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Author | Antoni Gurgui; Debora Gil; Enric Marti | ||||
Title | Laplacian Unitary Domain for Texture Morphing | Type | Conference Article | ||
Year | 2015 | Publication | Proceedings of the 10th International Conference on Computer Vision Theory and Applications VISIGRAPP2015 | Abbreviated Journal | |
Volume | 1 | Issue | Pages | 693-699 | |
Keywords | Facial; metamorphosis;LaplacianMorphing | ||||
Abstract | Deformation of expressive textures is the gateway to realistic computer synthesis of expressions. By their good mathematical properties and flexible formulation on irregular meshes, most texture mappings rely on solutions to the Laplacian in the cartesian space. In the context of facial expression morphing, this approximation can be seen from the opposite point of view by neglecting the metric. In this paper, we use the properties of the Laplacian in manifolds to present a novel approach to warping expressive facial images in order to generate a morphing between them. | ||||
Address | Munich; Germany; February 2015 | ||||
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Publisher | SciTePress | Place of Publication | Editor | ||
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ISSN | ISBN | 978-989-758-089-5 | Medium | ||
Area | Expedition | Conference | VISAPP | ||
Notes | IAM; 600.075 | Approved | no | ||
Call Number | Admin @ si @ GGM2015 | Serial | 2614 | ||
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Author | Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Marta Diez-Ferrer; Antoni Rosell; Debora Gil | ||||
Title | Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy | Type | Conference Article | ||
Year | 2015 | Publication | 6th International Conference on Information Processing in Computer-Assisted Interventions IPCAI2015 | Abbreviated Journal | |
Volume | 10 | Issue | 6 | Pages | 935-945 |
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Abstract | PURPOSE:
Lack of objective measurement of tracheal obstruction degree has a negative impact on the chosen treatment prone to lead to unnecessary repeated explorations and other scanners. Accurate computation of tracheal stenosis in videobronchoscopy would constitute a breakthrough for this noninvasive technique and a reduction in operation cost for the public health service. METHODS: Stenosis calculation is based on the comparison of the region delimited by the lumen in an obstructed frame and the region delimited by the first visible ring in a healthy frame. We propose a parametric strategy for the extraction of lumen and tracheal ring regions based on models of their geometry and appearance that guide a deformable model. To ensure a systematic applicability, we present a statistical framework to choose optimal parametric values and a strategy to choose the frames that minimize the impact of scope optical distortion. RESULTS: Our method has been tested in 40 cases covering different stenosed tracheas. Experiments report a non- clinically relevant [Formula: see text] of discrepancy in the calculated stenotic area and a computational time allowing online implementation in the operating room. CONCLUSIONS: Our methodology allows reliable measurements of airway narrowing in the operating room. To fully assess its clinical impact, a prospective clinical trial should be done. |
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Address | Barcelona; Spain; June 2015 | ||||
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Area | Expedition | Conference | IPCAI | ||
Notes | IAM; MV; 600.075 | Approved | no | ||
Call Number | Admin @ si @ SBS2015b | Serial | 2613 | ||
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Author | Carles Sanchez; Debora Gil; R. Tazi; Jorge Bernal; Y. Ruiz; L. Planas; F. Javier Sanchez; Antoni Rosell | ||||
Title | Quasi-real time digital assessment of Central Airway Obstruction | Type | Conference Article | ||
Year | 2015 | Publication | 3rd European congress for bronchology and interventional pulmonology ECBIP2015 | Abbreviated Journal | |
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Address | Barcelona; Spain; April 2015 | ||||
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Area | Expedition | Conference | ECBIP | ||
Notes | IAM; MV; 600.075 | Approved | no | ||
Call Number | SGT2015 | Serial | 2612 | ||
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Author | Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Antoni Rosell; Marta Diez-Ferrer; Debora Gil | ||||
Title | Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy | Type | Journal Article | ||
Year | 2015 | Publication | International Journal of Computer Assisted Radiology and Surgery | Abbreviated Journal | IJCAR |
Volume | 10 | Issue | 6 | Pages | 935-945 |
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Notes | IAM; MV; 600.075 | Approved | no | ||
Call Number | Admin @ si @ SBS2015a | Serial | 2611 | ||
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Author | Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; J.Roncaries; Debora Gil | ||||
Title | Automatic evaluation of practices in Moodle for Self Learning in Engineering | Type | Journal | ||
Year | 2015 | Publication | Journal of Technology and Science Education | Abbreviated Journal | JOTSE |
