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Author | Jean-Christophe Burie; J. Chazalon; M. Coustaty; S. Eskenazi; Muhammad Muzzamil Luqman; M. Mehri; Nibal Nayef; Jean-Marc Ogier; S. Prum; Marçal Rusiñol | ||||
Title | ICDAR2015 Competition on Smartphone Document Capture and OCR (SmartDoc) | Type | Conference Article | ||
Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
Volume | Issue | Pages | 1161 - 1165 | ||
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Abstract | Smartphones are enabling new ways of capture,
hence arises the need for seamless and reliable acquisition and digitization of documents, in order to convert them to editable, searchable and a more human-readable format. Current stateof-the-art works lack databases and baseline benchmarks for digitizing mobile captured documents. We have organized a competition for mobile document capture and OCR in order to address this issue. The competition is structured into two independent challenges: smartphone document capture, and smartphone OCR. This report describes the datasets for both challenges along with their ground truth, details the performance evaluation protocols which we used, and presents the final results of the participating methods. In total, we received 13 submissions: 8 for challenge-I, and 5 for challenge-2. |
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Address | Nancy; France; August 2015 | ||||
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Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.077; 601.223; 600.084 | Approved | no | ||
Call Number | Admin @ si @ BCC2015 | Serial | 2681 | ||
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Author | Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados | ||||
Title | Towards Query-by-Speech Handwritten Keyword Spotting | Type | Conference Article | ||
Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
Volume | Issue | Pages | 501-505 | ||
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Abstract | 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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Address | Nancy; France; August 2015 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.084; 600.061; 601.223; 600.077;ADAS | Approved | no | ||
Call Number | Admin @ si @ RAT2015b | Serial | 2682 | ||
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Author | Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados; R.Jain; D.Doermann | ||||
Title | Novel Line Verification for Multiple Instance Focused Retrieval in Document Collections | Type | Conference Article | ||
Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
Volume | Issue | Pages | 481-485 | ||
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Address | Nancy; France; August 2015 | ||||
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Language | Summary Language | Original Title | |||
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Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.077; 601.223; 600.084; 600.061 | Approved | no | ||
Call Number | Admin @ si @ GRK2015 | Serial | 2683 | ||
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Author | Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier; Josep Llados | ||||
Title | A Comparative Study of Local Detectors and Descriptors for Mobile Document Classification | Type | Conference Article | ||
Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
Volume | Issue | Pages | 596-600 | ||
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Abstract | In this paper we conduct a comparative study of local key-point detectors and local descriptors for the specific task of mobile document classification. A classification architecture based on direct matching of local descriptors is used as baseline for the comparative study. A set of four different key-point
detectors and four different local descriptors are tested in all the possible combinations. The experiments are conducted in a database consisting of 30 model documents acquired on 6 different backgrounds, totaling more than 36.000 test images. |
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Address | Nancy; France; August 2015 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.084; 600.61; 601.223; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RCO2015 | Serial | 2684 | ||
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Author | J. Chazalon; Marçal Rusiñol; Jean-Marc Ogier; Josep Llados | ||||
Title | A Semi-Automatic Groundtruthing Tool for Mobile-Captured Document Segmentation | Type | Conference Article | ||
Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
Volume | Issue | Pages | 621-625 | ||
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Abstract | This paper presents a novel way to generate groundtruth data for the evaluation of mobile document capture systems, focusing on the first stage of the image processing pipeline involved: document object detection and segmentation in lowquality preview frames. We introduce and describe a simple, robust and fast technique based on color markers which enables a semi-automated annotation of page corners. We also detail a technique for marker removal. Methods and tools presented in the paper were successfully used to annotate, in few hours, 24889
frames in 150 video files for the smartDOC competition at ICDAR 2015 |
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Address | Nancy; France; August 2015 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.084; 600.061; 601.223; 600.077 | Approved | no | ||
Call Number | Admin @ si @ CRO2015b | Serial | 2685 | ||
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Author | Mikhail Mozerov; Joost Van de Weijer | ||||
Title | Global Color Sparseness and a Local Statistics Prior for Fast Bilateral Filtering | Type | Journal Article | ||
Year | 2015 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal | TIP |
