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Author Kaida Xiao; Sophie Wuerger; Chenyang Fu; Dimosthenis Karatzas edit  doi
openurl 
  Title Unique Hue Data for Colour Appearance Models. Part i: Loci of Unique Hues and Hue Uniformity Type Journal Article
  Year 2011 Publication Color Research & Application Abbreviated Journal CRA  
  Volume 36 Issue 5 Pages 316-323  
  Keywords unique hues; colour appearance models; CIECAM02; hue uniformity  
  Abstract Psychophysical experiments were conducted to assess unique hues on a CRT display for a large sample of colour-normal observers (n 1⁄4 185). These data were then used to evaluate the most commonly used colour appear- ance model, CIECAM02, by transforming the CIEXYZ tris- timulus values of the unique hues to the CIECAM02 colour appearance attributes, lightness, chroma and hue angle. We report two findings: (1) the hue angles derived from our unique hue data are inconsistent with the commonly used Natural Color System hues that are incorporated in the CIECAM02 model. We argue that our predicted unique hue angles (derived from our large dataset) provide a more reliable standard for colour management applications when the precise specification of these salient colours is im- portant. (2) We test hue uniformity for CIECAM02 in all four unique hues and show significant disagreements for all hues, except for unique red which seems to be invariant under lightness changes. Our dataset is useful to improve the CIECAM02 model as it provides reliable data for benchmarking.  
  Address  
  Corporate Author Thesis  
  Publisher Wiley Periodicals Inc Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes (up) DAG Approved no  
  Call Number Admin @ si @ XWF2011 Serial 1816  
Permanent link to this record
 

 
Author Albert Gordo; Florent Perronnin edit  doi
isbn  openurl
  Title Asymmetric Distances for Binary Embeddings Type Conference Article
  Year 2011 Publication IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 729 - 736  
  Keywords  
  Abstract In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes which binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances which are applicable to a wide variety of embedding techniques including Locality Sensitive Hashing (LSH), Locality Sensitive Binary Codes (LSBC), Spectral Hashing (SH) and Semi-Supervised Hashing (SSH). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques. We also propose a novel simple binary embedding technique – PCA Embedding (PCAE) – which is shown to yield competitive results with respect to more complex algorithms such as SH and SSH.  
  Address Providence, RI  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4577-0394-2 Medium  
  Area Expedition Conference CVPR  
  Notes (up) DAG Approved no  
  Call Number Admin @ si @ GoP2011; IAM @ iam @ GoP2011 Serial 1817  
Permanent link to this record
 

 
Author Chenyang Fu; Kaida Xiao; Dimosthenis Karatzas; Sophie Wuerger edit  doi
openurl 
  Title Investigation of Unique Hue Setting Changes with Ageing Type Journal Article
  Year 2011 Publication Chinese Optics Letters Abbreviated Journal COL  
  Volume 9 Issue 5 Pages 053301-1-5  
  Keywords  
  Abstract Clromatic sensitivity along the protan, deutan, and tritan lines and the loci of the unique hues (red, green, yellow, blue) for a very large sample (n = 185) of colour-normal observers ranging from 18 to 75 years of age are assessed. Visual judgments are obtained under normal viewing conditions using colour patches on self-luminous display under controlled adaptation conditions. Trivector discrimination thresholds show an increase as a function of age along the protan, deutan, and tritan axes, with the largest increase present along the tritan line, less pronounced shifts in unique hue settings are also observed. Based on the chromatic (protan, deutan, tritan) thresholds and using scaled cone signals, we predict the unique hue changes with ageing. A dependency on age for unique red and unique yellow for predicted hue angle is found. We conclude that the chromatic sensitivity deteriorates significantly with age, whereas the appearance of unique hues is much less affected, remaining almost constant despite the known changes in the ocular media.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes (up) DAG Approved no  
  Call Number Admin @ si @ XFW2011 Serial 1818  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny edit  openurl
  Title Descriptor-based Svm Wall Detector Type Conference Article
  Year 2011 Publication 9th International Workshop on Graphic Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Architectural floorplans 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 showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. In this paper we describe an evolution of this new approach in two directions: firstly we evaluate different features to obtain the description of every patch. Secondly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These modifications of the method have been tested for wall detection on two datasets of architectural floorplans with different notations and compared with the results obtained with the original approach.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes (up) DAG Approved no  
  Call Number Admin @ si @ HMS2011b Serial 1819  
Permanent link to this record
 

 
Author Partha Pratim Roy; Umapada Pal; Josep Llados edit  doi
openurl 
  Title Document Seal Detection Using Ght and Character Proximity Graphs Type Journal Article
  Year 2011 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 44 Issue 6 Pages 1282-1295  
  Keywords Seal recognition; Graphical symbol spotting; Generalized Hough transform; Multi-oriented character recognition  
  Abstract This paper deals with automatic detection of seal (stamp) from documents with cluttered background. Seal detection involves a difficult challenge due to its multi-oriented nature, arbitrary shape, overlapping of its part with signature, noise, etc. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors computed from recognition result of individual connected components (characters). Scale and rotation invariant features are used in a Support Vector Machine (SVM) classifier to recognize multi-scale and multi-oriented text characters. The concept of generalized Hough transform (GHT) is used to detect the seal and a voting scheme is designed for finding possible location of the seal in a document based on the spatial feature descriptor of neighboring component pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal in a document. Experiment is performed in an archive of historical documents of handwritten/printed English text. Experimental results show that the method is robust in locating seal instances of arbitrary shape and orientation in documents, and also efficient in indexing a collection of documents for retrieval purposes.  
  Address  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes (up) DAG Approved no  
  Call Number Admin @ si @ RPL2011 Serial 1820  
Permanent link to this record
 