Volume | 5 | Issue | 2 | Pages | 97-106 |
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Notes | IAM; DAG; 600.075; 600.077 | Approved | no | ||
Call Number | Admin @ si @ SRM2015 | Serial | 2610 | ||
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Author | Jorge Bernal; F. Javier Sanchez; Gloria Fernandez Esparrach; Debora Gil; Cristina Rodriguez de Miguel; Fernando Vilariño | ||||
Title | WM-DOVA Maps for Accurate Polyp Highlighting in Colonoscopy: Validation vs. Saliency Maps from Physicians | Type | Journal Article | ||
Year | 2015 | Publication | Computerized Medical Imaging and Graphics | Abbreviated Journal | CMIG |
Volume | 43 | Issue | Pages | 99-111 | |
Keywords | Polyp localization; Energy Maps; Colonoscopy; Saliency; Valley detection | ||||
Abstract | We introduce in this paper a novel polyp localization method for colonoscopy videos. Our method is based on a model of appearance for polyps which defines polyp boundaries in terms of valley information. We propose the integration of valley information in a robust way fostering complete, concave and continuous boundaries typically associated to polyps. This integration is done by using a window of radial sectors which accumulate valley information to create WMDOVA1 energy maps related with the likelihood of polyp presence. We perform a double validation of our maps, which include the introduction of two new databases, including the first, up to our knowledge, fully annotated database with clinical metadata associated. First we assess that the highest value corresponds with the location of the polyp in the image. Second, we show that WM-DOVA energy maps can be comparable with saliency maps obtained from physicians' fixations obtained via an eye-tracker. Finally, we prove that our method outperforms state-of-the-art computational saliency results. Our method shows good performance, particularly for small polyps which are reported to be the main sources of polyp miss-rate, which indicates the potential applicability of our method in clinical practice. | ||||
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ISSN | 0895-6111 | ISBN | Medium | ||
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Notes | MV; IAM; 600.047; 600.060; 600.075;SIAI | Approved | no | ||
Call Number | Admin @ si @ BSF2015 | Serial | 2609 | ||
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Author | Enric Marti; J.Roncaries; Debora Gil; Aura Hernandez-Sabate; Antoni Gurgui; Ferran Poveda | ||||
Title | PBL On Line: A proposal for the organization, part-time monitoring and assessment of PBL group activities | Type | Journal | ||
Year | 2015 | Publication | Journal of Technology and Science Education | Abbreviated Journal | JOTSE |
Volume | 5 | Issue | 2 | Pages | 87-96 |
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Notes | IAM; ADAS; 600.076; 600.075 | Approved | no | ||
Call Number | Admin @ si @ MRG2015 | Serial | 2608 | ||
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Author | Frederic Sampedro; Anna Domenech; Sergio Escalera; Ignasi Carrio | ||||
Title | Deriving global quantitative tumor response parameters from 18F-FDG PET-CT scans in patients with non-Hodgkins lymphoma | Type | Journal Article | ||
Year | 2015 | Publication | Nuclear Medicine Communications | Abbreviated Journal | NMC |
Volume | 36 | Issue | 4 | Pages | 328-333 |
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Abstract | OBJECTIVES:
The aim of the study was to address the need for quantifying the global cancer time evolution magnitude from a pair of time-consecutive positron emission tomography-computed tomography (PET-CT) scans. In particular, we focus on the computation of indicators using image-processing techniques that seek to model non-Hodgkin's lymphoma (NHL) progression or response severity. MATERIALS AND METHODS: A total of 89 pairs of time-consecutive PET-CT scans from NHL patients were stored in a nuclear medicine station for subsequent analysis. These were classified by a consensus of nuclear medicine physicians into progressions, partial responses, mixed responses, complete responses, and relapses. The cases of each group were ordered by magnitude following visual analysis. Thereafter, a set of quantitative indicators designed to model the cancer evolution magnitude within each group were computed using semiautomatic and automatic image-processing techniques. Performance evaluation of the proposed indicators was measured by a correlation analysis with the expert-based visual analysis. RESULTS: The set of proposed indicators achieved Pearson's correlation results in each group with respect to the expert-based visual analysis: 80.2% in progressions, 77.1% in partial response, 68.3% in mixed response, 88.5% in complete response, and 100% in relapse. In the progression and mixed response groups, the proposed indicators outperformed the common indicators used in clinical practice [changes in metabolic tumor volume, mean, maximum, peak standardized uptake value (SUV mean, SUV max, SUV peak), and total lesion glycolysis] by more than 40%. CONCLUSION: Computing global indicators of NHL response using PET-CT imaging techniques offers a strong correlation with the associated expert-based visual analysis, motivating the future incorporation of such quantitative and highly observer-independent indicators in oncological decision making or treatment response evaluation scenarios. |