Volume | 24 | Issue | 12 | Pages | 5842-5853 |
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Abstract | The property of smoothing while preserving edges makes the bilateral filter a very popular image processing tool. However, its non-linear nature results in a computationally costly operation. Various works propose fast approximations to the bilateral filter. However, the majority does not generalize to vector input as is the case with color images. We propose a fast approximation to the bilateral filter for color images. The filter is based on two ideas. First, the number of colors, which occur in a single natural image, is limited. We exploit this color sparseness to rewrite the initial non-linear bilateral filter as a number of linear filter operations. Second, we impose a statistical prior to the image values that are locally present within the filter window. We show that this statistical prior leads to a closed-form solution of the bilateral filter. Finally, we combine both ideas into a single fast and accurate bilateral filter for color images. Experimental results show that our bilateral filter based on the local prior yields an extremely fast bilateral filter approximation, but with limited accuracy, which has potential application in real-time video filtering. Our bilateral filter, which combines color sparseness and local statistics, yields a fast and accurate bilateral filter approximation and obtains the state-of-the-art results. | ||||
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ISSN | 1057-7149 | ISBN | Medium | ||
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Notes | LAMP; 600.079;ISE;CIC | Approved | no | ||
Call Number | Admin @ si @ MoW2015b | Serial | 2689 | ||
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Author | Dimosthenis Karatzas; Lluis Gomez; Anguelos Nicolaou; Suman Ghosh; Andrew Bagdanov; Masakazu Iwamura; J. Matas; L. Neumann; V. Ramaseshan; S. Lu ; Faisal Shafait; Seiichi Uchida; Ernest Valveny | ||||
Title | ICDAR 2015 Competition on Robust Reading | Type | Conference Article | ||
Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
Volume | Issue | Pages | 1156-1160 | ||
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Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.077; 600.084 | Approved | no | ||
Call Number | Admin @ si @ KGN2015 | Serial | 2690 | ||
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Author | Lluis Gomez; Dimosthenis Karatzas | ||||
Title | Object Proposals for Text Extraction in the Wild | Type | Conference Article | ||
Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
Volume | Issue | Pages | 206 - 210 | ||
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Abstract | Object Proposals is a recent computer vision technique receiving increasing interest from the research community. Its main objective is to generate a relatively small set of bounding box proposals that are most likely to contain objects of interest. The use of Object Proposals techniques in the scene text understanding field is innovative. Motivated by the success of powerful while expensive techniques to recognize words in a holistic way, Object Proposals techniques emerge as an alternative to the traditional text detectors. In this paper we study to what extent the existing generic Object Proposals methods may be useful for scene text understanding. Also, we propose a new Object Proposals algorithm that is specifically designed for text and compare it with other generic methods in the state of the art. Experiments show that our proposal is superior in its ability of producing good quality word proposals in an efficient way. The source code of our method is made publicly available | ||||
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Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.077; 600.084; 601.197 | Approved | no | ||
Call Number | Admin @ si @ GoK2015 | Serial | 2691 | ||
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Author | Anguelos Nicolaou; Andrew Bagdanov; Marcus Liwicki; Dimosthenis Karatzas | ||||
Title | Sparse Radial Sampling LBP for Writer Identification | Type | Conference Article | ||
Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
Volume | Issue | Pages | 716-720 | ||
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Abstract | In this paper we present the use of Sparse Radial Sampling Local Binary Patterns, a variant of Local Binary Patterns (LBP) for text-as-texture classification. By adapting and extending the standard LBP operator to the particularities of text we get a generic text-as-texture classification scheme and apply it to writer identification. In experiments on CVL and ICDAR 2013 datasets, the proposed feature-set demonstrates State-Of-the-Art (SOA) performance. Among the SOA, the proposed method is the only one that is based on dense extraction of a single local feature descriptor. This makes it fast and applicable at the earliest stages in a DIA pipeline without the need for segmentation, binarization, or extraction of multiple features. | ||||
Address | Nancy; France; August 2015 | ||||
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Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ NBL2015 | Serial | 2692 | ||
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Author | Suman Ghosh; Lluis Gomez; Dimosthenis Karatzas; Ernest Valveny | ||||
Title | Efficient indexing for Query By String text retrieval | Type | Conference Article | ||
Year | 2015 | Publication | 6th IAPR International Workshop on Camera Based Document Analysis and Recognition CBDAR2015 | Abbreviated Journal | |
Volume | Issue | Pages | 1236 - 1240 | ||
