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Author |
Jorge Bernal; Debora Gil; Carles Sanchez; F. Javier Sanchez |
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Title |
Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis |
Type |
Conference Article |
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Year |
2014 |
Publication |
1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy |
Abbreviated Journal |
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Volume |
8899 |
Issue |
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Pages |
1-10 |
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Keywords |
Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps |
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Abstract |
In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation. |
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Boston; USA; September 2014 |
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Springer International Publishing |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-319-13409-3 |
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CARE |
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Notes |
MV; IAM; 600.044; 600.047; 600.060; 600.075 |
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no |
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Call Number |
Admin @ si @ BGS2014b |
Serial |
2503 |
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Author |
Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu |
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Title |
Robust Head Gestures Recognition for Assistive Technology |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Pattern Recognition |
Abbreviated Journal |
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Volume |
8495 |
Issue |
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Pages |
152-161 |
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This paper presents a system capable of recognizing six head gestures: nodding, shaking, turning right, turning left, looking up, and looking down. The main difference of our system compared to other methods is that the Hidden Markov Models presented in this paper, are fully connected and consider all possible states in any given order, providing the following advantages to the system: (1) allows unconstrained movement of the head and (2) it can be easily integrated into a wearable device (e.g. glasses, neck-hung devices), in which case it can robustly recognize gestures in the presence of ego-motion. Experimental results show that this approach outperforms common methods that use restricted HMMs for each gesture. |
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Springer International Publishing |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-319-07490-0 |
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Notes |
LAMP; |
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no |
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Call Number |
Admin @ si @ TSR2014b |
Serial |
2505 |
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Author |
Francesco Brughi; Debora Gil; Llorenç Badiella; Eva Jove Casabella; Oriol Ramos Terrades |
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Title |
Exploring the impact of inter-query variability on the performance of retrieval systems |
Type |
Conference Article |
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Year |
2014 |
Publication |
11th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
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Volume |
8814 |
Issue |
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Pages |
413–420 |
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Abstract |
This paper introduces a framework for evaluating the performance of information retrieval systems. Current evaluation metrics provide an average score that does not consider performance variability across the query set. In this manner, conclusions lack of any statistical significance, yielding poor inference to cases outside the query set and possibly unfair comparisons. We propose to apply statistical methods in order to obtain a more informative measure for problems in which different query classes can be identified. In this context, we assess the performance variability on two levels: overall variability across the whole query set and specific query class-related variability. To this end, we estimate confidence bands for precision-recall curves, and we apply ANOVA in order to assess the significance of the performance across different query classes. |
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Algarve; Portugal; October 2014 |
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Springer International Publishing |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-319-11757-7 |
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ICIAR |
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Notes |
IAM; DAG; 600.060; 600.061; 600.077; 600.075 |
Approved |
no |
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Call Number |
Admin @ si @ BGB2014 |
Serial |
2559 |
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Permanent link to this record |
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Author |
Josep Llados; Marçal Rusiñol |
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Title |
Graphics Recognition Techniques |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
Abbreviated Journal |
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Volume |
D |
Issue |
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Pages |
489-521 |
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Keywords |
Dimension recognition; Graphics recognition; Graphic-rich documents; Polygonal approximation; Raster-to-vector conversion; Texture-based primitive extraction; Text-graphics separation |
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Abstract |
This chapter describes the most relevant approaches for the analysis of graphical documents. The graphics recognition pipeline can be splitted into three tasks. The low level or lexical task extracts the basic units composing the document. The syntactic level is focused on the structure, i.e., how graphical entities are constructed, and involves the location and classification of the symbols present in the document. The third level is a functional or semantic level, i.e., it models what the graphical symbols do and what they mean in the context where they appear. This chapter covers the lexical level, while the next two chapters are devoted to the syntactic and semantic level, respectively. The main problems reviewed in this chapter are raster-to-vector conversion (vectorization algorithms) and the separation of text and graphics components. The research and industrial communities have provided standard methods achieving reasonable performance levels. Hence, graphics recognition techniques can be considered to be in a mature state from a scientific point of view. Additionally this chapter provides insights on some related problems, namely, the extraction and recognition of dimensions in engineering drawings, and the recognition of hatched and tiled patterns. Both problems are usually associated, even integrated, in the vectorization process. |