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Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ SDE2015 | Serial | 2605 | ||
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Author | Isabelle Guyon; Kristin Bennett; Gavin Cawley; Hugo Jair Escalante; Sergio Escalera; Tin Kam Ho; Nuria Macia; Bisakha Ray; Alexander Statnikov; Evelyne Viegas | ||||
Title | Design of the 2015 ChaLearn AutoML Challenge | Type | Conference Article | ||
Year | 2015 | Publication | IEEE International Joint Conference on Neural Networks IJCNN2015 | Abbreviated Journal | |
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Abstract | ChaLearn is organizing for IJCNN 2015 an Automatic Machine Learning challenge (AutoML) to solve classification and regression problems from given feature representations, without any human intervention. This is a challenge with code
submission: the code submitted can be executed automatically on the challenge servers to train and test learning machines on new datasets. However, there is no obligation to submit code. Half of the prizes can be won by just submitting prediction results. There are six rounds (Prep, Novice, Intermediate, Advanced, Expert, and Master) in which datasets of progressive difficulty are introduced (5 per round). There is no requirement to participate in previous rounds to enter a new round. The rounds alternate AutoML phases in which submitted code is “blind tested” on datasets the participants have never seen before, and Tweakathon phases giving time (' 1 month) to the participants to improve their methods by tweaking their code on those datasets. This challenge will push the state-of-the-art in fully automatic machine learning on a wide range of problems taken from real world applications. The platform will remain available beyond the termination of the challenge: http://codalab.org/AutoML |
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Address | Killarney; Ireland; July 2015 | ||||
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Area | Expedition | Conference | IJCNN | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ GBC2015a | Serial | 2604 | ||
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Author | Hugo Jair Escalante; Jose Martinez; Sergio Escalera; Victor Ponce; Xavier Baro | ||||
Title | Improving Bag of Visual Words Representations with Genetic Programming | Type | Conference Article | ||
Year | 2015 | Publication | IEEE International Joint Conference on Neural Networks IJCNN2015 | Abbreviated Journal | |
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Abstract | The bag of visual words is a well established representation in diverse computer vision problems. Taking inspiration from the fields of text mining and retrieval, this representation has proved to be very effective in a large number of domains.
In most cases, a standard term-frequency weighting scheme is considered for representing images and videos in computer vision. This is somewhat surprising, as there are many alternative ways of generating bag of words representations within the text processing community. This paper explores the use of alternative weighting schemes for landmark tasks in computer vision: image categorization and gesture recognition. We study the suitability of using well-known supervised and unsupervised weighting schemes for such tasks. More importantly, we devise a genetic program that learns new ways of representing images and videos under the bag of visual words representation. The proposed method learns to combine term-weighting primitives trying to maximize the classification performance. Experimental results are reported in standard image and video data sets showing the effectiveness of the proposed evolutionary algorithm. |
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Address | Killarney; Ireland; July 2015 | ||||
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Area | Expedition | Conference | IJCNN | ||
Notes | HuPBA;MV | Approved | no | ||
Call Number | Admin @ si @ EME2015 | Serial | 2603 | ||
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Author | Firat Ismailoglu; Ida G. Sprinkhuizen-Kuyper; Evgueni Smirnov; Sergio Escalera; Ralf Peeters | ||||
Title | Fractional Programming Weighted Decoding for Error-Correcting Output Codes | Type | Conference Article | ||
Year | 2015 | Publication | Multiple Classifier Systems, Proceedings of 12th International Workshop , MCS 2015 | Abbreviated Journal | |
Volume | Issue | Pages | 38-50 | ||
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Abstract | In order to increase the classification performance obtained using Error-Correcting Output Codes designs (ECOC), introducing weights in the decoding phase of the ECOC has attracted a lot of interest. In this work, we present a method for ECOC designs that focuses on increasing hypothesis margin on the data samples given a base classifier. While achieving this, we implicitly reward the base classifiers with high performance, whereas punish those with low performance. The resulting objective function is of the fractional programming type and we deal with this problem through the Dinkelbach’s Algorithm. The conducted tests over well known UCI datasets show that the presented method is superior to the unweighted decoding and that it outperforms the results of the state-of-the-art weighted decoding methods in most of the performed experiments. | ||||
