toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links (down)
Author Aura Hernandez-Sabate; Debora Gil edit   pdf
url  doi
isbn  openurl
  Title The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries Type Book Chapter
  Year 2012 Publication Intravascular Ultrasound Abbreviated Journal  
  Volume Issue Pages 185-206  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Intech Place of Publication Editor Yasuhiro Honda  
  Language English Summary Language english Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-953-307-900-4 Medium  
  Area Expedition Conference  
  Notes IAM; ADAS Approved no  
  Call Number IAM @ iam @ HeG2012 Serial 1684  
Permanent link to this record
 

 
Author Jordi Roca; Maria Vanrell; C. Alejandro Parraga edit  url
isbn  openurl
  Title What is constant in colour constancy? Type Conference Article
  Year 2012 Publication 6th European Conference on Colour in Graphics, Imaging and Vision Abbreviated Journal  
  Volume Issue Pages 337-343  
  Keywords  
  Abstract Color constancy refers to the ability of the human visual system to stabilize
the color appearance of surfaces under an illuminant change. In this work we studied how the interrelations among nine colors are perceived under illuminant changes, particularly whether they remain stable across 10 different conditions (5 illuminants and 2 backgrounds). To do so we have used a paradigm that measures several colors under an immersive state of adaptation. From our measures we defined a perceptual structure descriptor that is up to 87% stable over all conditions, suggesting that color category features could be used to predict color constancy. This is in agreement with previous results on the stability of border categories [1,2] and with computational color constancy
algorithms [3] for estimating the scene illuminant.
 
  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 9781622767014 Medium  
  Area Expedition Conference CGIV  
  Notes CIC Approved no  
  Call Number RVP2012 Serial 2189  
Permanent link to this record
 

 
Author Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil edit   pdf
url  doi
isbn  openurl
  Title An illumination model of the trachea appearance in videobronchoscopy images Type Book Chapter
  Year 2012 Publication Image Analysis and Recognition Abbreviated Journal LNCS  
  Volume 7325 Issue Pages 313-320  
  Keywords Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation  
  Abstract Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution.
 
  Address Aveiro, Portugal  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-31297-7 Medium  
  Area 800 Expedition Conference ICIAR  
  Notes MV;IAM Approved no  
  Call Number IAM @ iam @ SSR2012 Serial 1898  
Permanent link to this record
 

 
Author Diego Cheda; Daniel Ponsa; Antonio Lopez edit   pdf
url  openurl
  Title Monocular Depth-based Background Estimation Type Conference Article
  Year 2012 Publication 7th International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume Issue Pages 323-328  
  Keywords  
  Abstract In this paper, we address the problem of reconstructing the background of a scene from a video sequence with occluding objects. The images are taken by hand-held cameras. Our method composes the background by selecting the appropriate pixels from previously aligned input images. To do that, we minimize a cost function that penalizes the deviations from the following assumptions: background represents objects whose distance to the camera is maximal, and background objects are stationary. Distance information is roughly obtained by a supervised learning approach that allows us to distinguish between close and distant image regions. Moving foreground objects are filtered out by using stationariness and motion boundary constancy measurements. The cost function is minimized by a graph cuts method. We demonstrate the applicability of our approach to recover an occlusion-free background in a set of sequences.  
  Address Roma  
  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 VISAPP  
  Notes ADAS Approved no  
  Call Number Admin @ si @ CPL2012b; ADAS @ adas @ cpl2012e Serial 2012  
Permanent link to this record
 

 
Author Albert Andaluz; Francesc Carreras; Cristina Santa Marta;Debora Gil edit   pdf
url  openurl
  Title Myocardial torsion estimation with Tagged-MRI in the OsiriX platform Type Conference Article
  Year 2012 Publication ISBI Workshop on Open Source Medical Image Analysis software Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Myocardial torsion (MT) plays a crucial role in the assessment of the functionality of the
left ventricle. For this purpose, the IAM group at the CVC has developed the Harmonic Phase Flow (HPF) plugin for the Osirix DICOM platform . We have validated its funcionalty on sequences acquired using different protocols and including healthy and pathological cases. Results show similar torsion trends for SPAMM acquisitions, with pathological cases introducing expected deviations from the ground truth. Finally, we provide the plugin free of charge at http://iam.cvc.uab.es
 
  Address Barcelona, Spain  
  Corporate Author Thesis  
  Publisher IEEE Place of Publication Editor Wiro Niessen (Erasmus MC) and Marc Modat (UCL)  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ISBI  
  Notes IAM Approved no  
  Call Number IAM @ iam @ ACS2012 Serial 1900  
Permanent link to this record
 

