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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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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ECCVW | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ PBS2014 | Serial | 2553 | ||
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Author | Xavier Perez Sala; Fernando De la Torre; Laura Igual; Sergio Escalera; Cecilio Angulo | ||||
Title | Subspace Procrustes Analysis | Type | Conference Article | ||
Year | 2014 | Publication | ECCV Workshop on ChaLearn Looking at People | Abbreviated Journal | |
Volume | 8925 | Issue | Pages | 654-668 | |
Keywords | |||||
Abstract | Procrustes Analysis (PA) has been a popular technique to align and build 2-D statistical models of shapes. Given a set of 2-D shapes PA is applied to remove rigid transformations. Then, a non-rigid 2-D model is computed by modeling (e.g., PCA) the residual. Although PA has been widely used, it has several limitations for modeling 2-D shapes: occluded landmarks and missing data can result in local minima solutions, and there is no guarantee that the 2-D shapes provide a uniform sampling of the 3-D space of rotations for the object. To address previous issues, this paper proposes Subspace PA (SPA). Given several instances of a 3-D object, SPA computes the mean and a 2-D subspace that can simultaneously model all rigid and non-rigid deformations of the 3-D object. We propose a discrete (DSPA) and continuous (CSPA) formulation for SPA, assuming that 3-D samples of an object are provided. DSPA extends the traditional PA, and produces unbiased 2-D models by uniformly sampling dierent views of the 3-D object. CSPA provides a continuous approach to uniformly sample the space of 3-D rotations, being more ecient in space and time. Experiments using SPA to learn 2-D models of bodies from motion capture data illustrate the benets of our approach. | ||||
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Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ECCVW | ||
Notes | OR; HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ PTI2014 | Serial | 2539 | ||
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Author | Sergio Escalera; Xavier Baro; Jordi Gonzalez; Miguel Angel Bautista; Meysam Madadi; Miguel Reyes; Victor Ponce; Hugo Jair Escalante; Jaime Shotton; Isabelle Guyon | ||||
Title | ChaLearn Looking at People Challenge 2014: Dataset and Results | Type | Conference Article | ||
Year | 2014 | Publication | ECCV Workshop on ChaLearn Looking at People | Abbreviated Journal | |
Volume | 8925 | Issue | Pages | 459-473 | |
Keywords | Human Pose Recovery; Behavior Analysis; Action and in- teractions; Multi-modal gestures; recognition | ||||
Abstract | This paper summarizes the ChaLearn Looking at People 2014 challenge data and the results obtained by the participants. The competition was split into three independent tracks: human pose recovery from RGB data, action and interaction recognition from RGB data sequences, and multi-modal gesture recognition from RGB-Depth sequences. For all the tracks, the goal was to perform user-independent recognition in sequences of continuous images using the overlapping Jaccard index as the evaluation measure. In this edition of the ChaLearn challenge, two large novel data sets were made publicly available and the Microsoft Codalab platform were used to manage the competition. Outstanding results were achieved in the three challenge tracks, with accuracy results of 0.20, 0.50, and 0.85 for pose recovery, action/interaction recognition, and multi-modal gesture recognition, respectively. | ||||
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Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ECCVW | ||
Notes | HuPBA; ISE; 600.063;MV | Approved | no | ||
Call Number | Admin @ si @ EBG2014 | Serial | 2529 | ||
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Author | Patricia Marquez; H. Kause; A. Fuster; Aura Hernandez-Sabate; L. Florack; Debora Gil; Hans van Assen | ||||
Title | Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging | Type | Conference Article | ||
Year | 2014 | Publication | 17th International Conference on Medical Image Computing and Computer Assisted Intervention | Abbreviated Journal | |
Volume | 8896 | Issue | Pages | 231-238 | |
Keywords | Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging | ||||
Abstract | Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across dierent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three dierent OF methods, including HARP. |
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Address | Boston; USA; September 2014 | ||||
Corporate Author | Thesis | ||||
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 | 978-3-319-14677-5 | Medium | |
Area | Expedition | Conference | STACOM | ||
Notes | IAM; ADAS; 600.060; 601.145; 600.076; 600.075 | Approved | no | ||
Call Number | Admin @ si @ MKF2014 | Serial | 2495 | ||
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Author | Jorge Bernal; Joan M. Nuñez; F. Javier Sanchez; Fernando Vilariño | ||||
Title | Polyp Segmentation Method in Colonoscopy Videos by means of MSA-DOVA Energy Maps Calculation | Type | Conference Article | ||
Year | 2014 | Publication | 3rd MICCAI Workshop on Clinical Image-based Procedures: Translational Research in Medical Imaging | Abbreviated Journal | |
Volume | 8680 | Issue | Pages | 41-49 | |
Keywords | Image segmentation; Polyps; Colonoscopy; Valley information; Energy maps | ||||
Abstract | In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation. | ||||
Address | Boston; USA; September 2014 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CLIP | ||
Notes | MV; 600.060; 600.044; 600.047;SIAI | Approved | no | ||
Call Number | Admin @ si @ BNS2014 | Serial | 2502 | ||
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Author | Joan M. Nuñez; Jorge Bernal; Miquel Ferrer; Fernando Vilariño | ||||
Title | Impact of Keypoint Detection on Graph-based Characterization of Blood Vessels in Colonoscopy Videos | Type | Conference Article | ||
