toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links (up)
Author Alicia Fornes; Xavier Otazu; Josep Llados edit   pdf
doi  openurl
  Title Show through cancellation and image enhancement by multiresolution contrast processing Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 200-204  
  Keywords  
  Abstract Historical documents suffer from different types of degradation and noise such as background variation, uneven illumination or dark spots. In case of double-sided documents, another common problem is that the back side of the document usually interferes with the front side because of the transparency of the document or ink bleeding. This effect is called the show through phenomenon. Many methods are developed to solve these problems, and in the case of show-through, by scanning and matching both the front and back sides of the document. In contrast, our approach is designed to use only one side of the scanned document. We hypothesize that show-trough are low contrast components, while foreground components are high contrast ones. A Multiresolution Contrast (MC) decomposition is presented in order to estimate the contrast of features at different spatial scales. We cancel the show-through phenomenon by thresholding these low contrast components. This decomposition is also able to enhance the image removing shadowed areas by weighting spatial scales. Results show that the enhanced images improve the readability of the documents, allowing scholars both to recover unreadable words and to solve ambiguities.  
  Address Washington; USA; August 2013  
  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 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 602.006; 600.045; 600.061; 600.052;CIC Approved no  
  Call Number Admin @ si @ FOL2013 Serial 2241  
Permanent link to this record
 

 
Author Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier edit   pdf
doi  openurl
  Title An active contour model for speech balloon detection in comics Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1240-1244  
  Keywords  
  Abstract Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent comic book understanding would enable a variety of new applications, including content-based retrieval and content retargeting. Document understanding in this domain is challenging as comics are semi-structured documents, combining semantically important graphical and textual parts. Few studies have been done in this direction. In this work we detail a novel approach for closed and non-closed speech balloon localization in scanned comic book pages, an essential step towards a fully automatic comic book understanding. The approach is compared with existing methods for closed balloon localization found in the literature and results are presented.  
  Address washington; USA; August 2013  
  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 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; CIC; 600.056 Approved no  
  Call Number Admin @ si @ RKW2013a Serial 2260  
Permanent link to this record
 

 
Author Bojana Gajic; Ariel Amato; Ramon Baldrich; Joost Van de Weijer; Carlo Gatta edit   pdf
doi  openurl
  Title Area Under the ROC Curve Maximization for Metric Learning Type Conference Article
  Year 2022 Publication CVPR 2022 Workshop on Efficien Deep Learning for Computer Vision (ECV 2022, 5th Edition) Abbreviated Journal  
  Volume Issue Pages  
  Keywords Training; Computer vision; Conferences; Area measurement; Benchmark testing; Pattern recognition  
  Abstract Most popular metric learning losses have no direct relation with the evaluation metrics that are subsequently applied to evaluate their performance. We hypothesize that training a metric learning model by maximizing the area under the ROC curve (which is a typical performance measure of recognition systems) can induce an implicit ranking suitable for retrieval problems. This hypothesis is supported by previous work that proved that a curve dominates in ROC space if and only if it dominates in Precision-Recall space. To test this hypothesis, we design and maximize an approximated, derivable relaxation of the area under the ROC curve. The proposed AUC loss achieves state-of-the-art results on two large scale retrieval benchmark datasets (Stanford Online Products and DeepFashion In-Shop). Moreover, the AUC loss achieves comparable performance to more complex, domain specific, state-of-the-art methods for vehicle re-identification.  
  Address New Orleans, USA; 20 June 2022  
  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 CVPRW  
  Notes CIC; LAMP; Approved no  
  Call Number Admin @ si @ GAB2022 Serial 3700  
Permanent link to this record
 

 
Author Bojana Gajic; Ramon Baldrich edit  doi
openurl 
  Title Cross-domain fashion image retrieval Type Conference Article
  Year 2018 Publication CVPR 2018 Workshop on Women in Computer Vision (WiCV 2018, 4th Edition) Abbreviated Journal  
  Volume Issue Pages 19500-19502  
  Keywords  
  Abstract Cross domain image retrieval is a challenging task that implies matching images from one domain to their pairs from another domain. In this paper we focus on fashion image retrieval, which involves matching an image of a fashion item taken by users, to the images of the same item taken in controlled condition, usually by professional photographer. When facing this problem, we have different products
in train and test time, and we use triplet loss to train the network. We stress the importance of proper training of simple architecture, as well as adapting general models to the specific task.
 
