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Author |
Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez |
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Title |
Unsupervised and Notation-Independent Wall Segmentation in Floor Plans Using a Combination of Statistical and Structural Strategies |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
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Volume |
8746 |
Issue |
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Pages |
109-121 |
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Keywords |
Graphics recognition; Floor plan analysis; Object segmentation |
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Abstract |
In this paper we present a wall segmentation approach in floor plans that is able to work independently to the graphical notation, does not need any pre-annotated data for learning, and is able to segment multiple-shaped walls such as beams and curved-walls. This method results from the combination of the wall segmentation approaches [3, 5] presented recently by the authors. Firstly, potential straight wall segments are extracted in an unsupervised way similar to [3], but restricting even more the wall candidates considered in the original approach. Then, based on [5], these segments are used to learn the texture pattern of walls and spot the lost instances. The presented combination of both methods has been tested on 4 available datasets with different notations and compared qualitatively and quantitatively to the state-of-the-art applied on these collections. Additionally, some qualitative results on floor plans directly downloaded from the Internet are reported in the paper. The overall performance of the method demonstrates either its adaptability to different wall notations and shapes, and to document qualities and resolutions. |
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Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
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Notes |
DAG; ADAS; 600.076; 600.077 |
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no |
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Call Number |
Admin @ si @ HVS2014 |
Serial |
2535 |
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Author |
Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados |
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Title |
Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
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Volume |
8746 |
Issue |
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Pages |
135-146 |
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Keywords |
Graphics recognition; Graphics retrieval; Image classification |
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Abstract |
This paper proposes a runlength histogram signature as a perceptual descriptor of architectural plans in a retrieval scenario. The style of an architectural drawing is characterized by the perception of lines, shapes and texture. Such visual stimuli are the basis for defining semantic concepts as space properties, symmetry, density, etc. We propose runlength histograms extracted in vertical, horizontal and diagonal directions as a characterization of line and space properties in floorplans, so it can be roughly associated to a description of walls and room structure. A retrieval application illustrates the performance of the proposed approach, where given a plan as a query, similar ones are obtained from a database. A ground truth based on human observation has been constructed to validate the hypothesis. Additional retrieval results on sketched building’s facades are reported qualitatively in this paper. Its good description and its adaptability to two different sketch drawings despite its simplicity shows the interest of the proposed approach and opens a challenging research line in graphics recognition. |
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Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
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Notes |
DAG; ADAS; 600.045; 600.056; 600.061; 600.076; 600.077 |
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no |
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Call Number |
Admin @ si @ HFF2014 |
Serial |
2536 |
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Author |
Alicia Fornes; V.C.Kieu; M. Visani; N.Journet; Anjan Dutta |
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Title |
The ICDAR/GREC 2013 Music Scores Competition: Staff Removal |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
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Volume |
8746 |
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Pages |
207-220 |
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Keywords |
Competition; Graphics recognition; Music scores; Writer identification; Staff removal |
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Abstract |
The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated in both staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario concerning old and degraded music scores. For this purpose, we have generated a new set of semi-synthetic images using two degradation models that we previously introduced: local noise and 3D distortions. In this extended paper we provide an extended description of the dataset, degradation models, evaluation metrics, the participant’s methods and the obtained results that could not be presented at ICDAR and GREC proceedings due to page limitations. |
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Springer Berlin Heidelberg |
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Editor |
B.Lamiroy; J.-M. Ogier |
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ISSN |
0302-9743 |
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978-3-662-44853-3 |
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Notes |
DAG; 600.077; 600.061 |
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no |
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Call Number |
Admin @ si @ FKV2014 |
Serial |
2581 |
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Author |
Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados |
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Title |
Hierarchical Plausibility-Graphs for Symbol Spotting in Graphical Documents |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
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Volume |
8746 |
Issue |
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Pages |
25-37 |
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Abstract |
Graph representation of graphical documents often suffers from noise such as spurious nodes and edges, and their discontinuity. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance. But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result, the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset. |