 
Author Naila Murray; Luca Marchesotti; Florent Perronnin edit   pdf
url  doi
isbn  openurl
  Title AVA: A Large-Scale Database for Aesthetic Visual Analysis Type Conference Article
  Year 2012 Publication 25th IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 2408-2415  
  Keywords  
  Abstract With the ever-expanding volume of visual content available, the ability to organize and navigate such content by aesthetic preference is becoming increasingly important. While still in its nascent stage, research into computational models of aesthetic preference already shows great potential. However, to advance research, realistic, diverse and challenging databases are needed. To this end, we introduce a new large-scale database for conducting Aesthetic Visual Analysis: AVA. It contains over 250,000 images along with a rich variety of meta-data including a large number of aesthetic scores for each image, semantic labels for over 60 categories as well as labels related to photographic style. We show the advantages of AVA with respect to existing databases in terms of scale, diversity, and heterogeneity of annotations. We then describe several key insights into aesthetic preference afforded by AVA. Finally, we demonstrate, through three applications, how the large scale of AVA can be leveraged to improve performance on existing preference tasks  
  Address Providence, Rhode Islan  
  Corporate Author Thesis  
  Publisher IEEE Xplore 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 978-1-4673-1226-4 Medium  
  Area Expedition Conference CVPR  
  Notes CIC Approved no  
  Call Number Admin @ si @ MMP2012a Serial 2025  
Permanent link to this record
 

 
Author Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco edit   pdf
url  openurl
  Title An investigation into plausible neural mechanisms related to the the CIWaM computational model for brightness induction Type Conference Article
  Year 2012 Publication 2nd Joint AVA / BMVA Meeting on Biological and Machine Vision Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. From a purely computational perspective, we built a low-level computational model (CIWaM) of early sensory processing based on multi-resolution wavelets with the aim of replicating brightness and colour (Otazu et al., 2010, Journal of Vision, 10(12):5) induction effects. Furthermore, we successfully used the CIWaM architecture to define a computational saliency model (Murray et al, 2011, CVPR, 433-440; Vanrell et al, submitted to AVA/BMVA'12). From a biological perspective, neurophysiological evidence suggests that perceived brightness information may be explicitly represented in V1. In this work we investigate possible neural mechanisms that offer a plausible explanation for such effects. To this end, we consider the model by Z.Li (Li, 1999, Network:Comput. Neural Syst., 10, 187-212) which is based on biological data and focuses on the part of V1 responsible for contextual influences, namely, layer 2-3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has proven to account for phenomena such as visual saliency, which share with brightness induction the relevant effect of contextual influences (the ones modelled by CIWaM). In the proposed model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition taken from the computational model (CIWaM).
This model successfully accounts for well known pyschophysical effects (among them: the White's and modied White's effects, the Todorovic, Chevreul, achromatic ring patterns, and grating induction effects) for static contexts and also for brigthness induction in dynamic contexts defined by modulating the luminance of surrounding areas. From a methodological point of view, we conclude that the results obtained by the computational model (CIWaM) are compatible with the ones obtained by the neurodynamical model proposed here.
 
  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 AV A  
  Notes CIC Approved no  
  Call Number Admin @ si @ OPD2012a Serial 2132  
Permanent link to this record
 

 
Author Graham D. Finlayson; Javier Vazquez; Sabine Süsstrunk; Maria Vanrell edit   pdf
url  doi
openurl 
  Title Spectral sharpening by spherical sampling Type Journal Article
  Year 2012 Publication Journal of the Optical Society of America A Abbreviated Journal JOSA A  
  Volume 29 Issue 7 Pages 1199-1210  
  Keywords  
  Abstract There are many works in color that assume illumination change can be modeled by multiplying sensor responses by individual scaling factors. The early research in this area is sometimes grouped under the heading “von Kries adaptation”: the scaling factors are applied to the cone responses. In more recent studies, both in psychophysics and in computational analysis, it has been proposed that scaling factors should be applied to linear combinations of the cones that have narrower support: they should be applied to the so-called “sharp sensors.” In this paper, we generalize the computational approach to spectral sharpening in three important ways. First, we introduce spherical sampling as a tool that allows us to enumerate in a principled way all linear combinations of the cones. This allows us to, second, find the optimal sharp sensors that minimize a variety of error measures including CIE Delta E (previous work on spectral sharpening minimized RMS) and color ratio stability. Lastly, we extend the spherical sampling paradigm to the multispectral case. Here the objective is to model the interaction of light and surface in terms of color signal spectra. Spherical sampling is shown to improve on the state of the art.  
  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 1084-7529 ISBN Medium  
  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number Admin @ si @ FVS2012 Serial 2000  
Permanent link to this record
 