  Address Salt Lake City, USA; 22 June 2018  
  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 CVPRW  
  Notes CIC; 600.087 Approved no  
  Call Number Admin @ si @ Serial 3709  
Permanent link to this record
 

 
Author Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell; Dimitris Samaras edit   pdf
doi  openurl
  Title The Photometry of Intrinsic Images Type Conference Article
  Year 2014 Publication 27th IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 1494-1501  
  Keywords  
  Abstract Intrinsic characterization of scenes is often the best way to overcome the illumination variability artifacts that complicate most computer vision problems, from 3D reconstruction to object or material recognition. This paper examines the deficiency of existing intrinsic image models to accurately account for the effects of illuminant color and sensor characteristics in the estimation of intrinsic images and presents a generic framework which incorporates insights from color constancy research to the intrinsic image decomposition problem. The proposed mathematical formulation includes information about the color of the illuminant and the effects of the camera sensors, both of which modify the observed color of the reflectance of the objects in the scene during the acquisition process. By modeling these effects, we get a “truly intrinsic” reflectance image, which we call absolute reflectance, which is invariant to changes of illuminant or camera sensors. This model allows us to represent a wide range of intrinsic image decompositions depending on the specific assumptions on the geometric properties of the scene configuration and the spectral properties of the light source and the acquisition system, thus unifying previous models in a single general framework. We demonstrate that even partial information about sensors improves significantly the estimated reflectance images, thus making our method applicable for a wide range of sensors. We validate our general intrinsic image framework experimentally with both synthetic data and natural images.  
  Address Columbus; Ohio; USA; June 2014  
  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 CVPR  
  Notes CIC; 600.052; 600.051; 600.074 Approved no  
  Call Number Admin @ si @ SPB2014 Serial 2506  
Permanent link to this record
 

 
Author M. Danelljan; Fahad Shahbaz Khan; Michael Felsberg; Joost Van de Weijer edit   pdf
doi  openurl
  Title Adaptive color attributes for real-time visual tracking Type Conference Article
  Year 2014 Publication 27th IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 1090 - 1097  
  Keywords  
  Abstract Visual tracking is a challenging problem in computer vision. Most state-of-the-art visual trackers either rely on luminance information or use simple color representations for image description. Contrary to visual tracking, for object
recognition and detection, sophisticated color features when combined with luminance have shown to provide excellent performance. Due to the complexity of the tracking problem, the desired color feature should be computationally
efficient, and possess a certain amount of photometric invariance while maintaining high discriminative power.
This paper investigates the contribution of color in a tracking-by-detection framework. Our results suggest that color attributes provides superior performance for visual tracking. We further propose an adaptive low-dimensional
variant of color attributes. Both quantitative and attributebased evaluations are performed on 41 challenging benchmark color sequences. The proposed approach improves the baseline intensity-based tracker by 24% in median distance precision. Furthermore, we show that our approach outperforms
state-of-the-art tracking methods while running at more than 100 frames per second.
 
  Address Nottingham; UK; September 2014  
  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 CVPR  
  Notes CIC; LAMP; 600.074; 600.079 Approved no  
  Call Number Admin @ si @ DKF2014 Serial 2509  
Permanent link to this record
 

 
Author Rahat Khan; Joost Van de Weijer; Fahad Shahbaz Khan; Damien Muselet; christophe Ducottet; Cecile Barat edit   pdf
doi  openurl
  Title Discriminative Color Descriptors Type Conference Article
  Year 2013 Publication IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 2866 - 2873  
  Keywords  
  Abstract Color description is a challenging task because of large variations in RGB values which occur due to scene accidental events, such as shadows, shading, specularities, illuminant color changes, and changes in viewing geometry. Traditionally, this challenge has been addressed by capturing the variations in physics-based models, and deriving invariants for the undesired variations. The drawback of this approach is that sets of distinguishable colors in the original color space are mapped to the same value in the photometric invariant space. This results in a drop of discriminative power of the color description. In this paper we take an information theoretic approach to color description. We cluster color values together based on their discriminative power in a classification problem. The clustering has the explicit objective to minimize the drop of mutual information of the final representation. We show that such a color description automatically learns a certain degree of photometric invariance. We also show that a universal color representation, which is based on other data sets than the one at hand, can obtain competing performance. Experiments show that the proposed descriptor outperforms existing photometric invariants. Furthermore, we show that combined with shape description these color descriptors obtain excellent results on four challenging datasets, namely, PASCAL VOC 2007, Flowers-102, Stanford dogs-120 and Birds-200.  
  Address Portland; Oregon; June 2013  
  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 1063-6919 ISBN Medium  
  Area Expedition Conference CVPR  
  Notes CIC; 600.048 Approved no  
  Call Number Admin @ si @ KWK2013a Serial 2262  
Permanent link to this record
 

