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Author |
Jun Wan; Yibing Zhao; Shuai Zhou; Isabelle Guyon; Sergio Escalera |
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Title |
ChaLearn Looking at People RGB-D Isolated and Continuous Datasets for Gesture Recognition |
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Conference Article |
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2016 |
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29th IEEE Conference on Computer Vision and Pattern Recognition Worshops |
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In this paper, we present two large video multi-modal datasets for RGB and RGB-D gesture recognition: the ChaLearn LAP RGB-D Isolated Gesture Dataset (IsoGD)and the Continuous Gesture Dataset (ConGD). Both datasets are derived from the ChaLearn Gesture Dataset
(CGD) that has a total of more than 50000 gestures for the “one-shot-learning” competition. To increase the potential of the old dataset, we designed new well curated datasets composed of 249 gesture labels, and including 47933 gestures manually labeled the begin and end frames in sequences.Using these datasets we will open two competitions
on the CodaLab platform so that researchers can test and compare their methods for “user independent” gesture recognition. The first challenge is designed for gesture spotting
and recognition in continuous sequences of gestures while the second one is designed for gesture classification from segmented data. The baseline method based on the bag of visual words model is also presented. |
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Las Vegas; USA; July 2016 |
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CVPRW |
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HuPBA;MILAB; |
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no |
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Admin @ si @ WZZ2016 |
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2771 |
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Author |
Miguel Reyes; Jordi Vitria; Petia Radeva; Sergio Escalera |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Real-time Activity Monitoring of Inpatients |
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Conference Article |
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2010 |
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Medical Image Computing in Catalunya: Graduate Student Workshop |
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35–36 |
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In this paper, we present the development of an application capable of monitoring a set of patient vital signs in real time. The application has been designed to support the medical staff of a hospital. Preliminary results show the suitability
of the system to prevent the injury produced by the agitation of the patients. |
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Girona |
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MICCAT |
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OR;MILAB;HUPBA;MV |
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BCNPCL @ bcnpcl @ RVR2010 |
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1477 |
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Author |
V. Poulain d'Andecy; Emmanuel Hartmann; Marçal Rusiñol |
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Title |
Field Extraction by hybrid incremental and a-priori structural templates |
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Conference Article |
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2018 |
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13th IAPR International Workshop on Document Analysis Systems |
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251 - 256 |
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Layout Analysis; information extraction; incremental learning |
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In this paper, we present an incremental framework for extracting information fields from administrative documents. First, we demonstrate some limits of the existing state-of-the-art methods such as the delay of the system efficiency. This is a concern in industrial context when we have only few samples of each document class. Based on this analysis, we propose a hybrid system combining incremental learning by means of itf-df statistics and a-priori generic
models. We report in the experimental section our results obtained with a dataset of real invoices. |
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Viena; Austria; April 2018 |
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DAG; 600.084; 600.129; 600.121 |
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Admin @ si @ PHR2018 |
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3106 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Query Driven Word Retrieval in Graphical Documents |
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Conference Article |
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2010 |
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9th IAPR International Workshop on Document Analysis Systems |
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191–198 |
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In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents. |
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Boston; USA |
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978-1-60558-773-8 |
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DAG |
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no |
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DAG @ dag @ RPL2010b |
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1433 |
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Author |
Marçal Rusiñol; Josep Llados |
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Title |
Efficient Logo Retrieval Through Hashing Shape Context Descriptors |
Type |
Conference Article |
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Year |
2010 |
Publication |
9th IAPR International Workshop on Document Analysis Systems |
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215–222 |
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Abstract ![sorted by Abstract field, descending order (down)](img/sort_desc.gif) |
In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents. |
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Boston; USA |
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DAG |
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DAG @ dag @ RuL2010b |
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1434 |
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Author |
David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados |
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Title |
Integrating Visual and Textual Cues for Query-by-String Word Spotting |
Type |
Conference Article |
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2013 |
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12th International Conference on Document Analysis and Recognition |
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511 - 515 |
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In this paper, we present a word spotting framework that follows the query-by-string paradigm where word images are represented both by textual and visual representations. The textual representation is formulated in terms of character $n$-grams while the visual one is based on the bag-of-visual-words scheme. These two representations are merged together and projected to a sub-vector space. This transform allows to, given a textual query, retrieve word instances that were only represented by the visual modality. Moreover, this statistical representation can be used together with state-of-the-art indexation structures in order to deal with large-scale scenarios. The proposed method is evaluated using a collection of historical documents outperforming state-of-the-art performances. |
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Washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
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DAG; ADAS; 600.045; 600.055; 600.061 |
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no |
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Admin @ si @ ART2013 |