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Springer Berlin Heidelberg |
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Editor |
Bart Lamiroy; Jean-Marc Ogier |
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ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
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Notes |
DAG; 600.045; 600.056; 600.061; 600.077 |
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no |
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Call Number |
Admin @ si @ BDJ2014 |
Serial |
2699 |
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Author |
Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
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Title |
Spotting Graphical Symbols in Camera-Acquired Documents in Real Time |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
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Volume |
8746 |
Issue |
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Pages |
3-10 |
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Abstract |
In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time. |
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Publisher |
Springer Berlin Heidelberg |
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Editor |
Bart Lamiroy; Jean-Marc Ogier |
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ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
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Notes |
DAG; 600.045; 600.055; 600.061; 600.077 |
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no |
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Call Number |
Admin @ si @ RKL2014 |
Serial |
2700 |
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Author |
Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados |
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Title |
Classification of Administrative Document Images by Logo Identification |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
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Volume |
8746 |
Issue |
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Pages |
49-58 |
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Keywords |
Administrative Document Classification; Logo Recognition; Logo Spotting |
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Abstract |
This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier’s graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents. |
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Springer Berlin Heidelberg |
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Editor |
Bart Lamiroy; Jean-Marc Ogier |
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ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
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Notes |
DAG; 600.056; 600.045; 605.203; 600.077 |
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no |
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Call Number |
Admin @ si @ RPK2014 |
Serial |
2701 |
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Author |
Ernest Valveny; Oriol Ramos Terrades; Joan Mas; Marçal Rusiñol |
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Title |
Interactive Document Retrieval and Classification. |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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Volume |
48 |
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Pages |
17-30 |
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Abstract |
In this chapter we describe a system for document retrieval and classification following the interactive-predictive framework. In particular, the system addresses two different scenarios of document analysis: document classification based on visual appearance and logo detection. These two classical problems of document analysis are formulated following the interactive-predictive model, taking the user interaction into account to make easier the process of annotating and labelling the documents. A system implementing this model in a real scenario is presented and analyzed. This system also takes advantage of active learning techniques to speed up the task of labelling the documents. |
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Springer Berlin Heidelberg |
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Editor |
Angel Sappa; Jordi Vitria |
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ISSN |
1868-4394 |
ISBN |
978-3-642-35931-6 |
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DAG |
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no |
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Call Number |
Admin @ si @ VRM2013 |
Serial |
2341 |
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Permanent link to this record |
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Author |
Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny |
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Title |
Notation-invariant patch-based wall detector in architectural floor plans |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Graphics Recognition. New Trends and Challenges |
Abbreviated Journal |
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Volume |
7423 |
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Pages |
79--88 |
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Abstract |
Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper. |
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Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-36823-3 |
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Notes |
DAG; 600.045; 600.056; 605.203 |
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no |
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Call Number |
Admin @ si @ HMS2013 |
Serial |
2322 |
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Author |
Joost Van de Weijer; Fahad Shahbaz Khan; Marc Masana |
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Title |
Interactive Visual and Semantic Image Retrieval |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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Volume |
48 |
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Pages |
31-35 |
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Abstract |
One direct consequence of recent advances in digital visual data generation and the direct availability of this information through the World-Wide Web, is a urgent demand for efficient image retrieval systems. The objective of image retrieval is to allow users to efficiently browse through this abundance of images. Due to the non-expert nature of the majority of the internet users, such systems should be user friendly, and therefore avoid complex user interfaces. In this chapter we investigate how high-level information provided by recently developed object recognition techniques can improve interactive image retrieval. Wel apply a bagof- word based image representation method to automatically classify images in a number of categories. These additional labels are then applied to improve the image retrieval system. Next to these high-level semantic labels, we also apply a low-level image description to describe the composition and color scheme of the scene. Both descriptions are incorporated in a user feedback image retrieval setting. The main objective is to show that automatic labeling of images with semantic labels can improve image retrieval results. |