Address | Gunzburg; Germany; June 2015 | ||||
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Publisher | Springer International Publishing | Place of Publication | Editor | ||
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ISSN | ISBN | 978-3-319-20247-1 | Medium | ||
Area | Expedition | Conference | MCS | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ ISS2015 | Serial | 2601 | ||
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Author | C. Alejandro Parraga | ||||
Title | Perceptual Psychophysics | Type | Book Chapter | ||
Year | 2015 | Publication | Biologically-Inspired Computer Vision: Fundamentals and Applications | Abbreviated Journal | |
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Publisher | Place of Publication | Editor | G.Cristobal; M.Keil; L.Perrinet | ||
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ISSN | ISBN | 978-3-527-41264-8 | Medium | ||
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Notes | CIC; 600.074 | Approved | no | ||
Call Number | Admin @ si @ Par2015 | Serial | 2600 | ||
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Author | Manuel Graña; Bogdan Raducanu | ||||
Title | Special Issue on Bioinspired and knowledge based techniques and applications | Type | Journal Article | ||
Year | 2015 | Publication | Neurocomputing | Abbreviated Journal | NEUCOM |
Volume | Issue | Pages | 1-3 | ||
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Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ GrR2015 | Serial | 2598 | ||
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Author | Estefania Talavera; Mariella Dimiccoli; Marc Bolaños; Maedeh Aghaei; Petia Radeva | ||||
Title | R-clustering for egocentric video segmentation | Type | Conference Article | ||
Year | 2015 | Publication | Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 | Abbreviated Journal | |
Volume | 9117 | Issue | Pages | 327-336 | |
Keywords | Temporal video segmentation; Egocentric videos; Clustering | ||||
Abstract | In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energy-minimization framework. Given the tendency of most AC methods to oversegment video sequences when clustering their frames, we combine the clustering with a concept drift detection technique (ADWIN) that has rigorous guarantee of performances. ADWIN serves as a statistical upper bound for the clustering-based video segmentation. We integrate both techniques in an energy-minimization framework that serves to disambiguate the decision of both techniques and to complete the segmentation taking into account the temporal continuity of video frames descriptors. We present experiments over egocentric sets of more than 13.000 images acquired with different wearable cameras, showing that our method outperforms state-of-the-art clustering methods. | ||||
Address | Santiago de Compostela; España; June 2015 | ||||
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Publisher | Springer International Publishing | 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 | 978-3-319-19389-2 | Medium | |
Area | Expedition | Conference | IbPRIA | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ TDB2015 | Serial | 2597 | ||
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Author | Marc Bolaños; Maite Garolera; Petia Radeva | ||||
Title | Object Discovery using CNN Features in Egocentric Videos | Type | Conference Article | ||
Year | 2015 | Publication | Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 | Abbreviated Journal | |
Volume | 9117 | Issue | Pages | 67-74 | |
Keywords | Object discovery; Egocentric videos; Lifelogging; CNN | ||||
Abstract | Lifelogging devices based on photo/video are spreading faster everyday. This growth can represent great benefits to develop methods for extraction of meaningful information about the user wearing the device and his/her environment. In this paper, we propose a semi-supervised strategy for easily discovering objects relevant to the person wearing a first-person camera. The egocentric video sequence acquired by the camera, uses both the appearance extracted by means of a deep convolutional neural network and an object refill methodology that allow to discover objects even in case of small amount of object appearance in the collection of images. We validate our method on a sequence of 1000 egocentric daily images and obtain results with an F-measure of 0.5, 0.17 better than the state of the art approach. | ||||
Address | Santiago de Compostela; España; June 2015 | ||||
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Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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ISSN | 0302-9743 | ISBN | 978-3-319-19389-2 | Medium | |
Area | Expedition | Conference | IbPRIA | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ BGR2015 | Serial | 2596 | ||
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