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Bogdan Raducanu; Jordi Vitria |
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A Robust Particle Filter-Based Face Tracker Using Combination of Color and Geometric Information |
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2006 |
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International Conference on Image Analysis and Recognition (ICIAR´06), LNCS 4141 (A. Campilho et al., eds.), 1: 922–933 |
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OR;MV |
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BCNPCL @ bcnpcl @ RaV2006c |
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715 |
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Author |
Joaquin Salas; P. Martinez; Jordi Gonzalez |
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Title |
Background Updating with the Use of Intrinsic Curves |
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2006 |
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International Conference on Image Analysis and Recognition (ICIAR´06), LNCS 4141 (A. Campilho et al., eds.), 1: 731–742, ISBN 978–3–540–44891–4 |
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ISE @ ise @ SMG2006 |
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768 |
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Author |
Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez |
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Title |
Real Time Vehicle Pose Using On-Board Stereo Vision System |
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Conference Article |
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2006 |
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International Conference on Image Analysis and Recognition |
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ICIAR |
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LNCS 4142 |
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205–216 |
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This paper presents a robust technique for a real time estimation of both camera’s position and orientation—referred as pose. A commercial stereo vision system is used. Unlike previous approaches, it can be used either for urban or highway scenarios. The proposed technique consists of two stages. Initially, a compact 2D representation of the original 3D data points is computed. Then, a RANSAC based least squares approach is used for fitting a plane to the road. At the same time,
relative camera’s position and orientation are computed. The proposed technique is intended to be used on a driving assistance scheme for applications such as obstacle or pedestrian detection. Experimental results on urban environments with different road geometries are presented. |
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ADAS @ adas @ SGD2006b |
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671 |
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Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
An Iterative Multiresolution Scheme for SFM |
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Conference Article |
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2006 |
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International Conference on Image Analysis and Recognition |
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ICIAR 2006 |
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LNCS 4141 |
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1 |
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804–815 |
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ADAS @ adas @ JSL2006c |
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704 |
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Author |
Giacomo Magnifico; Beata Megyesi; Mohamed Ali Souibgui; Jialuo Chen; Alicia Fornes |
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Title |
Lost in Transcription of Graphic Signs in Ciphers |
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Conference Article |
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2022 |
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International Conference on Historical Cryptology (HistoCrypt 2022) |
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153-158 |
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transcription of ciphers; hand-written text recognition of symbols; graphic signs |
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Hand-written Text Recognition techniques with the aim to automatically identify and transcribe hand-written text have been applied to historical sources including ciphers. In this paper, we compare the performance of two machine learning architectures, an unsupervised method based on clustering and a deep learning method with few-shot learning. Both models are tested on seen and unseen data from historical ciphers with different symbol sets consisting of various types of graphic signs. We compare the models and highlight their differences in performance, with their advantages and shortcomings. |
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Amsterdam, Netherlands, June 20-22, 2022 |
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HystoCrypt |
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DAG; 600.121; 600.162; 602.230; 600.140 |
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Admin @ si @ MBS2022 |
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3731 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Morphology Based Handwritten Line Segmentation using Foreground and Background Information |
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Conference Article |
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2008 |
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International Conference on Frontiers in Handwriting Recognition, |
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241–246 |
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Montreal (Canada) |
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ICFHR |
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DAG |
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DAG @ dag @ RPL2008a |
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1050 |
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Author |
Jose Antonio Rodriguez; Florent Perronnin |
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Title |
Local Gradient Histogram Features for Word Spotting in Unconstrained Handwritten Documents |
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2008 |
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International Conference on Frontiers in Handwriting Recognition |
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7–12 |
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Montreal (Canada) |
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ICFHR |
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no |
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Admin @ si @ RoP2008b |
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1066 |
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Author |
Jose Antonio Rodriguez; Florent Perronnin |
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Title |
Score Normalization for Hmm-based Word Spotting Using Universal Background Model |
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Conference Article |
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2008 |
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International Conference on Frontiers in Handwriting Recognition |
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82–87 |
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Montreal (Canada) |
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ICFHR |
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Admin @ si @ RoP2008c |
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1067 |
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Author |
Helena Muñoz; Fernando Vilariño; Dimosthenis Karatzas |
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Title |
Eye-Movements During Information Extraction from Administrative Documents |
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2019 |
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International Conference on Document Analysis and Recognition Workshops |
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6-9 |
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A key aspect of digital mailroom processes is the extraction of relevant information from administrative documents. More often than not, the extraction process cannot be fully automated, and there is instead an important amount of manual intervention. In this work we study the human process of information extraction from invoice document images. We explore whether the gaze of human annotators during an manual information extraction process could be exploited towards reducing the manual effort and automating the process. To this end, we perform an eye-tracking experiment replicating real-life interfaces for information extraction. Through this pilot study we demonstrate that relevant areas in the document can be identified reliably through automatic fixation classification, and the obtained models generalize well to new subjects. Our findings indicate that it is in principle possible to integrate the human in the document image analysis loop, making use of the scanpath to automate the extraction process or verify extracted information. |
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Sydney; Australia; September 2019 |
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ICDARW |
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DAG; 600.140; 600.121; 600.129;SIAI |
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no |
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Admin @ si @ MVK2019 |
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3336 |
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Author |
Mariella Dimiccoli; Petia Radeva |
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Title |
Lifelogging in the era of outstanding digitization |
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2015 |
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International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage |
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In this paper, we give an overview on the emerging trend of the digitized self, focusing on visual lifelogging through wearable cameras. This is about continuously recording our life from a first-person view by wearing a camera that passively captures images. On one hand, visual lifelogging has opened the door to a large number of applications, including health. On the other, it has also boosted new challenges in the field of data analysis as well as new ethical concerns. While currently increasing efforts are being devoted to exploit lifelogging data for the improvement of personal well-being, we believe there are still many interesting applications to explore, ranging from tourism to the digitization of human behavior. |
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Verliko Tarmovo; Bulgaria; September 2015 |
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DiPP |
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MILAB |
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no |
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Admin @ si @DiR2016 |
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2792 |
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Author |
Pedro Martins; Paulo Carvalho; Carlo Gatta |
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Stable Salient Shapes |
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2012 |
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International Conference on Digital Image Computing: Techniques and Applications |
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DICTA |
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MILAB |
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Admin @ si @ MCG2012b |
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2166 |
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Partha Pratim Roy; Josep Llados; Umapada Pal |
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Text/Graphics Separation in Color Maps |
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2007 |
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International Conference on Computing: Theory and Applications |
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545–551 |
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Kolkata (India) |
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DAG @ dag @ RLP2007a |
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806 |
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Petia Radeva; Enric Marti |
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Facial Features Segmentation by Model-Based Snakes |
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1995 |
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International Conference on Computing Analysis and Image Processing |
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Deformable models have recently been accepted as a standard technique to segment different features in facial images. Despite they give a good approximation of the salient features in a facial image, the resulting shapes of the segmentation process seem somewhat artificial with respect to the natural feature shapes. In this paper we show that active contour models (in particular, rubber snakes) give more close and natural representation of the detected feature shape. Besides, using snakes for facial segmentation frees us from the problem of determination of the numerous weigths of deformable models. Another advantage of rubber snakes is their reduced computational cost. Our experiments using rubber snakes for segmentation of facial snapshots have shown a significant improvement compared to deformable models. |
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Bellaterra (Barcelona), Spain |
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MILAB;IAM |
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IAM @ iam @ RAM1995a |
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1633 |
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Joost Van de Weijer; Shida Beigpour |
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The Dichromatic Reflection Model: Future Research Directions and Applications |
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2011 |
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International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
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dblp |
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The dichromatic reflection model (DRM) predicts that color distributions form a parallelogram in color space, whose shape is defined by the body reflectance and the illuminant color. In this paper we resume the assumptions which led to the DRM and shortly recall two of its main applications domains: color image segmentation and photometric invariant feature computation. After having introduced the model we discuss several limitations of the theory, especially those which are raised once working on real-world uncalibrated images. In addition, we summerize recent extensions of the model which allow to handle more complicated light interactions. Finally, we suggest some future research directions which would further extend its applicability. |
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Algarve, Portugal |
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SciTePress |
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Mestetskiy, Leonid and Braz, José |
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978-989-8425-47-8 |
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VISIGRAPP |
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CIC |
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no |
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Admin @ si @ WeB2011 |
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1778 |
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Javad Zolfaghari Bengar; Joost Van de Weijer; Bartlomiej Twardowski; Bogdan Raducanu |
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Title |
Reducing Label Effort: Self- Supervised Meets Active Learning |
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2021 |
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International Conference on Computer Vision Workshops |
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1631-1639 |
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Active learning is a paradigm aimed at reducing the annotation effort by training the model on actively selected informative and/or representative samples. Another paradigm to reduce the annotation effort is self-training that learns from a large amount of unlabeled data in an unsupervised way and fine-tunes on few labeled samples. Recent developments in self-training have achieved very impressive results rivaling supervised learning on some datasets. The current work focuses on whether the two paradigms can benefit from each other. We studied object recognition datasets including CIFAR10, CIFAR100 and Tiny ImageNet with several labeling budgets for the evaluations. Our experiments reveal that self-training is remarkably more efficient than active learning at reducing the labeling effort, that for a low labeling budget, active learning offers no benefit to self-training, and finally that the combination of active learning and self-training is fruitful when the labeling budget is high. The performance gap between active learning trained either with self-training or from scratch diminishes as we approach to the point where almost half of the dataset is labeled. |
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October 2021 |
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|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICCVW |
|
| |
Notes |
LAMP; OR |
Approved |
no |
|
| |
Call Number |
Admin @ si @ ZVT2021 |
Serial |
3672 |
|
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