 
Author Xavier Boix; Josep M. Gonfaus; Joost Van de Weijer; Andrew Bagdanov; Joan Serrat; Jordi Gonzalez edit   pdf
url  doi
openurl 
  Title Harmony Potentials: Fusing Global and Local Scale for Semantic Image Segmentation Type Journal Article
  Year 2012 Publication International Journal of Computer Vision Abbreviated Journal IJCV  
  Volume 96 Issue 1 Pages 83-102  
  Keywords  
  Abstract The Hierarchical Conditional Random Field(HCRF) model have been successfully applied to a number of image labeling problems, including image segmentation. However, existing HCRF models of image segmentation do not allow multiple classes to be assigned to a single region, which limits their ability to incorporate contextual information across multiple scales.
At higher scales in the image, this representation yields an oversimpli ed model since multiple classes can be reasonably expected to appear within large regions. This simpli ed model particularly limits the impact of information at higher scales. Since class-label information at these scales is usually more reliable than at lower, noisier scales, neglecting this information is undesirable. To
address these issues, we propose a new consistency potential for image labeling problems, which we call the harmony potential. It can encode any possible combi-
nation of labels, penalizing only unlikely combinations of classes. We also propose an e ective sampling strategy over this expanded label set that renders tractable the underlying optimization problem. Our approach obtains state-of-the-art results on two challenging, standard benchmark datasets for semantic image segmentation: PASCAL VOC 2010, and MSRC-21.
 
  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 0920-5691 ISBN Medium  
  Area Expedition Conference  
  Notes ISE;CIC;ADAS Approved no  
  Call Number Admin @ si @ BGW2012 Serial 1718  
Permanent link to this record
 

 
Author Naila Murray; Luca Marchesotti; Florent Perronnin edit   pdf
url  doi
isbn  openurl
  Title Learning to Rank Images using Semantic and Aesthetic Labels Type Conference Article
  Year 2012 Publication 23rd British Machine Vision Conference Abbreviated Journal  
  Volume Issue Pages 110.1-110.10  
  Keywords  
  Abstract Most works on image retrieval from text queries have addressed the problem of retrieving semantically relevant images. However, the ability to assess the aesthetic quality of an image is an increasingly important differentiating factor for search engines. In this work, given a semantic query, we are interested in retrieving images which are semantically relevant and score highly in terms of aesthetics/visual quality. We use large-margin classifiers and rankers to learn statistical models capable of ordering images based on the aesthetic and semantic information. In particular, we compare two families of approaches: while the first one attempts to learn a single ranker which takes into account both semantic and aesthetic information, the second one learns separate semantic and aesthetic models. We carry out a quantitative and qualitative evaluation on a recently-published large-scale dataset and we show that the second family of techniques significantly outperforms the first one.  
  Address Guildford, London  
  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 1-901725-46-4 Medium  
  Area Expedition Conference BMVC  
  Notes CIC Approved no  
  Call Number Admin @ si @ MMP2012b Serial 2027  
Permanent link to this record
 

 
Author Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil edit   pdf
url  doi
isbn  openurl
  Title Optimal Medial Surface Generation for Anatomical Volume Representations Type Book Chapter
  Year 2012 Publication Abdominal Imaging. Computational and Clinical Applications Abbreviated Journal LNCS  
  Volume 7601 Issue Pages 265-273  
  Keywords Medial surface representation; volume reconstruction  
  Abstract Medial representations are a widely used technique in abdominal organ shape representation and parametrization. Those methods require good medial manifolds as a starting point. Any medial
surface used to parametrize a volume should be simple enough to allow an easy manipulation and complete enough to allow an accurate reconstruction of the volume. Obtaining good quality medial
surfaces is still a problem with current iterative thinning methods. This forces the usage of generic, pre-calculated medial templates that are adapted to the final shape at the cost of a drop in volume reconstruction.
This paper describes an operator for generation of medial structures that generates clean and complete manifolds well suited for their further use in medial representations of abdominal organ volumes. While being simpler than thinning surfaces, experiments show its high performance in volume reconstruction and preservation of medial surface main branching topology.
 
