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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 | ||||
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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 | Christophe Rigaud; Clement Guerin | ||||
Title | Localisation contextuelle des personnages de bandes dessinées | Type | Conference Article | ||
Year | 2014 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
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Abstract | Les auteurs proposent une méthode de localisation des personnages dans des cases de bandes dessinées en s'appuyant sur les caractéristiques des bulles de dialogue. L'évaluation montre un taux de localisation des personnages allant jusqu'à 65%. | ||||
Address | Nancy; Francia; March 2014 | ||||
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Area | Expedition | Conference | CIFED | ||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RiG2014 | Serial | 2481 | ||
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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 | 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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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
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 | Enric Marti; Antoni Gurgui; Debora Gil; Aura Hernandez-Sabate; Jaume Rocarias; Ferran Poveda | ||||
Title | ABP on line: Seguimiento, estregas y evaluación en aprendizaje basado en proyectos | Type | Miscellaneous | ||
Year | 2014 | Publication | 8th International Congress on University Teaching and Innovation | Abbreviated Journal | |
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Address | Tarragona; juliol 2014 | ||||
Corporate Author | Thesis | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CIDUI | ||
Notes | IAM; ADAS; 600.076; 600.063; 600.075 | Approved | no | ||
Call Number | Admin @ si @ MGG2014 | Serial | 2457 | ||
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Author | Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; Jaume Rocarias; Debora Gil | ||||
Title | Evaluación automática de prácticas en Moodle para el aprendizaje autónomo en Ingenierías | Type | Miscellaneous | ||
Year | 2014 | Publication | 8th International Congress on University Teaching and Innovation | Abbreviated Journal | |
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Address | Tarragona; juliol 2014 | ||||
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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CIDUI | ||
Notes | IAM; 600.075;DAG | Approved | no | ||
Call Number | Admin @ si @ SRM2014 | Serial | 2458 | ||
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Author | Maedeh Aghaei; Petia Radeva | ||||
Title | Bag-of-Tracklets for Person Tracking in Life-Logging Data | Type | Conference Article | ||
Year | 2014 | Publication | 17th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
Volume | 269 | Issue | Pages | 35-44 | |
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Abstract | 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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Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-1-61499-451-0 | Medium | ||
Area | Expedition | Conference | CCIA | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ AgR2015 | Serial | 2607 | ||
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Author | Agata Lapedriza; David Masip; David Sanchez | ||||
Title | Emotions Classification using Facial Action Units Recognition | Type | Conference Article | ||
Year | 2014 | Publication | 17th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
Volume | 269 | Issue | Pages | 55-64 | |
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Abstract | In this work we build a system for automatic emotion classification from image sequences. We analyze subtle changes in facial expressions by detecting a subset of 12 representative facial action units (AUs). Then, we classify emotions based on the output of these AUs classifiers, i.e. the presence/absence of AUs. We base the AUs classification upon a set of spatio-temporal geometric and appearance features for facial representation, fusing them within the emotion classifier. A decision tree is trained for emotion classifying, making the resulting model easy to interpret by capturing the combination of AUs activation that lead to a particular emotion. For Cohn-Kanade database, the proposed system classifies 7 emotions with a mean accuracy of near 90%, attaining a similar recognition accuracy in comparison with non-interpretable models that are not based in AUs detection. | ||||
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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 | 978-1-61499-451-0 | Medium | ||
Area | Expedition | Conference | CCIA | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ LMS2014 | Serial | 2622 | ||
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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 | 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 | |||
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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 | Adria Ruiz; Joost Van de Weijer; Xavier Binefa | ||||
Title | Regularized Multi-Concept MIL for weakly-supervised facial behavior categorization | Type | Conference Article | ||
Year | 2014 | Publication | 25th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | We address the problem of estimating high-level semantic labels for videos of recorded people by means of analysing their facial expressions. This problem, to which we refer as facial behavior categorization, is a weakly-supervised learning problem where we do not have access to frame-by-frame facial gesture annotations but only weak-labels at the video level are available. Therefore, the goal is to learn a set of discriminative expressions and how they determine the video weak-labels. Facial behavior categorization can be posed as a Multi-Instance-Learning (MIL) problem and we propose a novel MIL method called Regularized Multi-Concept MIL to solve it. In contrast to previous approaches applied in facial behavior analysis, RMC-MIL follows a Multi-Concept assumption which allows different facial expressions (concepts) to contribute differently to the video-label. Moreover, to handle with the high-dimensional nature of facial-descriptors, RMC-MIL uses a discriminative approach to model the concepts and structured sparsity regularization to discard non-informative features. RMC-MIL is posed as a convex-constrained optimization problem where all the parameters are jointly learned using the Projected-Quasi-Newton method. In our experiments, we use two public data-sets to show the advantages of the Regularized Multi-Concept approach and its improvement compared to existing MIL methods. RMC-MIL outperforms state-of-the-art results in the UNBC data-set for pain detection. | ||||
