are shown using a dataset of 48 segmented whole body FDG-PET/CT scans. | ||||
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ SDE2014b | Serial | 2548 | ||
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| Author | Frederic Sampedro; Sergio Escalera; Anna Puig | ||||
| Title | Iterative Multiclass Multiscale Stacked Sequential Learning: definition and application to medical volume segmentation | Type | Journal Article | ||
| Year | 2014 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 46 | Issue | Pages | 1-10 | |
| Keywords | Machine learning; Sequential learning; Multi-class problems; Contextual learning; Medical volume segmentation | ||||
| Abstract | In this work we present the iterative multi-class multi-scale stacked sequential learning framework (IMMSSL), a novel learning scheme that is particularly suited for medical volume segmentation applications. This model exploits the inherent voxel contextual information of the structures of interest in order to improve its segmentation performance results. Without any feature set or learning algorithm prior assumption, the proposed scheme directly seeks to learn the contextual properties of a region from the predicted classifications of previous classifiers within an iterative scheme. Performance results regarding segmentation accuracy in three two-class and multi-class medical volume datasets show a significant improvement with respect to state of the art alternatives. Due to its easiness of implementation and its independence of feature space and learning algorithm, the presented machine learning framework could be taken into consideration as a first choice in complex volume segmentation scenarios. | ||||
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ SEP2014 | Serial | 2550 | ||
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| Author | Eloi Puertas; Miguel Angel Bautista; Daniel Sanchez; Sergio Escalera; Oriol Pujol | ||||
| Title | Learning to Segment Humans by Stacking their Body Parts, | Type | Conference Article | ||
| Year | 2014 | Publication | ECCV Workshop on ChaLearn Looking at People | Abbreviated Journal | |
| Volume | 8925 | Issue | Pages | 685-697 | |
| Keywords | Human body segmentation; Stacked Sequential Learning | ||||
| Abstract | Human segmentation in still images is a complex task due to the wide range of body poses and drastic changes in environmental conditions. Usually, human body segmentation is treated in a two-stage fashion. First, a human body part detection step is performed, and then, human part detections are used as prior knowledge to be optimized by segmentation strategies. In this paper, we present a two-stage scheme based on Multi-Scale Stacked Sequential Learning (MSSL). We define an extended feature set by stacking a multi-scale decomposition of body
part likelihood maps. These likelihood maps are obtained in a first stage by means of a ECOC ensemble of soft body part detectors. In a second stage, contextual relations of part predictions are learnt by a binary classifier, obtaining an accurate body confidence map. The obtained confidence map is fed to a graph cut optimization procedure to obtain the final segmentation. Results show improved segmentation when MSSL is included in the human segmentation pipeline. |
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| Area | Expedition | Conference | ECCVW | ||
| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ PBS2014 | Serial | 2553 | ||
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| Author | Marc Bolaños; Maite Garolera; Petia Radeva | ||||
| Title | Video Segmentation of Life-Logging Videos | Type | Conference Article | ||
| Year | 2014 | Publication | 8th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
| Volume | 8563 | Issue | Pages | 1-9 | |
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| Area | Expedition | Conference | AMDO | ||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ BGR2014 | Serial | 2558 | ||
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| Author | Francesco Brughi; Debora Gil; Llorenç Badiella; Eva Jove Casabella; Oriol Ramos Terrades | ||||
| Title | Exploring the impact of inter-query variability on the performance of retrieval systems | Type | Conference Article | ||
| Year | 2014 | Publication | 11th International Conference on Image Analysis and Recognition | Abbreviated Journal | |
| Volume | 8814 | Issue | Pages | 413–420 | |
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| Abstract | This paper introduces a framework for evaluating the performance of information retrieval systems. Current evaluation metrics provide an average score that does not consider performance variability across the query set. In this manner, conclusions lack of any statistical significance, yielding poor inference to cases outside the query set and possibly unfair comparisons. We propose to apply statistical methods in order to obtain a more informative measure for problems in which different query classes can be identified. In this context, we assess the performance variability on two levels: overall variability across the whole query set and specific query class-related variability. To this end, we estimate confidence bands for precision-recall curves, and we apply ANOVA in order to assess the significance of the performance across different query classes. | ||||
| Address | Algarve; Portugal; October 2014 | ||||
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| Publisher | Springer International Publishing | Place of Publication | Editor |
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-319-11757-7 | Medium | |
| Area | Expedition | Conference | ICIAR | ||
| Notes | IAM; DAG; 600.060; 600.061; 600.077; 600.075 | Approved | no | ||
| Call Number | Admin @ si @ BGB2014 | Serial | 2559 | ||
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| Author | Francisco Blanco; Felipe Lumbreras; Joan Serrat; Roswitha Siener; Silvia Serranti; Giuseppe Bonifazi; Montserrat Lopez Mesas; Manuel Valiente | ||||
| Title | Taking advantage of Hyperspectral Imaging classification of urinary stones against conventional IR Spectroscopy | Type | Journal Article | ||
| Year | 2014 | Publication | Journal of Biomedical Optics | Abbreviated Journal | JBiO |
| Volume | 19 | Issue | 12 | Pages | 126004-1 - 126004-9 |
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| Abstract | The analysis of urinary stones is mandatory for the best management of the disease after the stone passage in order to prevent further stone episodes. Thus the use of an appropriate methodology for an individualized stone analysis becomes a key factor for giving the patient the most suitable treatment. A recently developed hyperspectral imaging methodology, based on pixel-to-pixel analysis of near-infrared spectral images, is compared to the reference technique in stone analysis, infrared (IR) spectroscopy. The developed classification model yields >90% correct classification rate when compared to IR and is able to precisely locate stone components within the structure of the stone with a 15 µm resolution. Due to the little sample pretreatment, low analysis time, good performance of the model, and the automation of the measurements, they become analyst independent; this methodology can be considered to become a routine analysis for clinical laboratories. | ||||
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| Notes | ADAS; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ BLS2014 | Serial | 2563 | ||
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| Author | P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes | ||||
| Title | Représentation par graphe de mots manuscrits dans les images pour la recherche par similarité | Type | Conference Article | ||
| Year | 2014 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
| Volume | Issue | Pages | 233-248 | ||
| Keywords | word spotting; graph-based representation; shape context description; graph edit distance; DTW; block merging; query by example | ||||
| Abstract | Effective information retrieval on handwritten document images has always been
a challenging task. In this paper, we propose a novel handwritten word spotting approach based on graph representation. The presented model comprises both topological and morphological signatures of handwriting. Skeleton-based graphs with the Shape Context labeled vertexes are established for connected components. Each word image is represented as a sequence of graphs. In order to be robust to the handwriting variations, an exhaustive merging process based on DTW alignment results introduced in the similarity measure between word images. With respect to the computation complexity, an approximate graph edit distance approach using bipartite matching is employed for graph matching. The experiments on the George Washington dataset and the marriage records from the Barcelona Cathedral dataset demonstrate that the proposed approach outperforms the state-of-the-art structural methods. |
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| Address | Nancy; Francia; March 2014 | ||||
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| Area | Expedition | Conference | CIFED | ||
| Notes | DAG; 600.061; 602.006; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ WEG2014c | Serial | 2564 | ||
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| Author | Michal Drozdzal; Jordi Vitria; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva | ||||
| Title | Intestinal event segmentation for endoluminal video analysis | Type | Conference Article | ||
| Year | 2014 | Publication | 21st IEEE International Conference on Image Processing | Abbreviated Journal | |
| Volume | Issue | Pages | 3592 - 3596 | ||
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| Address | Paris; Francia; October 2014 | ||||
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| Area | Expedition | Conference | ICIP | ||
| Notes | MILAB; OR;MV | Approved | no | ||
| Call Number | Admin @ si @ DVS2014 | Serial | 2565 | ||
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| Author | Gabriel Villalonga; Sebastian Ramos; German Ros; David Vazquez; Antonio Lopez | ||||
| Title | 3d Pedestrian Detection via Random Forest | Type | Miscellaneous | ||
| Year | 2014 | Publication | European Conference on Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 231-238 | ||
| Keywords | Pedestrian Detection | ||||
| Abstract | Our demo focuses on showing the extraordinary performance of our novel 3D pedestrian detector along with its simplicity and real-time capabilities. This detector has been designed for autonomous driving applications, but it can also be applied in other scenarios that cover both outdoor and indoor applications.
Our pedestrian detector is based on the combination of a random forest classifier with HOG-LBP features and the inclusion of a preprocessing stage based on 3D scene information in order to precisely determinate the image regions where the detector should search for pedestrians. This approach ends up in a high accurate system that runs real-time as it is required by many computer vision and robotics applications. |
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| Address | Zurich; suiza; September 2014 | ||||
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| Area | Expedition | Conference | ECCV-Demo | ||
| Notes | ADAS; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ VRR2014 | Serial | 2570 | ||
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| Author | Antonio Esteban Lansaque | ||||
| Title | 3D reconstruction and recognition using structured ligth | Type | Report | ||
| Year | 2014 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume | 179 | Issue | Pages | ||
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| Abstract | This work covers the problem of 3D reconstruction, recognition and 6DOF pose estimation. The goal of this project is to reconstruct a 3D scene and to align an object model of the industrial pieces onto the reconstructed scene. The reconstruction algorithm is based on stereo techniques and the recognition algorithm is based on SHOT descriptors computed on a set of uniform keypoints. Correspondences are used to estimate a first 6DOF transformation that maps the model onto the scene and then ICP algorithm is used to refine the transformation. In order to check the effectiveness of the proposed algorithm, several experiments were performed. These experiments were conducted on a lab environment in order to get results under the same conditions in all of them. Although obtained results are not real time results, the proposed algorithm ends up with high rates of object recognition. | ||||
| Address | UAB; September 2014 | ||||
| Corporate Author | Thesis | Master's thesis | |||
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| Notes | IAM; 600.075 | Approved | no | ||
| Call Number | Admin @ si @ Est2014 | Serial | 2578 | ||
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| Author | Ricard Balague | ||||
| Title | Exploring the combination of color cues for intrinsic image decomposition | Type | Report | ||
| Year | 2014 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume | 178 | Issue | Pages | ||
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| Abstract | Intrinsic image decomposition is a challenging problem that consists in separating an image into its physical characteristics: reflectance and shading. This problem can be solved in different ways, but most methods have combined information from several visual cues. In this work we describe an extension of an existing method proposed by Serra et al. which considers two color descriptors and combines them by means of a Markov Random Field. We analyze in depth the weak points of the method and we explore more possibilities to use in both descriptors. The proposed extension depends on the combination of the cues considered to overcome some of the limitations of the original method. Our approach is tested on the MIT dataset and Beigpour et al. dataset, which contain images of real objects acquired under controlled conditions and synthetic images respectively, with their corresponding ground truth. | ||||
| Address | UAB; September 2014 | ||||
| Corporate Author | Thesis | Master's thesis | |||
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| Notes | CIC; 600.074 | Approved | no | ||
| Call Number | Admin @ si @ Bal2014 | Serial | 2579 | ||
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| Author | Sebastian Ramos | ||||
| Title | Vision-based Detection of Road Hazards for Autonomous Driving | Type | Report | ||
| Year | 2014 | Publication | CVC Technical Report | Abbreviated Journal | |
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| Address | UAB; September 2014 | ||||
| Corporate Author | Thesis | Master's thesis | |||
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| Notes | ADAS; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ Ram2014 | Serial | 2580 | ||
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| Author | Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika | ||||
| Title | Facial Expression Recognition based on Multi-view Observations with Application to Social Robotics | Type | Conference Article | ||
| Year | 2014 | Publication | 1st Workshop on Computer Vision for Affective Computing | Abbreviated Journal | |
| Volume | Issue | Pages | 1-8 | ||
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| Abstract | Human-robot interaction is a hot topic nowadays in the social robotics community. One crucial aspect is represented by the affective communication which comes encoded through the facial expressions. In this paper, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, view- and texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial
expression. |
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| Address | Singapore; November 2014 | ||||
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| Area | Expedition | Conference | ACCV | ||
| Notes | LAMP; | Approved | no | ||
| Call Number | Admin @ si @ RBD2014 | Serial | 2599 | ||
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| Author | Frederic Sampedro; Sergio Escalera; Anna Domenech; Ignasi Carrio | ||||
| Title | A computational framework for cancer response assessment based on oncological PET-CT scans | Type | Journal Article | ||
| Year | 2014 | Publication | Computers in Biology and Medicine | Abbreviated Journal | CBM |
| Volume | 55 | Issue | Pages | 92–99 | |
| Keywords | Computer aided diagnosis; Nuclear medicine; Machine learning; Image processing; Quantitative analysis | ||||
| Abstract | In this work we present a comprehensive computational framework to help in the clinical assessment of cancer response from a pair of time consecutive oncological PET-CT scans. In this scenario, the design and implementation of a supervised machine learning system to predict and quantify cancer progression or response conditions by introducing a novel feature set that models the underlying clinical context is described. Performance results in 100 clinical cases (corresponding to 200 whole body PET-CT scans) in comparing expert-based visual analysis and classifier decision making show up to 70% accuracy within a completely automatic pipeline and 90% accuracy when providing the system with expert-guided PET tumor segmentation masks. | ||||
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ SED2014 | Serial | 2606 | ||
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