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Abstract | This paper deals with Query By String word spotting in scene images. A hierarchical text segmentation algorithm based on text specific selective search is used to find text regions. These regions are indexed per character n-grams present in the text region. An attribute representation based on Pyramidal Histogram of Characters (PHOC) is used to compare text regions with the query text. For generation of the index a similar attribute space based Pyramidal Histogram of character n-grams is used. These attribute models are learned using linear SVMs over the Fisher Vector [1] representation of the images along with the PHOC labels of the corresponding strings. | ||||
Address | Nancy; France; August 2015 | ||||
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Area | Expedition | Conference | CBDAR | ||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ GGK2015 | Serial | 2693 | ||
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Author | J.Kuhn; A.Nussbaumer; J.Pirker; Dimosthenis Karatzas; A. Pagani; O.Conlan; M.Memmel; C.M.Steiner; C.Gutl; D.Albert; Andreas Dengel | ||||
Title | Advancing Physics Learning Through Traversing a Multi-Modal Experimentation Space | Type | Conference Article | ||
Year | 2015 | Publication | Workshop Proceedings on the 11th International Conference on Intelligent Environments | Abbreviated Journal | |
Volume | 19 | Issue | Pages | 373-380 | |
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Abstract | Translating conceptual knowledge into real world experiences presents a significant educational challenge. This position paper presents an approach that supports learners in moving seamlessly between conceptual learning and their application in the real world by bringing physical and virtual experiments into everyday settings. Learners are empowered in conducting these situated experiments in a variety of physical settings by leveraging state of the art mobile, augmented reality, and virtual reality technology. A blend of mobile-based multi-sensory physical experiments, augmented reality and enabling virtual environments can allow learners to bridge their conceptual learning with tangible experiences in a completely novel manner. This approach focuses on the learner by applying self-regulated personalised learning techniques, underpinned by innovative pedagogical approaches and adaptation techniques, to ensure that the needs and preferences of each learner are catered for individually. | ||||
Address | Praga; Chzech Republic; July 2015 | ||||
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Area | Expedition | Conference | IE | ||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ KNP2015 | Serial | 2694 | ||
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Author | Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva | ||||
Title | Towards social interaction detection in egocentric photo-streams | Type | Conference Article | ||
Year | 2015 | Publication | Proceedings of SPIE, 8th International Conference on Machine Vision , ICMV 2015 | Abbreviated Journal | |
Volume | 9875 | Issue | Pages | ||
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Abstract | Detecting social interaction in videos relying solely on visual cues is a valuable task that is receiving increasing attention in recent years. In this work, we address this problem in the challenging domain of egocentric photo-streams captured by a low temporal resolution wearable camera (2fpm). The major difficulties to be handled in this context are the sparsity of observations as well as unpredictability of camera motion and attention orientation due to the fact that the camera is worn as part of clothing. Our method consists of four steps: multi-faces localization and tracking, 3D localization, pose estimation and analysis of f-formations. By estimating pair-to-pair interaction probabilities over the sequence, our method states the presence or absence of interaction with the camera wearer and specifies which people are more involved in the interaction. We tested our method over a dataset of 18.000 images and we show its reliability on our considered purpose. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only. | ||||
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Area | Expedition | Conference | ICMV | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ ADR2015a | Serial | 2702 | ||
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Author | Ivan Huerta; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez | ||||
Title | Chromatic shadow detection and tracking for moving foreground segmentation | Type | Journal Article | ||
Year | 2015 | Publication | Image and Vision Computing | Abbreviated Journal | IMAVIS |
Volume | 41 | Issue | Pages | 42-53 | |
Keywords | Detecting moving objects; Chromatic shadow detection; Temporal local gradient; Spatial and Temporal brightness and angle distortions; Shadow tracking | ||||
Abstract | Advanced segmentation techniques in the surveillance domain deal with shadows to avoid distortions when detecting moving objects. Most approaches for shadow detection are still typically restricted to penumbra shadows and cannot cope well with umbra shadows. Consequently, umbra shadow regions are usually detected as part of moving objects, thus aecting the performance of the nal detection. In this paper we address the detection of both penumbra and umbra shadow regions. First, a novel bottom-up approach is presented based on gradient and colour models, which successfully discriminates between chromatic moving cast shadow regions and those regions detected as moving objects. In essence, those regions corresponding to potential shadows are detected based on edge partitioning and colour statistics. Subsequently (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for each potential shadow region for detecting the umbra shadow regions. Our second contribution renes even further the segmentation results: a tracking-based top-down approach increases the performance of our bottom-up chromatic shadow detection algorithm by properly correcting non-detected shadows.