Year | 2014 | Publication | CARE workshop | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Colonoscopy; Graph Matching; Biometrics; Vessel; Intersection | ||||
Abstract | We explore the potential of the use of blood vessels as anatomical landmarks for developing image registration methods in colonoscopy images. An unequivocal representation of blood vessels could be used to guide follow-up methods to track lesions over different interventions. We propose a graph-based representation to characterize network structures, such as blood vessels, based on the use of intersections and endpoints. We present a study consisting of the assessment of the minimal performance a keypoint detector should achieve so that the structure can still be recognized. Experimental results prove that, even by achieving a loss of 35% of the keypoints, the descriptive power of the associated graphs to the vessel pattern is still high enough to recognize blood vessels. | ||||
Address | Boston; USA; September 2014 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CARE | ||
Notes | MV; DAG; 600.060; 600.047; 600.077;SIAI | Approved | no | ||
Call Number | Admin @ si @ NBF2014 | Serial | 2504 | ||
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Author | Jorge Bernal; Debora Gil; Carles Sanchez; F. Javier Sanchez | ||||
Title | Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis | Type | Conference Article | ||
Year | 2014 | Publication | 1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy | Abbreviated Journal | |
Volume | 8899 | Issue | Pages | 1-10 | |
Keywords | Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps | ||||
Abstract | In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation. | ||||
Address | Boston; USA; September 2014 | ||||
Corporate Author | Thesis | ||||
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 | 978-3-319-13409-3 | Medium | |
Area | Expedition | Conference | CARE | ||
Notes | MV; IAM; 600.044; 600.047; 600.060; 600.075 | Approved | no | ||
Call Number | Admin @ si @ BGS2014b | Serial | 2503 | ||
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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 | |
Keywords | |||||
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 | ||||
Corporate Author | Thesis | ||||
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 | 978-3-319-11757-7 | 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 | Oualid M. Benkarim; Petia Radeva; Laura Igual | ||||
Title | Label Consistent Multiclass Discriminative Dictionary Learning for MRI Segmentation | Type | Conference Article | ||
Year | 2014 | Publication | 8th Conference on Articulated Motion and Deformable Objects | Abbreviated Journal | |
Volume | 8563 | Issue | Pages | 138-147 | |
Keywords | MRI segmentation; sparse representation; discriminative dic- tionary learning; multiclass classication | ||||
Abstract | The automatic segmentation of multiple subcortical structures in brain Magnetic Resonance Images (MRI) still remains a challenging task. In this paper, we address this problem using sparse representation and discriminative dictionary learning, which have shown promising results in compression, image denoising and recently in MRI segmentation. Particularly, we use multiclass dictionaries learned from a set of brain atlases to simultaneously segment multiple subcortical structures.
We also impose dictionary atoms to be specialized in one given class using label consistent K-SVD, which can alleviate the bias produced by unbalanced libraries, present when dealing with small structures. The proposed method is compared with other state of the art approaches for the segmentation of the Basal Ganglia of 35 subjects of a public dataset. The promising results of the segmentation method show the eciency of the multiclass discriminative dictionary learning algorithms in MRI segmentation problems. |
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Address | Palma de Mallorca; July 2014 | ||||
Corporate Author | Thesis | ||||
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 | 978-3-319-08848-8 | Medium | |
Area | Expedition | Conference | AMDO | ||
Notes | MILAB; OR | Approved | no | ||
Call Number | Admin @ si @ BRI2014 | Serial | 2494 | ||
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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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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 | AMDO | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ BGR2014 | Serial | 2558 | ||
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Author | Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu | ||||
Title | Robust Head Gestures Recognition for Assistive Technology | Type | Book Chapter | ||
Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | |
Volume | 8495 | Issue | Pages | 152-161 | |
Keywords | |||||
Abstract | This paper presents a system capable of recognizing six head gestures: nodding, shaking, turning right, turning left, looking up, and looking down. The main difference of our system compared to other methods is that the Hidden Markov Models presented in this paper, are fully connected and consider all possible states in any given order, providing the following advantages to the system: (1) allows unconstrained movement of the head and (2) it can be easily integrated into a wearable device (e.g. glasses, neck-hung devices), in which case it can robustly recognize gestures in the presence of ego-motion. Experimental results show that this approach outperforms common methods that use restricted HMMs for each gesture. | ||||
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Corporate Author | Thesis | ||||
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 | 978-3-319-07490-0 | Medium | |
Area | Expedition | Conference | |||
Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ TSR2014b | Serial | 2505 | ||
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Author | Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez | ||||
Title | On-line lumen centre detection in gastrointestinal and respiratory endoscopy | Type | Conference Article | ||