 
Author Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados edit  openurl
  Title Classification of Administrative Document Images by Logo Identification Type Conference Article
  Year 2011 Publication In proceedings of 9th IAPR Workshop on Graphic Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  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.  
  Address Seoul, Corea  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes (up) DAG Approved no  
  Call Number Admin @ si @ RPK2011 Serial 1821  
Permanent link to this record
 

 
Author Kaida Xiao; Chenyang Fu; D.Mylonas; Dimosthenis Karatzas; S. Wuerger edit  url
doi  openurl
  Title Unique Hue Data for Colour Appearance Models. Part ii: Chromatic Adaptation Transform Type Journal Article
  Year 2013 Publication Color Research & Application Abbreviated Journal CRA  
  Volume 38 Issue 1 Pages 22-29  
  Keywords  
  Abstract Unique hue settings of 185 observers under three room-lighting conditions were used to evaluate the accuracy of full and mixed chromatic adaptation transform models of CIECAM02 in terms of unique hue reproduction. Perceptual hue shifts in CIECAM02 were evaluated for both models with no clear difference using the current Commission Internationale de l'Éclairage (CIE) recommendation for mixed chromatic adaptation ratio. Using our large dataset of unique hue data as a benchmark, an optimised parameter is proposed for chromatic adaptation under mixed illumination conditions that produces more accurate results in unique hue reproduction. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2013  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes (up) DAG Approved no  
  Call Number Admin @ si @ XFM2013 Serial 1822  
Permanent link to this record
 

 
Author Alicia Fornes; Volkmar Frinken; Andreas Fischer; Jon Almazan; G. Jackson; Horst Bunke edit  doi
isbn  openurl
  Title A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors Type Conference Article
  Year 2011 Publication Proceedings of the 2011 Workshop on Historical Document Imaging and Processing Abbreviated Journal  
  Volume Issue Pages 83-90  
  Keywords  
  Abstract The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition. In addition to the challenges given by modern handwritten data, a lack of training data as well as effects caused by the degradation of documents can be observed. In this scenario, keyword spotting arises to be a viable solution to make documents amenable for searching and browsing. For this task we propose the adaptation of shape descriptors used in symbol recognition. By treating each word image as a shape, it can be represented using the Blurred Shape Model and the De-formable Blurred Shape Model. Experiments on the George Washington database demonstrate that this approach is able to outperform the commonly used Dynamic Time Warping approach.  
  Address  
  Corporate Author Thesis  
  Publisher ACM Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4503-0916-5 Medium  
  Area Expedition Conference HIP  
  Notes (up) DAG Approved no  
  Call Number Admin @ si @ FFF2011a Serial 1823  
Permanent link to this record
 

 
Author Andreas Fischer; Volkmar Frinken; Alicia Fornes; Horst Bunke edit  doi
openurl 
  Title Transcription Alignment of Latin Manuscripts Using Hidden Markov Models Type Conference Article
  Year 2011 Publication Proceedings of the 2011 Workshop on Historical Document Imaging and Processing Abbreviated Journal  
  Volume Issue Pages 29-36  
  Keywords  
  Abstract Transcriptions of historical documents are a valuable source for extracting labeled handwriting images that can be used for training recognition systems. In this paper, we introduce the Saint Gall database that includes images as well as the transcription of a Latin manuscript from the 9th century written in Carolingian script. Although the available transcription is of high quality for a human reader, the spelling of the words is not accurate when compared with the handwriting image. Hence, the transcription poses several challenges for alignment regarding, e.g., line breaks, abbreviations, and capitalization. We propose an alignment system based on character Hidden Markov Models that can cope with these challenges and efficiently aligns complete document pages. On the Saint Gall database, we demonstrate that a considerable alignment accuracy can be achieved, even with weakly trained character models.  
  Address  
  Corporate Author Thesis  
  Publisher ACM Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference HIP  
  Notes (up) DAG Approved no  
  Call Number Admin @ si @ FFF2011b Serial 1824  
Permanent link to this record
 

 
Author Anjan Dutta; Josep Llados; Umapada Pal edit  doi
isbn  openurl
  Title Bag-of-GraphPaths Descriptors for Symbol Recognition and Spotting in Line Drawings Type Conference Article
  Year 2011 Publication In proceedings of 9th IAPR Workshop on Graphic Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Graphical symbol recognition and spotting recently have become an important research activity. In this work we present a descriptor for symbols, especially for line drawings. The descriptor is based on the graph representation of graphical objects. We construct graphs from the vectorized information of the binarized images, where the critical points detected by the vectorization algorithm are considered as nodes and the lines joining them are considered as edges. Graph paths between two nodes in a graph are the finite sequences of nodes following the order from the starting to the final node. The occurrences of different graph paths in a given graph is an important feature, as they capture the geometrical and structural attributes of a graph. So the graph representing a symbol can efficiently be represent by the occurrences of its different paths. Their occurrences in a symbol can be obtained in terms of a histogram counting the number of some fixed prototype paths, we call the histogram as the Bag-of-GraphPaths (BOGP). These BOGP histograms are used as a descriptor to measure the distance among the symbols in vector space. We use the descriptor for three applications, they are: (1) classification of the graphical symbols, (2) spotting of the architectural symbols on floorplans, (3) classification of the historical handwritten words.  
  Address Seoul, Korea  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-36823-3 Medium  
  Area Expedition Conference GREC  
  Notes (up) DAG Approved no  
  Call Number Admin @ si @ DLP2011c Serial 1825  
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