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2224 |
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Author |
Thanh Ha Do; Oriol Ramos Terrades; Salvatore Tabbone |
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Title |
DSD: document sparse-based denoising algorithm |
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Journal Article |
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2019 |
Publication |
Pattern Analysis and Applications |
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PAA |
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22 |
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1 |
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177–186 |
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Document denoising; Sparse representations; Sparse dictionary learning; Document degradation models |
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In this paper, we present a sparse-based denoising algorithm for scanned documents. This method can be applied to any kind of scanned documents with satisfactory results. Unlike other approaches, the proposed approach encodes noise documents through sparse representation and visual dictionary learning techniques without any prior noise model. Moreover, we propose a precision parameter estimator. Experiments on several datasets demonstrate the robustness of the proposed approach compared to the state-of-the-art methods on document denoising. |
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DAG; 600.097; 600.140; 600.121 |
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Admin @ si @ DRT2019 |
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3254 |
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Author |
Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados |
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Title |
Browsing Heterogeneous Document Collections by a Segmentation-Free Word Spotting Method |
Type |
Conference Article |
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2011 |
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11th International Conference on Document Analysis and Recognition |
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63-67 |
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In this paper, we present a segmentation-free word spotting method that is able to deal with heterogeneous document image collections. We propose a patch-based framework where patches are represented by a bag-of-visual-words model powered by SIFT descriptors. A later refinement of the feature vectors is performed by applying the latent semantic indexing technique. The proposed method performs well on both handwritten and typewritten historical document images. We have also tested our method on documents written in non-Latin scripts. |
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Beijing, China |
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DAG;ADAS |
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Admin @ si @ RAT2011 |
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1788 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados; Mathieu Nicolas Delalandre |
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Title |
Multi-Oriented and Multi-Sized Touching Character Segmentation using Dynamic Programming |
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Conference Article |
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2009 |
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10th International Conference on Document Analysis and Recognition |
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11–15 |
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In this paper, we present a scheme towards the segmentation of English multi-oriented touching strings into individual characters. When two or more characters touch, they generate a big cavity region at the background portion. Using Convex Hull information, we use these background information to find some initial points to segment a touching string into possible primitive segments (a primitive segment consists of a single character or a part of a character). Next these primitive segments are merged to get optimum segmentation and dynamic programming is applied using total likelihood of characters as the objective function. SVM classifier is used to find the likelihood of a character. To consider multi-oriented touching strings the features used in the SVM are invariant to character orientation. Circular ring and convex hull ring based approach has been used along with angular information of the contour pixels of the character to make the feature rotation invariant. From the experiment, we obtained encouraging results. |
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Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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DAG |
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DAG @ dag @ RPL2009a |
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1240 |
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Marçal Rusiñol; Volkmar Frinken; Dimosthenis Karatzas; Andrew Bagdanov; Josep Llados |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Multimodal page classification in administrative document image streams |
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Journal Article |
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2014 |
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International Journal on Document Analysis and Recognition |
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IJDAR |
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17 |
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4 |
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331-341 |
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Digital mail room; Multimodal page classification; Visual and textual document description |
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Abstract ![sorted by Abstract field, descending order (down)](img/sort_desc.gif) |
In this paper, we present a page classification application in a banking workflow. The proposed architecture represents administrative document images by merging visual and textual descriptions. The visual description is based on a hierarchical representation of the pixel intensity distribution. The textual description uses latent semantic analysis to represent document content as a mixture of topics. Several off-the-shelf classifiers and different strategies for combining visual and textual cues have been evaluated. A final step uses an n-gram model of the page stream allowing a finer-grained classification of pages. The proposed method has been tested in a real large-scale environment and we report results on a dataset of 70,000 pages. |
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Springer Berlin Heidelberg |
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1433-2833 |
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DAG; LAMP; 600.056; 600.061; 601.240; 601.223; 600.077; 600.079 |
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Admin @ si @ RFK2014 |
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2523 |
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Miguel Oliveira; Victor Santos; Angel Sappa; P. Dias |
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Title |
Scene Representations for Autonomous Driving: an approach based on polygonal primitives |
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Conference Article |
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2015 |
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2nd Iberian Robotics Conference ROBOT2015 |
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417 |
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503-515 |
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Scene reconstruction; Point cloud; Autonomous vehicles |
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In this paper, we present a novel methodology to compute a 3D scene
representation. The algorithm uses macro scale polygonal primitives to model the scene. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Results show that the approach is capable of producing accurate descriptions of the scene. In addition, the algorithm is very efficient when compared to other techniques. |
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Lisboa; Portugal; November 2015 |
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ROBOT |
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ADAS; 600.076; 600.086 |
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Admin @ si @ OSS2015a |
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2662 |
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Author |
Razieh Rastgoo; Kourosh Kiani; Sergio Escalera |
![goto web page url](img/www.gif)
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Title |
A deep co-attentive hand-based video question answering framework using multi-view skeleton |
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Journal Article |
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2023 |
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Multimedia Tools and Applications |
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MTAP |
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82 |
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1401–1429 |
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In this paper, we present a novel hand –based Video Question Answering framework, entitled Multi-View Video Question Answering (MV-VQA), employing the Single Shot Detector (SSD), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Bidirectional Encoder Representations from Transformers (BERT), and Co-Attention mechanism with RGB videos as the inputs. Our model includes three main blocks: vision, language, and attention. In the vision block, we employ a novel representation to obtain some efficient multiview features from the hand object using the combination of five 3DCNNs and one LSTM network. To obtain the question embedding, we use the BERT model in language block. Finally, we employ a co-attention mechanism on vision and language features to recognize the final answer. For the first time, we propose such a hand-based Video-QA framework including the multi-view hand skeleton features combined with the question embedding and co-attention mechanism. Our framework is capable of processing the arbitrary numbers of questions in the dataset annotations. There are different application domains for this framework. Here, as an application domain, we applied our framework to dynamic hand gesture recognition for the first time. Since the main object in dynamic hand gesture recognition is the human hand, we performed a step-by-step analysis of the hand detection and multi-view hand skeleton impact on the model performance. Evaluation results on five datasets, including two datasets in VideoQA, two datasets in dynamic hand gesture, and one dataset in hand action recognition show that MV-VQA outperforms state-of-the-art alternatives. |
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HUPBA |
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Admin @ si @ RKE2023b |
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3881 |
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Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Towards Query-by-Speech Handwritten Keyword Spotting |
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Conference Article |
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2015 |
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13th International Conference on Document Analysis and Recognition ICDAR2015 |
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501-505 |
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In this paper, we present a new querying paradigm for handwritten keyword spotting. We propose to represent handwritten word images both by visual and audio representations, enabling a query-by-speech keyword spotting system. The two representations are merged together and projected to a common sub-space in the training phase. This transform allows to, given a spoken query, retrieve word instances that were only represented by the visual modality. In addition, the same method can be used backwards at no additional cost to produce a handwritten text-tospeech system. We present our first results on this new querying mechanism using synthetic voices over the George Washington
dataset. |
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Nancy; France; August 2015 |
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DAG; 600.084; 600.061; 601.223; 600.077;ADAS |
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Admin @ si @ RAT2015b |
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2682 |
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Author |
E. Tavalera; Mariella Dimiccoli; Marc Bolaños; Maedeh Aghaei; Petia Radeva |
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Title |
Regularized Clustering for Egocentric Video Segmentation |
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Book Chapter |
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2015 |
Publication |
Pattern Recognition and Image Analysis |
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327-336 |
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Temporal video segmentation ; Egocentric videos ; Clustering |
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In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energyminimization framework. Given the tendency of most AC methods to oversegment video sequences when clustering their frames, we combine the clustering with a concept drift detection technique (ADWIN) that has rigorous guarantee of performances. ADWIN serves as a statistical upper bound for the clustering-based video segmentation. We integrate techniques in an energy-minimization framework that serves disambiguate the decision of both techniques and to complete the segmentation taking into account the temporal continuity of video frames We present experiments over egocentric sets of more than 13.000 images acquired with different wearable cameras, showing that our method outperforms state-of-the-art clustering methods. |
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Springer International Publishing |
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978-3-319-19390-8 |
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MILAB |
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Admin @ si @TDB2015a |
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2781 |
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Estefania Talavera; Mariella Dimiccoli; Marc Bolaños; Maedeh Aghaei; Petia Radeva |
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Title |
R-clustering for egocentric video segmentation |
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Conference Article |
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Year |
2015 |
Publication |
Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 |
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9117 |
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327-336 |
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Temporal video segmentation; Egocentric videos; Clustering |
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In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energy-minimization framework. Given the tendency of most AC methods to oversegment video sequences when clustering their frames, we combine the clustering with a concept drift detection technique (ADWIN) that has rigorous guarantee of performances. ADWIN serves as a statistical upper bound for the clustering-based video segmentation. We integrate both techniques in an energy-minimization framework that serves to disambiguate the decision of both techniques and to complete the segmentation taking into account the temporal continuity of video frames descriptors. We present experiments over egocentric sets of more than 13.000 images acquired with different wearable cameras, showing that our method outperforms state-of-the-art clustering methods. |
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Santiago de Compostela; España; June 2015 |
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Springer International Publishing |
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0302-9743 |
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978-3-319-19389-2 |
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IbPRIA |
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MILAB |
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Admin @ si @ TDB2015 |
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2597 |
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