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Author |
Joan Serrat; Ferran Diego; Jose Manuel Alvarez; Felipe Lumbreras |
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Title |
Alignment of Videos Recorded from Moving Vehicles |
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Conference Article |
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Year |
2007 |
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in 14th International Conference on Image Analysis and Processing, |
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512–517 |
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Modena (Italia) |
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ADAS @ adas @ SDA2007 |
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879 |
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Katerine Diaz; Jesus Martinez del Rincon; Aura Hernandez-Sabate; Marçal Rusiñol; Francesc J. Ferri |
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Title |
Fast Kernel Generalized Discriminative Common Vectors for Feature Extraction |
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Journal Article |
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Year |
2018 |
Publication |
Journal of Mathematical Imaging and Vision |
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JMIV |
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60 |
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4 |
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512-524 |
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This paper presents a supervised subspace learning method called Kernel Generalized Discriminative Common Vectors (KGDCV), as a novel extension of the known Discriminative Common Vectors method with Kernels. Our method combines the advantages of kernel methods to model complex data and solve nonlinear
problems with moderate computational complexity, with the better generalization properties of generalized approaches for large dimensional data. These attractive combination makes KGDCV specially suited for feature extraction and classification in computer vision, image processing and pattern recognition applications. Two different approaches to this generalization are proposed, a first one based on the kernel trick (KT) and a second one based on the nonlinear projection trick (NPT) for even higher efficiency. Both methodologies
have been validated on four different image datasets containing faces, objects and handwritten digits, and compared against well known non-linear state-of-art methods. Results show better discriminant properties than other generalized approaches both linear or kernel. In addition, the KGDCV-NPT approach presents a considerable computational gain, without compromising the accuracy of the model. |
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DAG; ADAS; 600.086; 600.130; 600.121; 600.118; 600.129 |
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no |
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Admin @ si @ DMH2018a |
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3062 |
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Author |
Raul Gomez; Lluis Gomez; Jaume Gibert; Dimosthenis Karatzas |
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Title |
Learning to Learn from Web Data through Deep Semantic Embeddings |
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Conference Article |
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Year |
2018 |
Publication |
15th European Conference on Computer Vision Workshops |
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11134 |
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514-529 |
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In this paper we propose to learn a multimodal image and text embedding from Web and Social Media data, aiming to leverage the semantic knowledge learnt in the text domain and transfer it to a visual model for semantic image retrieval. We demonstrate that the pipeline can learn from images with associated text without supervision and perform a thourough analysis of five different text embeddings in three different benchmarks. We show that the embeddings learnt with Web and Social Media data have competitive performances over supervised methods in the text based image retrieval task, and we clearly outperform state of the art in the MIRFlickr dataset when training in the target data. Further we demonstrate how semantic multimodal image retrieval can be performed using the learnt embeddings, going beyond classical instance-level retrieval problems. Finally, we present a new dataset, InstaCities1M, composed by Instagram images and their associated texts that can be used for fair comparison of image-text embeddings. |
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Munich; Alemanya; September 2018 |
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ECCVW |
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DAG; 600.129; 601.338; 600.121 |
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no |
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Admin @ si @ GGG2018a |
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3175 |
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Author |
Petia Radeva; Enric Marti |
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Title |
An improved model of snakes for model-based segmentation |
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Conference Article |
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Year |
1995 |
Publication |
Proceedings of Computer Analysis of Images and Patterns |
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515-520 |
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The main advantage of segmentation by snakes consists in its ability to incorporate smoothness constraints on the detected shapes that can occur. Likewise, we propose to model snakes with other properties that reflect the information provided about the object of interest in a different extent. We consider different kinds of snakes, those searching for contours with a certain direction, those preserving an object’s model, those seeking for symmetry, those expanding open, etc. The availability of such a collection of snakes allows not only the more complete use of the knowledge about the segmented object, but also to solve some problems of the existing snakes. Our experiments on segmentation of facial features justify the usefulness of snakes with different properties. |
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CAIP |
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MILAB;IAM |
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no |
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IAM @ iam @ RaM1995b |
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1632 |
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Author |
Palaiahnakote Shivakumara; Anjan Dutta; Chew Lim Tan; Umapada Pal |