To do so, a combination of motion lters in a data association framework exploits the temporal consistency between objects and shadows to increase the shadow detection rate. Experimental results exceed current state-of-the- art in shadow accuracy for multiple well-known surveillance image databases which contain dierent shadowed materials and illumination conditions. |
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Notes | ISE; 600.078; 600.063 | Approved | no | ||
Call Number | Admin @ si @ HHM2015 | Serial | 2703 | ||
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Author | Sergio Escalera; Junior Fabian; Pablo Pardo; Xavier Baro; Jordi Gonzalez; Hugo Jair Escalante; Marc Oliu; Dusan Misevic; Ulrich Steiner; Isabelle Guyon | ||||
Title | ChaLearn Looking at People 2015: Apparent Age and Cultural Event Recognition Datasets and Results | Type | Conference Article | ||
Year | 2015 | Publication | 16th IEEE International Conference on Computer Vision Workshops | Abbreviated Journal | |
Volume | Issue | Pages | 243 - 251 | ||
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Abstract | Following previous series on Looking at People (LAP) competitions [14, 13, 11, 12, 2], in 2015 ChaLearn ran two new competitions within the field of Looking at People: (1) age estimation, and (2) cultural event recognition, both in
still images. We developed a crowd-sourcing application to collect and label data about the apparent age of people (as opposed to the real age). In terms of cultural event recognition, one hundred categories had to be recognized. These tasks involved scene understanding and human body analysis. This paper summarizes both challenges and data, as well as the results achieved by the participants of the competition. |
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Address | Santiago de Chile; December 2015 | ||||
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Area | Expedition | Conference | ICCVW | ||
Notes | ISE; 600.063; 600.078;MV;OR | Approved | no | ||
Call Number | Admin @ si @ EFP2015 | Serial | 2704 | ||
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Author | Josep M. Gonfaus; Marco Pedersoli; Jordi Gonzalez; Andrea Vedaldi; Xavier Roca | ||||
Title | Factorized appearances for object detection | Type | Journal Article | ||
Year | 2015 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU |
Volume | 138 | Issue | Pages | 92–101 | |
Keywords | Object recognition; Deformable part models; Learning and sharing parts; Discovering discriminative parts | ||||
Abstract | Deformable object models capture variations in an object’s appearance that can be represented as image deformations. Other effects such as out-of-plane rotations, three-dimensional articulations, and self-occlusions are often captured by considering mixture of deformable models, one per object aspect. A more scalable approach is representing instead the variations at the level of the object parts, applying the concept of a mixture locally. Combining a few part variations can in fact cheaply generate a large number of global appearances.
A limited version of this idea was proposed by Yang and Ramanan [1], for human pose dectection. In this paper we apply it to the task of generic object category detection and extend it in several ways. First, we propose a model for the relationship between part appearances more general than the tree of Yang and Ramanan [1], which is more suitable for generic categories. Second, we treat part locations as well as their appearance as latent variables so that training does not need part annotations but only the object bounding boxes. Third, we modify the weakly-supervised learning of Felzenszwalb et al. and Girshick et al. [2], [3] to handle a significantly more complex latent structure. Our model is evaluated on standard object detection benchmarks and is found to improve over existing approaches, yielding state-of-the-art results for several object categories. |
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Notes | ISE; 600.063; 600.078 | Approved | no | ||
Call Number | Admin @ si @ GPG2015 | Serial | 2705 | ||
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