Year | 2013 | Publication | Second International Workshop Clinical Image-Based Procedures | Abbreviated Journal | |
Volume | 8361 | Issue | Pages | 31-38 | |
Keywords | Lumen centre detection; Bronchoscopy; Colonoscopy | ||||
Abstract | We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %). | ||||
Address | Nagoya; Japan; September 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | Springer International Publishing | Place of Publication | Editor | Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-3-319-05665-4 | Medium | ||
Area | 800 | Expedition | Conference | CLIP | |
Notes | MV; IAM; 600.047; 600.044; 600.060 | Approved | no | ||
Call Number | Admin @ si @ SBG2013 | Serial | 2302 | ||
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Author | Alex Pardo; Albert Clapes; Sergio Escalera; Oriol Pujol | ||||
Title | Actions in Context: System for people with Dementia | Type | Conference Article | ||
Year | 2013 | Publication | 2nd International Workshop on Citizen Sensor Networks (Citisen2013) at the European Conference on Complex Systems | Abbreviated Journal | |
Volume | Issue | Pages | 3-14 | ||
Keywords | Multi-modal data Fusion; Computer vision; Wearable sensors; Gesture recognition; Dementia | ||||
Abstract | In the next forty years, the number of people living with dementia is expected to triple. In the last stages, people affected by this disease become dependent. This hinders the autonomy of the patient and has a huge social impact in time, money and effort. Given this scenario, we propose an ubiquitous system capable of recognizing daily specific actions. The system fuses and synchronizes data obtained from two complementary modalities – ambient and egocentric. The ambient approach consists in a fixed RGB-Depth camera for user and object recognition and user-object interaction, whereas the egocentric point of view is given by a personal area network (PAN) formed by a few wearable sensors and a smartphone, used for gesture recognition. The system processes multi-modal data in real-time, performing paralleled task recognition and modality synchronization, showing high performance recognizing subjects, objects, and interactions, showing its reliability to be applied in real case scenarios. | ||||
Address | Barcelona; September 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | Springer International Publishing | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-319-04177-3 | Medium | |
Area | Expedition | Conference | ECCS | ||
Notes | HUPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ PCE2013 | Serial | 2354 | ||
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Author | Fadi Dornaika; Alireza Bosaghzadeh; Bogdan Raducanu | ||||
Title | Efficient Graph Construction for Label Propagation based Multi-observation Face Recognition | Type | Conference Article | ||
Year | 2013 | Publication | Human Behavior Understanding 4th International Workshop | Abbreviated Journal | |
Volume | 8212 | Issue | Pages | 124-135 | |
Keywords | |||||
Abstract | Workshop on Human Behavior Understanding
Human-machine interaction is a hot topic nowadays in the communities of multimedia and computer vision. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. Recently, graph-based label propagation for multi-observation face recognition was proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot adapt optimally to the data. In this paper, we propose a novel approach for efficient and adaptive graph construction that can be used for multi-observation face recognition as well as for other recognition problems. Experimental results performed on Honda video face database, show a distinct advantage of the proposed method over the standard graph construction methods. |
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Address | Barcelona | ||||
Corporate Author | Thesis | ||||
Publisher | Springer International Publishing | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-319-02713-5 | Medium | |
Area | Expedition | Conference | HBU | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ DBR2013 | Serial | 2315 | ||
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Author | Arnau Baro; Pau Riba; Alicia Fornes | ||||
Title | Musigraph: Optical Music Recognition Through Object Detection and Graph Neural Network | Type | Conference Article | ||
Year | 2022 | Publication | Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition (ICFHR2022) | Abbreviated Journal | |
Volume | 13639 | Issue | Pages | 171-184 | |
Keywords | Object detection; Optical music recognition; Graph neural network | ||||
Abstract | During the last decades, the performance of optical music recognition has been increasingly improving. However, and despite the 2-dimensional nature of music notation (e.g. notes have rhythm and pitch), most works treat musical scores as a sequence of symbols in one dimension, which make their recognition still a challenge. Thus, in this work we explore the use of graph neural networks for musical score recognition. First, because graphs are suited for n-dimensional representations, and second, because the combination of graphs with deep learning has shown a great performance in similar applications. Our methodology consists of: First, we will detect each isolated/atomic symbols (those that can not be decomposed in more graphical primitives) and the primitives that form a musical symbol. Then, we will build the graph taking as root node the notehead and as leaves those primitives or symbols that modify the note’s rhythm (stem, beam, flag) or pitch (flat, sharp, natural). Finally, the graph is translated into a human-readable character sequence for a final transcription and evaluation. Our method has been tested on more than five thousand measures, showing promising results. | ||||
Address | December 04 – 07, 2022; Hyderabad, India | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICFHR | ||
Notes | DAG; 600.162; 600.140; 602.230 | Approved | no | ||
Call Number | Admin @ si @ BRF2022b | Serial | 3740 | ||
Permanent link to this record |