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Title |
Multi-oriented scene text detection in video based on wavelet and angle projection boundary growing |
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Journal Article |
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Year |
2014 |
Publication |
Multimedia Tools and Applications |
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MTAP |
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72 |
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1 |
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515-539 |
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In this paper, we address two complex issues: 1) Text frame classification and 2) Multi-oriented text detection in video text frame. We first divide a video frame into 16 blocks and propose a combination of wavelet and median-moments with k-means clustering at the block level to identify probable text blocks. For each probable text block, the method applies the same combination of feature with k-means clustering over a sliding window running through the blocks to identify potential text candidates. We introduce a new idea of symmetry on text candidates in each block based on the observation that pixel distribution in text exhibits a symmetric pattern. The method integrates all blocks containing text candidates in the frame and then all text candidates are mapped on to a Sobel edge map of the original frame to obtain text representatives. To tackle the multi-orientation problem, we present a new method called Angle Projection Boundary Growing (APBG) which is an iterative algorithm and works based on a nearest neighbor concept. APBG is then applied on the text representatives to fix the bounding box for multi-oriented text lines in the video frame. Directional information is used to eliminate false positives. Experimental results on a variety of datasets such as non-horizontal, horizontal, publicly available data (Hua’s data) and ICDAR-03 competition data (camera images) show that the proposed method outperforms existing methods proposed for video and the state of the art methods for scene text as well. |
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Springer US |
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1380-7501 |
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DAG; 600.077 |
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no |
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Admin @ si @ SDT2014 |
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2357 |
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Author |
Spencer Low; Oliver Nina; Angel Sappa; Erik Blasch; Nathan Inkawhich |
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Title |
Multi-Modal Aerial View Image Challenge: Translation From Synthetic Aperture Radar to Electro-Optical Domain Results-PBVS 2023 |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops |
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515-523 |
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This paper unveils the discoveries and outcomes of the inaugural iteration of the Multi-modal Aerial View Image Challenge (MAVIC) aimed at image translation. The primary objective of this competition is to stimulate research efforts towards the development of models capable of translating co-aligned images between multiple modalities. To accomplish the task of image translation, the competition utilizes images obtained from both synthetic aperture radar (SAR) and electro-optical (EO) sources. Specifically, the challenge centers on the translation from the SAR modality to the EO modality, an area of research that has garnered attention. The inaugural challenge demonstrates the feasibility of the task. The dataset utilized in this challenge is derived from the UNIfied COincident Optical and Radar for recognitioN (UNICORN) dataset. We introduce an new version of the UNICORN dataset that is focused on enabling the sensor translation task. Performance evaluation is conducted using a combination of measures to ensure high fidelity and high accuracy translations. |
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Vancouver; Canada; June 2023 |
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CVPRW |
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MSIAU |
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no |
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Admin @ si @ LNS2023a |
Serial |
3913 |
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Author |
Joan Mas; Jose Antonio Rodriguez; Dimosthenis Karatzas; Gemma Sanchez; Josep Llados |
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Title |
HistoSketch: A Semi-Automatic Annotation Tool for Archival Documents |
Type |
Conference Article |
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Year |
2008 |
Publication |
Proceedings of the 8th International Workshop on Document Analysis Systems, |
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517–524 |
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Nara (Japan) |
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DAG |
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no |
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DAG @ dag @ MRK2008a |
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1061 |
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Author |
J.Poujol; Cristhian A. Aguilera-Carrasco; E.Danos; Boris X. Vintimilla; Ricardo Toledo; Angel Sappa |
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Title |
Visible-Thermal Fusion based Monocular Visual Odometry |
Type |
Conference Article |
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Year |
2015 |
Publication |
2nd Iberian Robotics Conference ROBOT2015 |
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Volume |
417 |
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517-528 |
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Monocular Visual Odometry; LWIR-RGB cross-spectral Imaging; Image Fusion. |
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The manuscript evaluates the performance of a monocular visual odometry approach when images from different spectra are considered, both independently and fused. The objective behind this evaluation is to analyze if classical approaches can be improved when the given images, which are from different spectra, are fused and represented in new domains. The images in these new domains should have some of the following properties: i) more robust to noisy data; ii) less sensitive to changes (e.g., lighting); iii) more rich in descriptive information, among other. In particular in the current work two different image fusion strategies are considered. Firstly, images from the visible and thermal spectrum are fused using a Discrete Wavelet Transform (DWT) approach. Secondly, a monochrome threshold strategy is considered. The obtained