Address | Nottingham; UK; September 2014 | ||||
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Area | Expedition | Conference | BMVC | ||
Notes | LAMP; CIC; 600.074; 600.079 | Approved | no | ||
Call Number | Admin @ si @ RWB2014 | Serial | 2508 | ||
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Author | Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez | ||||
Title | Incremental Domain Adaptation of Deformable Part-based Models | Type | Conference Article | ||
Year | 2014 | Publication | 25th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Pedestrian Detection; Part-based models; Domain Adaptation | ||||
Abstract | Nowadays, classifiers play a core role in many computer vision tasks. The underlying assumption for learning classifiers is that the training set and the deployment environment (testing) follow the same probability distribution regarding the features used by the classifiers. However, in practice, there are different reasons that can break this constancy assumption. Accordingly, reusing existing classifiers by adapting them from the previous training environment (source domain) to the new testing one (target domain)
is an approach with increasing acceptance in the computer vision community. In this paper we focus on the domain adaptation of deformable part-based models (DPMs) for object detection. In particular, we focus on a relatively unexplored scenario, i.e. incremental domain adaptation for object detection assuming weak-labeling. Therefore, our algorithm is ready to improve existing source-oriented DPM-based detectors as soon as a little amount of labeled target-domain training data is available, and keeps improving as more of such data arrives in a continuous fashion. For achieving this, we follow a multiple instance learning (MIL) paradigm that operates in an incremental per-image basis. As proof of concept, we address the challenging scenario of adapting a DPM-based pedestrian detector trained with synthetic pedestrians to operate in real-world scenarios. The obtained results show that our incremental adaptive models obtain equally good accuracy results as the batch learned models, while being more flexible for handling continuously arriving target-domain data. |
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Address | Nottingham; uk; September 2014 | ||||
Corporate Author | Thesis | ||||
Publisher | BMVA Press | Place of Publication | Editor | Valstar, Michel and French, Andrew and Pridmore, Tony | |
Language | Summary Language | Original Title | |||
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Area | Expedition | Conference | BMVC | ||
Notes | ADAS; 600.057; 600.054; 600.076 | Approved | no | ||
Call Number | XRV2014c; ADAS @ adas @ xrv2014c | Serial | 2455 | ||
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Author | Antonio Hernandez; Stan Sclaroff; Sergio Escalera | ||||
Title | Contextual rescoring for Human Pose Estimation | Type | Conference Article | ||
Year | 2014 | Publication | 25th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | A contextual rescoring method is proposed for improving the detection of body joints of a pictorial structure model for human pose estimation. A set of mid-level parts is incorporated in the model, and their detections are used to extract spatial and score-related features relative to other body joint hypotheses. A technique is proposed for the automatic discovery of a compact subset of poselets that covers a set of validation images
while maximizing precision. A rescoring mechanism is defined as a set-based boosting classifier that computes a new score for body joint detections, given its relationship to detections of other body joints and mid-level parts in the image. This new score complements the unary potential of a discriminatively trained pictorial structure model. Experiments on two benchmarks show performance improvements when considering the proposed mid-level image representation and rescoring approach in comparison with other pictorial structure-based approaches. |
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Address | Nottingham; UK; September 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | BMVC | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | HSE2014 | Serial | 2525 | ||
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Author | E. Bondi ; L. Sidenari; Andrew Bagdanov; Alberto del Bimbo | ||||
Title | Real-time people counting from depth imagery of crowded environments | Type | Conference Article | ||
Year | 2014 | Publication | 11th IEEE International Conference on Advanced Video and Signal based Surveillance | Abbreviated Journal | |
Volume | Issue | Pages | 337 - 342 | ||
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Abstract | In this paper we describe a system for automatic people counting in crowded environments. The approach we propose is a counting-by-detection method based on depth imagery. It is designed to be deployed as an autonomous appliance for crowd analysis in video surveillance application scenarios. Our system performs foreground/background segmentation on depth image streams in order to coarsely segment persons, then depth information is used to localize head candidates which are then tracked in time on an automatically estimated ground plane. The system runs in real-time, at a frame-rate of about 20 fps. We collected a dataset of RGB-D sequences representing three typical and challenging surveillance scenarios, including crowds, queuing and groups. An extensive comparative evaluation is given between our system and more complex, Latent SVM-based head localization for person counting applications. | ||||
Address | Seoul; Korea; August 2014 | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | AVSS | ||
Notes | LAMP; 600.079 | Approved | no | ||
Call Number | Admin @ si @ BSB2014 | Serial | 2540 | ||
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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 | ||
Permanent link to this record |