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Springer London |
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Editor |
D. Doermann; K. Tombre |
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ISBN |
978-0-85729-858-4 |
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Notes |
DAG; 600.077 |
Approved |
no |
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Call Number |
Admin @ si @ LlR2014 |
Serial |
2380 |
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Permanent link to this record |
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Author |
Salvatore Tabbone; Oriol Ramos Terrades |
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Title |
An Overview of Symbol Recognition |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
Abbreviated Journal |
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Volume |
D |
Issue |
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Pages |
523-551 |
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Keywords |
Pattern recognition; Shape descriptors; Structural descriptors; Symbolrecognition; Symbol spotting |
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Abstract |
According to the Cambridge Dictionaries Online, a symbol is a sign, shape, or object that is used to represent something else. Symbol recognition is a subfield of general pattern recognition problems that focuses on identifying, detecting, and recognizing symbols in technical drawings, maps, or miscellaneous documents such as logos and musical scores. This chapter aims at providing the reader an overview of the different existing ways of describing and recognizing symbols and how the field has evolved to attain a certain degree of maturity. |
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Publisher |
Springer London |
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Editor |
D. Doermann; K. Tombre |
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ISBN |
978-0-85729-858-4 |
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Notes |
DAG; 600.077 |
Approved |
no |
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Call Number |
Admin @ si @ TaT2014 |
Serial |
2489 |
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Permanent link to this record |
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Author |
A.Kesidis; Dimosthenis Karatzas |
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Title |
Logo and Trademark Recognition |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
Abbreviated Journal |
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Volume |
D |
Issue |
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Pages |
591-646 |
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Keywords |
Logo recognition; Logo removal; Logo spotting; Trademark registration; Trademark retrieval systems |
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Abstract |
The importance of logos and trademarks in nowadays society is indisputable, variably seen under a positive light as a valuable service for consumers or a negative one as a catalyst of ever-increasing consumerism. This chapter discusses the technical approaches for enabling machines to work with logos, looking into the latest methodologies for logo detection, localization, representation, recognition, retrieval, and spotting in a variety of media. This analysis is presented in the context of three different applications covering the complete depth and breadth of state of the art techniques. These are trademark retrieval systems, logo recognition in document images, and logo detection and removal in images and videos. This chapter, due to the very nature of logos and trademarks, brings together various facets of document image analysis spanning graphical and textual content, while it links document image analysis to other computer vision domains, especially when it comes to the analysis of real-scene videos and images. |
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Publisher |
Springer London |
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Editor |
D. Doermann; K. Tombre |
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ISBN |
978-0-85729-858-4 |
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Notes |
DAG; 600.077 |
Approved |
no |
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Call Number |
Admin @ si @ KeK2014 |
Serial |
2425 |
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Permanent link to this record |
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Author |
Alicia Fornes; Gemma Sanchez |
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Title |
Analysis and Recognition of Music Scores |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Handbook of Document Image Processing and Recognition |
Abbreviated Journal |
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Volume |
E |
Issue |
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Pages |
749-774 |
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Abstract |
The analysis and recognition of music scores has attracted the interest of researchers for decades. Optical Music Recognition (OMR) is a classical research field of Document Image Analysis and Recognition (DIAR), whose aim is to extract information from music scores. Music scores contain both graphical and textual information, and for this reason, techniques are closely related to graphics recognition and text recognition. Since music scores use a particular diagrammatic notation that follow the rules of music theory, many approaches make use of context information to guide the recognition and solve ambiguities. This chapter overviews the main Optical Music Recognition (OMR) approaches. Firstly, the different methods are grouped according to the OMR stages, namely, staff removal, music symbol recognition, and syntactical analysis. Secondly, specific approaches for old and handwritten music scores are reviewed. Finally, online approaches and commercial systems are also commented. |
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Publisher |
Springer London |
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Editor |
D. Doermann; K. Tombre |
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ISBN |
978-0-85729-860-7 |
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Notes |
DAG; ADAS; 600.076; 600.077 |
Approved |
no |