 
Author Ernest Valveny; Robert Benavente; Agata Lapedriza; Miquel Ferrer; Jaume Garcia; Gemma Sanchez edit   pdf
doi  openurl
  Title Adaptation of a computer programming course to the EXHE requirements: evaluation five years later Type Miscellaneous
  Year 2012 Publication European Journal of Engineering Education Abbreviated Journal  
  Volume 37 Issue 3 Pages 243-254  
  Keywords  
  Abstract  
  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 DAG; CIC; OR; invisible;MV Approved no  
  Call Number Admin @ si @ VBL2012 Serial 2070  
Permanent link to this record
 

 
Author Judit Martinez; Eva Costa; P. Herreros; F. Javier Sanchez; Ramon Baldrich edit  doi
openurl 
  Title A Modular and Scalable Architecture for PC-Based Real-Time Vision Systems Type Journal Article
  Year 2003 Publication Real–Time Imaging, (IF: 0.512) Abbreviated Journal  
  Volume 9 Issue Pages 99-112  
  Keywords  
  Abstract  
  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 CIC Approved no  
  Call Number CAT @ cat @ MCH2003b Serial 394  
Permanent link to this record
 

 
Author Xavier Otazu; Oriol Pujol edit  doi
openurl 
  Title Wavelet based approach to cluster analysis. Application on low dimensional data sets Type Journal Article
  Year 2006 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 27 Issue 14 Pages 1590–1605  
  Keywords  
  Abstract  
  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 MILAB; CIC; HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ OtP2006 Serial 658  
Permanent link to this record
 

 
Author T. Widemann; Xavier Otazu edit  doi
openurl 
  Title Titanias radius and an upper limit on its atmosphere from the September 8, 2001 stellar occultation Type Journal Article
  Year 2009 Publication International Journal of Solar System Studies Abbreviated Journal  
  Volume 199 Issue 2 Pages 458–476  
  Keywords Occultations; Uranus, satellites; Satellites, shapes; Satellites, dynamics; Ices; Satellites, atmospheres  
  Abstract On September 8, 2001 around 2 h UT, the largest uranian moon, Titania, occulted Hipparcos star 106829 (alias SAO 164538, a V=7.2, K0 III star). This was the first-ever observed occultation by this satellite, a rare event as Titania subtends only 0.11 arcsec on the sky. The star's unusual brightness allowed many observers, both amateurs or professionals, to monitor this unique event, providing fifty-seven occultations chords over three continents, all reported here. Selecting the best 27 occultation chords, and assuming a circular limb, we derive Titania's radius: View the MathML source (1-σ error bar). This implies a density of View the MathML source using the value View the MathML source derived by Taylor [Taylor, D.B., 1998. Astron. Astrophys. 330, 362–374]. We do not detect any significant difference between equatorial and polar radii, in the limit View the MathML source, in agreement with Voyager limb image retrieval during the 1986 flyby. Titania's offset with respect to the DE405 + URA027 (based on GUST86 theory) ephemeris is derived: ΔαTcos(δT)=−108±13 mas and ΔδT=−62±7 mas (ICRF J2000.0 system). Most of this offset is attributable to a Uranus' barycentric offset with respect to DE405, that we estimate to be: View the MathML source and ΔδU=−85±25 mas at the moment of occultation. This offset is confirmed by another Titania stellar occultation observed on August 1st, 2003, which provides an offset of ΔαTcos(δT)=−127±20 mas and ΔδT=−97±13 mas for the satellite. The combined ingress and egress data do not show any significant hint for atmospheric refraction, allowing us to set surface pressure limits at the level of 10–20 nbar. More specifically, we find an upper limit of 13 nbar (1-σ level) at 70 K and 17 nbar at 80 K, for a putative isothermal CO2 atmosphere. We also provide an upper limit of 8 nbar for a possible CH4 atmosphere, and 22 nbar for pure N2, again at the 1-σ level. We finally constrain the stellar size using the time-resolved star disappearance and reappearance at ingress and egress. We find an angular diameter of 0.54±0.03 mas (corresponding to View the MathML source projected at Titania). With a distance of 170±25 parsecs, this corresponds to a radius of 9.8±0.2 solar radii for HIP 106829, typical of a K0 III giant.  
  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 0019-1035 ISBN Medium  
  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number CAT @ cat @ Wid2009 Serial 1052  
Permanent link to this record
 