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Springer Berlin Heidelberg |
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Angel Sappa; Jordi Vitria |
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1868-4394 |
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978-3-642-35931-6 |
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Notes |
CIC; 605.203; 600.048 |
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no |
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Call Number |
Admin @ si @ WKC2013 |
Serial |
2284 |
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Author |
Carles Fernandez; Jordi Gonzalez; Joao Manuel R. S. Taveres; Xavier Roca |
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Title |
Towards Ontological Cognitive System |
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Book Chapter |
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Year |
2013 |
Publication |
Topics in Medical Image Processing and Computational Vision |
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8 |
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87-99 |
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The increasing ubiquitousness of digital information in our daily lives has positioned video as a favored information vehicle, and given rise to an astonishing generation of social media and surveillance footage. This raises a series of technological demands for automatic video understanding and management, which together with the compromising attentional limitations of human operators, have motivated the research community to guide its steps towards a better attainment of such capabilities. As a result, current trends on cognitive vision promise to recognize complex events and self-adapt to different environments, while managing and integrating several types of knowledge. Future directions suggest to reinforce the multi-modal fusion of information sources and the communication with end-users. |
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Springer Netherlands |
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2212-9391 |
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978-94-007-0725-2 |
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ISE; 605.203; 302.018; 600.049 |
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Admin @ si @ FGT2013 |
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2287 |
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Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados |
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Title |
Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces |
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Book Chapter |
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Year |
2013 |
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Graph Embedding for Pattern Analysis |
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1-26 |
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Ability to recognize patterns is among the most crucial capabilities of human beings for their survival, which enables them to employ their sophisticated neural and cognitive systems [1], for processing complex audio, visual, smell, touch, and taste signals. Man is the most complex and the best existing system of pattern recognition. Without any explicit thinking, we continuously compare, classify, and identify huge amount of signal data everyday [2], starting from the time we get up in the morning till the last second we fall asleep. This includes recognizing the face of a friend in a crowd, a spoken word embedded in noise, the proper key to lock the door, smell of coffee, the voice of a favorite singer, the recognition of alphabetic characters, and millions of more tasks that we perform on regular basis. |
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Springer New York |
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978-1-4614-4456-5 |
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DAG |
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no |
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Admin @ si @ LRL2013b |
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2271 |
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Author |
Abel Gonzalez-Garcia; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga |
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Title |
Coloresia: An Interactive Colour Perception Device for the Visually Impaired |
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Book Chapter |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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48 |
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47-66 |
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A significative percentage of the human population suffer from impairments in their capacity to distinguish or even see colours. For them, everyday tasks like navigating through a train or metro network map becomes demanding. We present a novel technique for extracting colour information from everyday natural stimuli and presenting it to visually impaired users as pleasant, non-invasive sound. This technique was implemented inside a Personal Digital Assistant (PDA) portable device. In this implementation, colour information is extracted from the input image and categorised according to how human observers segment the colour space. This information is subsequently converted into sound and sent to the user via speakers or headphones. In the original implementation, it is possible for the user to send its feedback to reconfigure the system, however several features such as these were not implemented because the current technology is limited.We are confident that the full implementation will be possible in the near future as PDA technology improves. |
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Springer Berlin Heidelberg |
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1868-4394 |
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978-3-642-35931-6 |
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Notes |
CIC; 600.052; 605.203 |
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no |
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Admin @ si @ GBP2013 |
Serial |
2266 |
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Author |
Michal Drozdzal; Santiago Segui; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria |
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Title |
An Application for Efficient Error-Free Labeling of Medical Images |
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Book Chapter |
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Year |
2013 |
Publication |
Multimodal Interaction in Image and Video Applications |
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48 |
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1-16 |
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Abstract |
In this chapter we describe an application for efficient error-free labeling of medical images. In this scenario, the compilation of a complete training set for building a realistic model of a given class of samples is not an easy task, making the process tedious and time consuming. For this reason, there is a need for interactive labeling applications that minimize the effort of the user while providing error-free labeling. We propose a new algorithm that is based on data similarity in feature space. This method actively explores data in order to find the best label-aligned clustering and exploits it to reduce the labeler effort, that is measured by the number of “clicks. Moreover, error-free labeling is guaranteed by the fact that all data and their labels proposals are visually revised by en expert. |
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Springer Berlin Heidelberg |
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1868-4394 |
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978-3-642-35931-6 |
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MILAB; OR;MV |
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Admin @ si @ DSR2013 |
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2235 |
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Author |
Marc Castello; Jordi Gonzalez; Ariel Amato; Pau Baiget; Carles Fernandez; Josep M. Gonfaus; Ramon Mollineda; Marco Pedersoli; Nicolas Perez de la Blanca; Xavier Roca |
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Title |
Exploiting Multimodal Interaction Techniques for Video-Surveillance |
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2013 |
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Multimodal Interaction in Image and Video Applications Intelligent Systems Reference Library |
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48 |
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8 |
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135-151 |
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In this paper we present an example of a video surveillance application that exploits Multimodal Interactive (MI) technologies. The main objective of the so-called VID-Hum prototype was to develop a cognitive artificial system for both the detection and description of a particular set of human behaviours arising from real-world events. The main procedure of the prototype described in this chapter entails: (i) adaptation, since the system adapts itself to the most common behaviours (qualitative data) inferred from tracking (quantitative data) thus being able to recognize abnormal behaviors; (ii) feedback, since an advanced interface based on Natural Language understanding allows end-users the communicationwith the prototype by means of conceptual sentences; and (iii) multimodality, since a virtual avatar has been designed to describe what is happening in the scene, based on those textual interpretations generated by the prototype. Thus, the MI methodology has provided an adequate framework for all these cooperating processes. |
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Springer Berlin Heidelberg |
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1868-4394 |
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978-3-642-35931-6 |
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ISE; 605.203; 600.049 |
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CGA2013 |
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2222 |
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Author |
David Vazquez; Antonio Lopez; Daniel Ponsa; David Geronimo |
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Title |
Interactive Training of Human Detectors |
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Book Chapter |
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2013 |
Publication |
Multiodal Interaction in Image and Video Applications |
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48 |
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169-182 |
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Pedestrian Detection; Virtual World; AdaBoost; Domain Adaptation |
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Image based human detection remains as a challenging problem. Most promising detectors rely on classifiers trained with labelled samples. However, labelling is a manual labor intensive step. To overcome this problem we propose to collect images of pedestrians from a virtual city, i.e., with automatic labels, and train a pedestrian detector with them, which works fine when such virtual-world data are similar to testing one, i.e., real-world pedestrians in urban areas. When testing data is acquired in different conditions than training one, e.g., human detection in personal photo albums, dataset shift appears. In previous work, we cast this problem as one of domain adaptation and solve it with an active learning procedure. In this work, we focus on the same problem but evaluating a different set of faster to compute features, i.e., Haar, EOH and their combination. In particular, we train a classifier with virtual-world data, using such features and Real AdaBoost as learning machine. This classifier is applied to real-world training images. Then, a human oracle interactively corrects the wrong detections, i.e., few miss detections are manually annotated and some false ones are pointed out too. A low amount of manual annotation is fixed as restriction. Real- and virtual-world difficult samples are combined within what we call cool world and we retrain the classifier with this data. Our experiments show that this adapted classifier is equivalent to the one trained with only real-world data but requiring 90% less manual annotations. |
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Springer Heidelberg New York Dordrecht London |
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Springer Berlin Heidelberg |
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English |
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1868-4394 |
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978-3-642-35931-6 |
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Notes |
ADAS; 600.057; 600.054; 605.203 |
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VLP2013; ADAS @ adas @ vlp2013 |
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2193 |
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