  Address Nice, France  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Yoshida, Hiroyuki and Hawkes, David and Vannier, MichaelW.  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-33611-9 Medium  
  Area Expedition Conference STACOM  
  Notes IAM Approved no  
  Call Number IAM @ iam @ VGG2012b Serial 1988  
Permanent link to this record
 

 
Author Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell edit   pdf
url  doi
openurl 
  Title Modulating Shape Features by Color Attention for Object Recognition Type Journal Article
  Year 2012 Publication International Journal of Computer Vision Abbreviated Journal IJCV  
  Volume 98 Issue 1 Pages 49-64  
  Keywords  
  Abstract Bag-of-words based image representation is a successful approach for object recognition. Generally, the subsequent stages of the process: feature detection,feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, it was found that the combination of different image cues, such as shape and color, often obtains below expected results. This paper presents a novel method for recognizing object categories when using ultiple cues by separately processing the shape and color cues and combining them by modulating the shape features by category specific color attention. Color is used to compute bottom up and top-down attention maps. Subsequently, these color attention maps are used to modulate the weights of the shape features. In regions with higher attention shape features are given more weight than in regions with low attention. We compare our approach with existing methods that combine color and shape cues on five data sets containing varied importance of both cues, namely, Soccer (color predominance), Flower (color and hape parity), PASCAL VOC 2007 and 2009 (shape predominance) and Caltech-101 (color co-interference). The experiments clearly demonstrate that in all five data sets our proposed framework significantly outperforms existing methods for combining color and shape information.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Netherlands 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 Approved no  
  Call Number Admin @ si @ KWV2012 Serial 1864  
Permanent link to this record
 

 
Author German Ros; Jesus Martinez del Rincon; Gines Garcia-Mateos edit   pdf
url  isbn
openurl 
  Title Articulated Particle Filter for Hand Tracking Type Conference Article
  Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 3581 - 3585  
  Keywords  
  Abstract This paper proposes a new version of Particle Filter, called Articulated Particle Filter – ArPF -, which has been specifically designed for an efficient sampling of hierarchical spaces, generated by articulated objects. Our approach decomposes the articulated motion into layers for efficiency purposes, making use of a careful modeling of the diffusion noise along with its propagation through the articulations. This produces an increase of accuracy and prevent for divergences. The algorithm is tested on hand tracking due to its complex hierarchical articulated nature. With this purpose, a new dataset generation tool for quantitative evaluation is also presented in this paper.  
  Address Tsukuba Science City, Japan  
  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 1051-4651 ISBN 978-1-4673-2216-4 Medium  
  Area Expedition Conference ICPR  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RMG2012 Serial 2031  
Permanent link to this record
 

 
Author Jose Carlos Rubio; Joan Serrat; Antonio Lopez; N. Paragios edit   pdf
url  isbn
openurl 
  Title Image Contextual Representation and Matching through Hierarchies and Higher Order Graphs Type Conference Article
  Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 2664 - 2667  
  Keywords  
  Abstract We present a region matching algorithm which establishes correspondences between regions from two segmented images. An abstract graph-based representation conceals the image in a hierarchical graph, exploiting the scene properties at two levels. First, the similarity and spatial consistency of the image semantic objects is encoded in a graph of commute times. Second, the cluttered regions of the semantic objects are represented with a shape descriptor. Many-to-many matching of regions is specially challenging due to the instability of the segmentation under slight image changes, and we explicitly handle it through high order potentials. We demonstrate the matching approach applied to images of world famous buildings, captured under different conditions, showing the robustness of our method to large variations in illumination and viewpoint.  
  Address Tsukuba Science City, Japan  
  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 1051-4651 ISBN 978-1-4673-2216-4 Medium  
  Area Expedition Conference ICPR  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RSL2012a; Serial 2032  
Permanent link to this record
 

 
Author Francisco Cruz; Oriol Ramos Terrades edit   pdf
url  openurl
  Title Document segmentation using relative location features Type Conference Article
  Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 1562-1565  
  Keywords  
  Abstract In this paper we evaluate the use of Relative Location Features (RLF) on a historical document segmentation task, and compare the quality of the results obtained on structured and unstructured documents using RLF and not using them. We prove that using these features improve the final segmentation on documents with a strong structure, while their application on unstructured documents does not show significant improvement. Although this paper is not focused on segmenting unstructured documents, results obtained on a benchmark dataset are equal or even overcome previous results of similar works.  
  Address Tsukuba Science City, Japan  
  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 ICPR  
  Notes DAG Approved no  
  Call Number Admin @ si @ CrR2012 Serial 2051  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: