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Author |
Frederic Sampedro; Sergio Escalera; Anna Puig |
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Title |
Iterative Multiclass Multiscale Stacked Sequential Learning: definition and application to medical volume segmentation |
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Journal Article |
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Year |
2014 |
Publication |
Pattern Recognition Letters |
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PRL |
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46 |
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1-10 |
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Machine learning; Sequential learning; Multi-class problems; Contextual learning; Medical volume segmentation |
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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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HuPBA;MILAB |
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no |
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Admin @ si @ SEP2014 |
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2550 |
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Author |
Eloi Puertas; Miguel Angel Bautista; Daniel Sanchez; Sergio Escalera; Oriol Pujol |
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Title |
Learning to Segment Humans by Stacking their Body Parts, |
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Conference Article |
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Year |
2014 |
Publication |
ECCV Workshop on ChaLearn Looking at People |
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8925 |
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685-697 |
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Human body segmentation; Stacked Sequential Learning |
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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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ECCVW |
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HuPBA;MILAB |
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no |
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Admin @ si @ PBS2014 |
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2553 |
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Author |
Marc Bolaños; Maite Garolera; Petia Radeva |
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Title |
Video Segmentation of Life-Logging Videos |
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Conference Article |
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Year |
2014 |
Publication |
8th Conference on Articulated Motion and Deformable Objects |
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8563 |
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1-9 |
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AMDO |
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MILAB |
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no |
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Admin @ si @ BGR2014 |
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2558 |
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Author |
Francisco Blanco; Felipe Lumbreras; Joan Serrat; Roswitha Siener; Silvia Serranti; Giuseppe Bonifazi; Montserrat Lopez Mesas; Manuel Valiente |
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Title |
Taking advantage of Hyperspectral Imaging classification of urinary stones against conventional IR Spectroscopy |
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Journal Article |
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Year |
2014 |
Publication |
Journal of Biomedical Optics |
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JBiO |
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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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ADAS; 600.076 |
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Admin @ si @ BLS2014 |
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2563 |
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Author |
P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes |
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Title |
Représentation par graphe de mots manuscrits dans les images pour la recherche par similarité |
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Conference Article |
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Year |
2014 |
Publication |
Colloque International Francophone sur l'Écrit et le Document |
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233-248 |
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Keywords |
word spotting; graph-based representation; shape context description; graph edit distance; DTW; block merging; query by example |
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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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Nancy; Francia; March 2014 |
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CIFED |
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DAG; 600.061; 602.006; 600.077 |
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no |
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Admin @ si @ WEG2014c |
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2564 |
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Author |
Michal Drozdzal; Jordi Vitria; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva |
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Title |
Intestinal event segmentation for endoluminal video analysis |
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Conference Article |
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Year |
2014 |
Publication |
21st IEEE International Conference on Image Processing |
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3592 - 3596 |
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Paris; Francia; October 2014 |
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ICIP |
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MILAB; OR;MV |
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no |
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Admin @ si @ DVS2014 |
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2565 |
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Author |
Gabriel Villalonga; Sebastian Ramos; German Ros; David Vazquez; Antonio Lopez |
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Title |
3d Pedestrian Detection via Random Forest |
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Miscellaneous |
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Year |
2014 |
Publication |
European Conference on Computer Vision |
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Pages |
231-238 |
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Keywords |
Pedestrian Detection |
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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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Zurich; suiza; September 2014 |
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ECCV-Demo |
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ADAS; 600.076 |
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no |
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Admin @ si @ VRR2014 |
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2570 |
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Author |
Antonio Esteban Lansaque |
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Title |
3D reconstruction and recognition using structured ligth |
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Report |
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2014 |
Publication |
CVC Technical Report |
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179 |
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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. |
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UAB; September 2014 |
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Master's thesis |
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IAM; 600.075 |
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no |
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Admin @ si @ Est2014 |
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2578 |
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Author |
Ricard Balague |
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Title |
Exploring the combination of color cues for intrinsic image decomposition |
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Report |
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2014 |
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CVC Technical Report |
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178 |
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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. |
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UAB; September 2014 |
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Master's thesis |
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CIC; 600.074 |
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no |
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Admin @ si @ Bal2014 |
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2579 |
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Author |
Sebastian Ramos |
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Title |
Vision-based Detection of Road Hazards for Autonomous Driving |
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Report |
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2014 |
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CVC Technical Report |
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UAB; September 2014 |
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Master's thesis |
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ADAS; 600.076 |
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Admin @ si @ Ram2014 |
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2580 |
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Author |
Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika |
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Title |
Facial Expression Recognition based on Multi-view Observations with Application to Social Robotics |
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Conference Article |
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2014 |
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1st Workshop on Computer Vision for Affective Computing |
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1-8 |
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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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Singapore; November 2014 |
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ACCV |
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LAMP; |
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Admin @ si @ RBD2014 |
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2599 |
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Author |
Frederic Sampedro; Sergio Escalera; Anna Domenech; Ignasi Carrio |
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A computational framework for cancer response assessment based on oncological PET-CT scans |
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2014 |
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Computers in Biology and Medicine |
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CBM |
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55 |
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92–99 |
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Computer aided diagnosis; Nuclear medicine; Machine learning; Image processing; Quantitative analysis |
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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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HuPBA;MILAB |
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Admin @ si @ SED2014 |
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2606 |
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Author |
Maedeh Aghaei; Petia Radeva |
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Bag-of-Tracklets for Person Tracking in Life-Logging Data |
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Conference Article |
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2014 |
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17th International Conference of the Catalan Association for Artificial Intelligence |
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269 |
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35-44 |
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By increasing popularity of wearable cameras, life-logging data analysis is becoming more and more important and useful to derive significant events out of this substantial collection of images. In this study, we introduce a new tracking method applied to visual life-logging, called bag-of-tracklets, which is based on detecting, localizing and tracking of people. Given the low spatial and temporal resolution of the image data, our model generates and groups tracklets in a unsupervised framework and extracts image sequences of person appearance according to a similarity score of the bag-of-tracklets. The model output is a meaningful sequence of events expressing human appearance and tracking them in life-logging data. The achieved results prove the robustness of our model in terms of efficiency and accuracy despite the low spatial and temporal resolution of the data. |
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978-1-61499-451-0 |
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CCIA |
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MILAB |
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no |
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Admin @ si @ AgR2015 |
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2607 |
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Author |
R. Clariso; David Masip; A. Rius |
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Student projects empowering mobile learning in higher education |
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2014 |
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Revista de Universidad y Sociedad del Conocimiento |
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RUSC |
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11 |
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192-207 |
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1698-580X |
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OR;MV |
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Admin @ si @ CMR2014 |
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2619 |
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Author |
Joan Arnedo-Moreno; D. Bañeres; Xavier Baro; S. Caballe; S. Guerrero; L. Porta; J. Prieto |
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Title |
Va-ID: A trust-based virtual assessment system |
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Conference Article |
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Year |
2014 |
Publication |
6th International Conference on Intelligent Networking and Collaborative Systems |
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Pages |
328 - 335 |
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Abstract |
Even though online education is a very important pillar of lifelong education, institutions are still reluctant to wager for a fully online educational model. At the end, they keep relying on on-site assessment systems, mainly because fully virtual alternatives do not have the deserved social recognition or credibility. Thus, the design of virtual assessment systems that are able to provide effective proof of student authenticity and authorship and the integrity of the activities in a scalable and cost efficient manner would be very helpful. This paper presents ValID, a virtual assessment approach based on a continuous trust level evaluation between students and the institution. The current trust level serves as the main mechanism to dynamically decide which kind of controls a given student should be subjected to, across different courses in a degree. The main goal is providing a fair trade-off between security, scalability and cost, while maintaining the perceived quality of the educational model. |
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Address |
Salerna; Italy; September 2014 |
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ISBN |
978-1-4799-6386-7 |
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INCOS |
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Notes |
OR; HuPBA;MV |
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no |
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Call Number |
Admin @ si @ ABB2014 |
Serial |
2620 |
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Permanent link to this record |