representations are evaluated under a visual odometry framework, highlighting
their advantages and disadvantages, using different urban and semi-urban scenarios. Comparisons with both monocular-visible spectrum and monocular-infrared spectrum, are also provided showing the validity of the proposed approach. |
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Lisboa; Portugal; November 2015 |
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Springer International Publishing |
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2194-5357 |
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978-3-319-27145-3 |
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ROBOT |
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ADAS; 600.076; 600.086 |
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no |
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Admin @ si @ PAD2015 |
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2663 |
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Author |
Carlo Gatta; Oriol Pujol; Oriol Rodriguez-Leor; J. Mauri; Petia Radeva |
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Title |
Robust Image-based IVUS Pullbacks Gating |
Type |
Book Chapter |
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Year |
2008 |
Publication |
Proceedings 11th International ConferenceMedical Image Computing and Computer–Assisted Intervention |
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5242 |
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518–525 |
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NY (USA) |
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MICCAI |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ GPR2008a |
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1037 |
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Author |
Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie |
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Title |
Inferring the Performance of Medical Imaging Algorithms |
Type |
Conference Article |
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2011 |
Publication |
14th International Conference on Computer Analysis of Images and Patterns |
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6854 |
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520-528 |
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Validation, Statistical Inference, Medical Imaging Algorithms. |
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Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence. |
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Sevilla |
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Springer-Verlag Berlin Heidelberg |
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Berlin |
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Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch |
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IAM; ADAS |
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no |
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IAM @ iam @ HGR2011 |
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1676 |
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Author |
Marçal Rusiñol; Dimosthenis Karatzas; Andrew Bagdanov; Josep Llados |
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Title |
Multipage Document Retrieval by Textual and Visual Representations |
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Conference Article |
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2012 |
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21st International Conference on Pattern Recognition |
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521-524 |
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In this paper we present a multipage administrative document image retrieval system based on textual and visual representations of document pages. Individual pages are represented by textual or visual information using a bag-of-words framework. Different fusion strategies are evaluated which allow the system to perform multipage document retrieval on the basis of a single page retrieval system. Results are reported on a large dataset of document images sampled from a banking workflow. |
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Tsukuba Science City, Japan |
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1051-4651 |
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978-1-4673-2216-4 |
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ICPR |
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DAG |
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no |
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Admin @ si @ RKB2012 |
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2053 |
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Author |
Wenwen Yu; Mingyu Liu; Mingrui Chen; Ning Lu; Yinlong We; Yuliang Liu; Dimosthenis Karatzas; Xiang Bai |
![goto web page url](img/www.gif)
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Title |
ICDAR 2023 Competition on Reading the Seal Title |
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Conference Article |
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Year |
2023 |
Publication |
17th International Conference on Document Analysis and Recognition |
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14188 |
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Reading seal title text is a challenging task due to the variable shapes of seals, curved text, background noise, and overlapped text. However, this important element is commonly found in official and financial scenarios, and has not received the attention it deserves in the field of OCR technology. To promote research in this area, we organized ICDAR 2023 competition on reading the seal title (ReST), which included two tasks: seal title text detection (Task 1) and end-to-end seal title recognition (Task 2). We constructed a dataset of 10,000 real seal data, covering the most common classes of seals, and labeled all seal title texts with text polygons and text contents. The competition opened on 30th December, 2022 and closed on 20th March, 2023. The competition attracted 53 participants and received 135 submissions from academia and industry, including 28 participants and 72 submissions for Task 1, and 25 participants and 63 submissions for Task 2, which demonstrated significant interest in this challenging task. In this report, we present an overview of the competition, including the organization, challenges, and results. We describe the dataset and tasks, and summarize the submissions and evaluation results. The results show that significant progress has been made in the field of seal title text reading, and we hope that this competition will inspire further research and development in this important area of OCR technology. |
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San Jose; CA; USA; August 2023 |