 
Author Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Antonio Lopez; Michael Felsberg edit   pdf
doi  openurl
  Title Coloring Action Recognition in Still Images Type Journal Article
  Year 2013 Publication International Journal of Computer Vision Abbreviated Journal IJCV  
  Volume 105 Issue 3 Pages 205-221  
  Keywords  
  Abstract In this article we investigate the problem of human action recognition in static images. By action recognition we intend a class of problems which includes both action classification and action detection (i.e. simultaneous localization and classification). Bag-of-words image representations yield promising results for action classification, and deformable part models perform very well object detection. The representations for action recognition typically use only shape cues and ignore color information. Inspired by the recent success of color in image classification and object detection, we investigate the potential of color for action classification and detection in static images. We perform a comprehensive evaluation of color descriptors and fusion approaches for action recognition. Experiments were conducted on the three datasets most used for benchmarking action recognition in still images: Willow, PASCAL VOC 2010 and Stanford-40. Our experiments demonstrate that incorporating color information considerably improves recognition performance, and that a descriptor based on color names outperforms pure color descriptors. Our experiments demonstrate that late fusion of color and shape information outperforms other approaches on action recognition. Finally, we show that the different color–shape fusion approaches result in complementary information and combining them yields state-of-the-art performance for action classification.  
  Address  
  Corporate Author Thesis  
  Publisher Springer US Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0920-5691 ISBN Medium  
  Area Expedition Conference  
  Notes CIC; ADAS; 600.057; 600.048 Approved no  
  Call Number Admin @ si @ KRW2013 Serial 2285  
Permanent link to this record
 

 
Author Alicia Fornes; Josep Llados; Gemma Sanchez; Xavier Otazu; Horst Bunke edit  doi
openurl 
  Title A Combination of Features for Symbol-Independent Writer Identification in Old Music Scores Type Journal Article
  Year 2010 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 13 Issue 4 Pages 243-259  
  Keywords  
  Abstract The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper, we present an architecture for writer identification in old handwritten music scores. Even though an important amount of music compositions contain handwritten text, the aim of our work is to use only music notation to determine the author. The main contribution is therefore the use of features extracted from graphical alphabets. Our proposal consists in combining the identification results of two different approaches, based on line and textural features. The steps of the ensemble architecture are the following. First of all, the music sheet is preprocessed for removing the staff lines. Then, music lines and texture images are generated for computing line features and textural features. Finally, the classification results are combined for identifying the writer. The proposed method has been tested on a database of old music scores from the seventeenth to nineteenth centuries, achieving a recognition rate of about 92% with 20 writers.  
  Address  
  Corporate Author Thesis  
  Publisher Springer-Verlag Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; CAT;CIC Approved no  
  Call Number FLS2010b Serial 1319  
Permanent link to this record
 

 
Author Fahad Shahbaz Khan; Shida Beigpour; Joost Van de Weijer; Michael Felsberg edit  doi
openurl 
  Title Painting-91: A Large Scale Database for Computational Painting Categorization Type Journal Article
  Year 2014 Publication Machine Vision and Applications Abbreviated Journal MVAP  
  Volume 25 Issue 6 Pages 1385-1397  
  Keywords  
  Abstract Computer analysis of visual art, especially paintings, is an interesting cross-disciplinary research domain. Most of the research in the analysis of paintings involve medium to small range datasets with own specific settings. Interestingly, significant progress has been made in the field of object and scene recognition lately. A key factor in this success is the introduction and availability of benchmark datasets for evaluation. Surprisingly, such a benchmark setup is still missing in the area of computational painting categorization. In this work, we propose a novel large scale dataset of digital paintings. The dataset consists of paintings from 91 different painters. We further show three applications of our dataset namely: artist categorization, style classification and saliency detection. We investigate how local and global features popular in image classification perform for the tasks of artist and style categorization. For both categorization tasks, our experimental results suggest that combining multiple features significantly improves the final performance. We show that state-of-the-art computer vision methods can correctly classify 50 % of unseen paintings to its painter in a large dataset and correctly attribute its artistic style in over 60 % of the cases. Additionally, we explore the task of saliency detection on paintings and show experimental findings using state-of-the-art saliency estimation algorithms.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0932-8092 ISBN Medium  
  Area Expedition Conference  
  Notes CIC; LAMP; 600.074; 600.079 Approved no  
  Call Number Admin @ si @ KBW2014 Serial 2510  
Permanent link to this record
 