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Call Number |
Admin @ si @ FoS2014 |
Serial |
2484 |
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Permanent link to this record |
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Author |
Svebor Karaman; Giuseppe Lisanti; Andrew Bagdanov; Alberto del Bimbo |
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Title |
From re-identification to identity inference: Labeling consistency by local similarity constraints |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Person Re-Identification |
Abbreviated Journal |
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Volume |
2 |
Issue |
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Pages |
287-307 |
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Keywords |
re-identification; Identity inference; Conditional random fields; Video surveillance |
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Abstract |
In this chapter, we introduce the problem of identity inference as a generalization of person re-identification. It is most appropriate to distinguish identity inference from re-identification in situations where a large number of observations must be identified without knowing a priori that groups of test images represent the same individual. The standard single- and multishot person re-identification common in the literature are special cases of our formulation. We present an approach to solving identity inference by modeling it as a labeling problem in a Conditional Random Field (CRF). The CRF model ensures that the final labeling gives similar labels to detections that are similar in feature space. Experimental results are given on the ETHZ, i-LIDS and CAVIAR datasets. Our approach yields state-of-the-art performance for multishot re-identification, and our results on the more general identity inference problem demonstrate that we are able to infer the identity of very many examples even with very few labeled images in the gallery. |
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Springer London |
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ISSN |
2191-6586 |
ISBN |
978-1-4471-6295-7 |
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Notes |
LAMP; 600.079 |
Approved |
no |
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Call Number |
Admin @ si @KLB2014b |
Serial |
2521 |
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Permanent link to this record |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
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Title |
Mathematical modeling of G protein-coupled receptor function: What can we learn from empirical and mechanistic models? |
Type |
Book Chapter |
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Year |
2014 |
Publication |
G Protein-Coupled Receptors – Modeling and Simulation Advances in Experimental Medicine and Biology |
Abbreviated Journal |
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Volume |
796 |
Issue |
3 |
Pages |
159-181 |
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Keywords |
β-arrestin; biased agonism; curve fitting; empirical modeling; evolutionary algorithm; functional selectivity; G protein; GPCR; Hill coefficient; intrinsic efficacy; inverse agonism; mathematical modeling; mechanistic modeling; operational model; parameter optimization; receptor dimer; receptor oligomerization; receptor constitutive activity; signal transduction; two-state model |
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Abstract |
Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists. |
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Springer Netherlands |
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ISSN |
0065-2598 |
ISBN |
978-94-007-7422-3 |
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Notes |
IAM; 600.075 |
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no |
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Call Number |
IAM @ iam @ RGG2014 |
Serial |
2197 |
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Author |
Palaiahnakote Shivakumara; Anjan Dutta; Chew Lim Tan; Umapada Pal |
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Title |
Multi-oriented scene text detection in video based on wavelet and angle projection boundary growing |
Type |
Journal Article |
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Year |
2014 |
Publication |
Multimedia Tools and Applications |
Abbreviated Journal |
MTAP |
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Volume |
72 |
Issue |
1 |
Pages |
515-539 |
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Abstract |
In this paper, we address two complex issues: 1) Text frame classification and 2) Multi-oriented text detection in video text frame. We first divide a video frame into 16 blocks and propose a combination of wavelet and median-moments with k-means clustering at the block level to identify probable text blocks. For each probable text block, the method applies the same combination of feature with k-means clustering over a sliding window running through the blocks to identify potential text candidates. We introduce a new idea of symmetry on text candidates in each block based on the observation that pixel distribution in text exhibits a symmetric pattern. The method integrates all blocks containing text candidates in the frame and then all text candidates are mapped on to a Sobel edge map of the original frame to obtain text representatives. To tackle the multi-orientation problem, we present a new method called Angle Projection Boundary Growing (APBG) which is an iterative algorithm and works based on a nearest neighbor concept. APBG is then applied on the text representatives to fix the bounding box for multi-oriented text lines in the video frame. Directional information is used to eliminate false positives. Experimental results on a variety of datasets such as non-horizontal, horizontal, publicly available data (Hua’s data) and ICDAR-03 competition data (camera images) show that the proposed method outperforms existing methods proposed for video and the state of the art methods for scene text as well. |
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Springer US |
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ISSN |
1380-7501 |
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Notes |
DAG; 600.077 |
Approved |
no |
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Call Number |
Admin @ si @ SDT2014 |
Serial |
2357 |
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Permanent link to this record |
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Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
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Title |
Rendering ground truth data sets to detect shadows cast by static objects in outdoors |
Type |
Journal Article |
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Year |
2014 |
Publication |
Multimedia Tools and Applications |
Abbreviated Journal |
MTAP |
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Volume |
70 |
Issue |
1 |
Pages |
557-571 |
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Keywords |
Synthetic ground truth data set; Sun position; Shadow detection; Static objects shadow detection |
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Abstract |
In our work, we are particularly interested in studying the shadows cast by static objects in outdoor environments, during daytime. To assess the accuracy of a shadow detection algorithm, we need ground truth information. The collection of such information is a very tedious task because it is a process that requires manual annotation. To overcome this severe limitation, we propose in this paper a methodology to automatically render ground truth using a virtual environment. To increase the degree of realism and usefulness of the simulated environment, we incorporate in the scenario the precise longitude, latitude and elevation of the actual location of the object, as well as the sun’s position for a given time and day. To evaluate our method, we consider a qualitative and a quantitative comparison. In the quantitative one, we analyze the shadow cast by a real object in a particular geographical location and its corresponding rendered model. To evaluate qualitatively the methodology, we use some ground truth images obtained both manually and automatically. |
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Springer US |
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1380-7501 |
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Notes |
LAMP; |
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no |
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Call Number |
Admin @ si @ ISR2014 |
Serial |
2229 |
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Permanent link to this record |
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Author |
Antonio Clavelli; Dimosthenis Karatzas; Josep Llados; Mario Ferraro; Giuseppe Boccignone |
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Title |
Modelling task-dependent eye guidance to objects in pictures |
Type |
Journal Article |
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Year |
2014 |
Publication |
Cognitive Computation |
Abbreviated Journal |
CoCom |
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Volume |
6 |
Issue |
3 |
Pages |
558-584 |
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Keywords |
Visual attention; Gaze guidance; Value; Payoff; Stochastic fixation prediction |
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Abstract |
5Y Impact Factor: 1.14 / 3rd (Computer Science, Artificial Intelligence)
We introduce a model of attentional eye guidance based on the rationale that the deployment of gaze is to be considered in the context of a general action-perception loop relying on two strictly intertwined processes: sensory processing, depending on current gaze position, identifies sources of information that are most valuable under the given task; motor processing links such information with the oculomotor act by sampling the next gaze position and thus performing the gaze shift. In such a framework, the choice of where to look next is task-dependent and oriented to classes of objects embedded within pictures of complex scenes. The dependence on task is taken into account by exploiting the value and the payoff of gazing at certain image patches or proto-objects that provide a sparse representation of the scene objects. The different levels of the action-perception loop are represented in probabilistic form and eventually give rise to a stochastic process that generates the gaze sequence. This way the model also accounts for statistical properties of gaze shifts such as individual scan path variability. Results of the simulations are compared either with experimental data derived from publicly available datasets and from our own experiments. |
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Springer US |
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1866-9956 |
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Notes |
DAG; 600.056; 600.045; 605.203; 601.212; 600.077 |
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no |
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Call Number |
Admin @ si @ CKL2014 |
Serial |
2419 |
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Permanent link to this record |
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Author |
C. Alejandro Parraga |
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Title |
Color Vision, Computational Methods for |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Encyclopedia of Computational Neuroscience |
Abbreviated Journal |
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Volume |
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Pages |
1-11 |
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Keywords |
Color computational vision; Computational neuroscience of color |
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Abstract |
The study of color vision has been aided by a whole battery of computational methods that attempt to describe the mechanisms that lead to our perception of colors in terms of the information-processing properties of the visual system. Their scope is highly interdisciplinary, linking apparently dissimilar disciplines such as mathematics, physics, computer science, neuroscience, cognitive science, and psychology. Since the sensation of color is a feature of our brains, computational approaches usually include biological features of neural systems in their descriptions, from retinal light-receptor interaction to subcortical color opponency, cortical signal decoding, and color categorization. They produce hypotheses that are usually tested by behavioral or psychophysical experiments. |
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Corporate Author |
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Thesis |
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Publisher |
Springer-Verlag Berlin Heidelberg |
Place of Publication |
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Editor |
Dieter Jaeger; Ranu Jung |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
978-1-4614-7320-6 |
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Expedition |
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Conference |
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Notes |
CIC; 600.074 |
Approved |
no |
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Call Number |
Admin @ si @ Par2014 |
Serial |
2512 |
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Permanent link to this record |