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ICDAR |
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DAG |
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no |
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Call Number |
Admin @ si @ YLC2023 |
Serial |
3897 |
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Author |
Salvatore Tabbone; Oriol Ramos Terrades |
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Title |
An Overview of Symbol Recognition |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
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D |
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523-551 |
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Keywords |
Pattern recognition; Shape descriptors; Structural descriptors; Symbolrecognition; Symbol spotting |
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Abstract |
According to the Cambridge Dictionaries Online, a symbol is a sign, shape, or object that is used to represent something else. Symbol recognition is a subfield of general pattern recognition problems that focuses on identifying, detecting, and recognizing symbols in technical drawings, maps, or miscellaneous documents such as logos and musical scores. This chapter aims at providing the reader an overview of the different existing ways of describing and recognizing symbols and how the field has evolved to attain a certain degree of maturity. |
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Springer London |
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D. Doermann; K. Tombre |
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978-0-85729-858-4 |
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DAG; 600.077 |
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no |
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Call Number |
Admin @ si @ TaT2014 |
Serial |
2489 |
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Author |
Hamdi Dibeklioglu; Theo Gevers; Albert Ali Salah |
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Title |
Are You Really Smiling at Me? Spontaneous versus Posed Enjoyment Smiles |
Type |
Conference Article |
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Year |
2012 |
Publication |
12th European Conference on Computer Vision |
Abbreviated Journal |
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Volume |
7574 |
Issue |
III |
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525-538 |
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Abstract |
Smiling is an indispensable element of nonverbal social interaction. Besides, automatic distinction between spontaneous and posed expressions is important for visual analysis of social signals. Therefore, in this paper, we propose a method to distinguish between spontaneous and posed enjoyment smiles by using the dynamics of eyelid, cheek, and lip corner movements. The discriminative power of these movements, and the effect of different fusion levels are investigated on multiple databases. Our results improve the state-of-the-art. We also introduce the largest spontaneous/posed enjoyment smile database collected to date, and report new empirical and conceptual findings on smile dynamics. The collected database consists of 1240 samples of 400 subjects. Moreover, it has the unique property of having an age range from 8 to 76 years. Large scale experiments on the new database indicate that eyelid dynamics are highly relevant for smile classification, and there are age-related differences in smile dynamics. |
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Address |
Florence, Italy |
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Springer Berlin Heidelberg |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-33711-6 |
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Conference |
ECCV |
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Notes |
ALTRES;ISE |
Approved |
no |
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Call Number |
Admin @ si @ DGS2012 |
Serial |
2024 |
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Author |
Marta Diez-Ferrer; Debora Gil; Cristian Tebe; Carles Sanchez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Positive Airway Pressure to Enhance Computed Tomography Imaging for Airway Segmentation for Virtual Bronchoscopic Navigation |
Type |
Journal Article |
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Year |
2018 |
Publication |
Respiration |
Abbreviated Journal |
RES |
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Volume |
96 |
Issue |
6 |
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
525-534 |
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Keywords |
Multidetector computed tomography; Bronchoscopy; Continuous positive airway pressure; Image enhancement; Virtual bronchoscopic navigation |
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Abstract |
Abstract
RATIONALE:
Virtual bronchoscopic navigation (VBN) guidance to peripheral pulmonary lesions is often limited by insufficient segmentation of the peripheral airways.
OBJECTIVES:
To test the effect of applying positive airway pressure (PAP) during CT acquisition to improve segmentation, particularly at end-expiration.
METHODS:
CT acquisitions in inspiration and expiration with 4 PAP protocols were recorded prospectively and compared to baseline inspiratory acquisitions in 20 patients. The 4 protocols explored differences between devices (flow vs. turbine), exposures (within seconds vs. 15-min) and pressure levels (10 vs. 14 cmH2O). Segmentation quality was evaluated with the number of airways and number of endpoints reached. A generalized mixed-effects model explored the estimated effect of each protocol.
MEASUREMENTS AND MAIN RESULTS:
Patient characteristics and lung function did not significantly differ between protocols. Compared to baseline inspiratory acquisitions, expiratory acquisitions after 15 min of 14 cmH2O PAP segmented 1.63-fold more airways (95% CI 1.07-2.48; p = 0.018) and reached 1.34-fold more endpoints (95% CI 1.08-1.66; p = 0.004). Inspiratory acquisitions performed immediately under 10 cmH2O PAP reached 1.20-fold (95% CI 1.09-1.33; p < 0.001) more endpoints; after 15 min the increase was 1.14-fold (95% CI 1.05-1.24; p < 0.001).
CONCLUSIONS:
CT acquisitions with PAP segment more airways and reach more endpoints than baseline inspiratory acquisitions. The improvement is particularly evident at end-expiration after 15 min of 14 cmH2O PAP. Further studies must confirm that the improvement increases diagnostic yield when using VBN to evaluate peripheral pulmonary lesions. |
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Notes |
IAM; 600.145 |
Approved |
no |
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Call Number |
Admin @ si @ DGT2018 |
Serial |
3135 |
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Permanent link to this record |