 
Author Fahad Shahbaz Khan; Joost Van de Weijer; Sadiq Ali; Michael Felsberg edit   pdf
doi  isbn
openurl 
  Title Evaluating the impact of color on texture recognition Type Conference Article
  Year 2013 Publication 15th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
  Volume 8047 Issue Pages 154-162  
  Keywords Color; Texture; image representation  
  Abstract State-of-the-art texture descriptors typically operate on grey scale images while ignoring color information. A common way to obtain a joint color-texture representation is to combine the two visual cues at the pixel level. However, such an approach provides sub-optimal results for texture categorisation task.
In this paper we investigate how to optimally exploit color information for texture recognition. We evaluate a variety of color descriptors, popular in image classification, for texture categorisation. In addition we analyze different fusion approaches to combine color and texture cues. Experiments are conducted on the challenging scenes and 10 class texture datasets. Our experiments clearly suggest that in all cases color names provide the best performance. Late fusion is the best strategy to combine color and texture. By selecting the best color descriptor with optimal fusion strategy provides a gain of 5% to 8% compared to texture alone on scenes and texture datasets.
 
  Address York; UK; August 2013  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-40260-9 Medium  
  Area Expedition Conference CAIP  
  Notes CIC; 600.048 Approved no  
  Call Number Admin @ si @ KWA2013 Serial 2263  
Permanent link to this record
 

 
Author Joost Van de Weijer; Fahad Shahbaz Khan edit   pdf
doi  isbn
openurl 
  Title Fusing Color and Shape for Bag-of-Words Based Object Recognition Type Conference Article
  Year 2013 Publication 4th Computational Color Imaging Workshop Abbreviated Journal  
  Volume 7786 Issue Pages 25-34  
  Keywords Object Recognition; color features; bag-of-words; image classification  
  Abstract In this article we provide an analysis of existing methods for the incorporation of color in bag-of-words based image representations. We propose a list of desired properties on which bases fusing methods can be compared. We discuss existing methods and indicate shortcomings of the two well-known fusing methods, namely early and late fusion. Several recent works have addressed these shortcomings by exploiting top-down information in the bag-of-words pipeline: color attention which is motivated from human vision, and Portmanteau vocabularies which are based on information theoretic compression of product vocabularies. We point out several remaining challenges in cue fusion and provide directions for future research.  
  Address Chiba; Japan; March 2013  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-36699-4 Medium  
  Area Expedition Conference CCIW  
  Notes CIC; 600.048 Approved no  
  Call Number Admin @ si @ WeK2013 Serial 2283  
Permanent link to this record
 

 
Author Abel Gonzalez-Garcia; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga edit   pdf
doi  isbn
openurl 
  Title Coloresia: An Interactive Colour Perception Device for the Visually Impaired Type Book Chapter
  Year 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal  
  Volume 48 Issue Pages 47-66  
  Keywords  
  Abstract 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.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium  
  Area Expedition Conference  
  Notes CIC; 600.052; 605.203 Approved no  
  Call Number Admin @ si @ GBP2013 Serial 2266  
Permanent link to this record
 

 
Author Joost Van de Weijer; Fahad Shahbaz Khan; Marc Masana edit   pdf
doi  isbn
openurl 
  Title Interactive Visual and Semantic Image Retrieval Type Book Chapter
  Year 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal  
  Volume 48 Issue Pages 31-35  
  Keywords  
  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.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Angel Sappa; Jordi Vitria  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium  
  Area Expedition Conference  
  Notes CIC; 605.203; 600.048 Approved no  
  Call Number Admin @ si @ WKC2013 Serial 2284  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: