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Author Josep M. Gonfaus; Theo Gevers; Arjan Gijsenij; Xavier Roca; Jordi Gonzalez edit   pdf
url  isbn
openurl 
  Title Edge Classification using Photo-Geo metric features Type Conference Article
  Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue (up) Pages 1497 - 1500  
  Keywords  
  Abstract Edges are caused by several imaging cues such as shadow, material and illumination transitions. Classification methods have been proposed which are solely based on photometric information, ignoring geometry to classify the physical nature of edges in images. In this paper, the aim is to present a novel strategy to handle both photometric and geometric information for edge classification. Photometric information is obtained through the use of quasi-invariants while geometric information is derived from the orientation and contrast of edges. Different combination frameworks are compared with a new principled approach that captures both information into the same descriptor. From large scale experiments on different datasets, it is shown that, in addition to photometric information, the geometry of edges is an important visual cue to distinguish between different edge types. It is concluded that by combining both cues the performance improves by more than 7% for shadows and highlights.  
  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 1051-4651 ISBN 978-1-4673-2216-4 Medium  
  Area Expedition Conference ICPR  
  Notes ISE Approved no  
  Call Number Admin @ si @ GGG2012b Serial 2142  
Permanent link to this record
 

 
Author Francesco Ciompi edit  openurl
  Title Multi-Class Learning for Vessel Characterization in Intravascular Ultrasound Type Book Whole
  Year 2012 Publication PhD Thesis, Universitat de Barcelona-CVC Abbreviated Journal  
  Volume Issue (up) Pages  
  Keywords  
  Abstract In this thesis we tackle the problem of automatic characterization of human coronary vessel in Intravascular Ultrasound (IVUS) image modality. The basis for the whole characterization process is machine learning applied to multi-class problems. In all the presented approaches, the Error-Correcting Output Codes (ECOC) framework is used as central element for the design of multi-class classifiers.
Two main topics are tackled in this thesis. First, the automatic detection of the vessel borders is presented. For this purpose, a novel context-aware classifier for multi-class classification of the vessel morphology is presented, namely ECOC-DRF. Based on ECOC-DRF, the lumen border and the media-adventitia border in IVUS are robustly detected by means of a novel holistic approach, achieving an error comparable with inter-observer variability and with state of the art methods.
The two vessel borders define the atheroma area of the vessel. In this area, tissue characterization is required. For this purpose, we present a framework for automatic plaque characterization by processing both texture in IVUS images and spectral information in raw Radio Frequency data. Furthermore, a novel method for fusing in-vivo and in-vitro IVUS data for plaque characterization is presented, namely pSFFS. The method demonstrates to effectively fuse data generating a classifier that improves the tissue characterization in both in-vitro and in-vivo datasets.
A novel method for automatic video summarization in IVUS sequences is also presented. The method aims to detect the key frames of the sequence, i.e., the frames representative of morphological changes. This novel method represents the basis for video summarization in IVUS as well as the markers for the partition of the vessel into morphological and clinically interesting events.
Finally, multi-class learning based on ECOC is applied to lung tissue characterization in Computed Tomography. The novel proposed approach, based on supervised and unsupervised learning, achieves accurate tissue classification on a large and heterogeneous dataset.
 
  Address  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Petia Radeva;Oriol Pujol  
  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 Approved no  
  Call Number Admin @ si @ Cio2012 Serial 2146  
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Author Karel Paleček; David Geronimo; Frederic Lerasle edit  doi
isbn  openurl
  Title Pre-attention cues for person detection Type Conference Article
  Year 2012 Publication Cognitive Behavioural Systems, COST 2102 International Training School Abbreviated Journal  
  Volume Issue (up) Pages 225-235  
  Keywords  
  Abstract Current state-of-the-art person detectors have been proven reliable and achieve very good detection rates. However, the performance is often far from real time, which limits their use to low resolution images only. In this paper, we deal with candidate window generation problem for person detection, i.e. we want to reduce the computational complexity of a person detector by reducing the number of regions that has to be evaluated. We base our work on Alexe’s paper [1], which introduced several pre-attention cues for generic object detection. We evaluate these cues in the context of person detection and show that their performance degrades rapidly for scenes containing multiple objects of interest such as pictures from urban environment. We extend this set by new cues, which better suits our class-specific task. The cues are designed to be simple and efficient, so that they can be used in the pre-attention phase of a more complex sliding window based person detector.  
  Address Dresden, Germany  
  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 978-3-642-34583-8 Medium  
  Area Expedition Conference COST-TS  
  Notes ADAS Approved no  
  Call Number Admin @ si @ PGL2012 Serial 2148  
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Author Petia Radeva; Michal Drozdzal; Santiago Segui; Laura Igual; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria edit   pdf
doi  isbn
openurl 
  Title Active labeling: Application to wireless endoscopy analysis Type Conference Article
  Year 2012 Publication High Performance Computing and Simulation, International Conference on Abbreviated Journal  
  Volume Issue (up) Pages 174-181  
  Keywords  
  Abstract Today, robust learners trained in a real supervised machine learning application should count with a rich collection of positive and negative examples. Although in many applications, it is not difficult to obtain huge amount of data, labeling those data can be a very expensive process, especially when dealing with data of high variability and complexity. A good example of such cases are data from medical imaging applications where annotating anomalies like tumors, polyps, atherosclerotic plaque or informative frames in wireless endoscopy need highly trained experts. Building a representative set of training data from medical videos (e.g. Wireless Capsule Endoscopy) means that thousands of frames to be labeled by an expert. It is quite normal that data in new videos come different and thus are not represented by the training set. In this paper, we review the main approaches on active learning and illustrate how active learning can help to reduce expert effort in constructing the training sets. We show that applying active learning criteria, the number of human interventions can be significantly reduced. The proposed system allows the annotation of informative/non-informative frames of Wireless Capsule Endoscopy video containing more than 30000 frames each one with less than 100 expert ”clicks”.  
  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 978-1-4673-2359-8 Medium  
  Area Expedition Conference HPCS  
  Notes MILAB; OR;MV Approved no  
  Call Number Admin @ si @ RDS2012 Serial 2152  
Permanent link to this record
 

 
Author Jose Carlos Rubio; Joan Serrat; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title Video Co-segmentation Type Conference Article
  Year 2012 Publication 11th Asian Conference on Computer Vision Abbreviated Journal  
  Volume 7725 Issue (up) Pages 13-24  
  Keywords  
  Abstract Segmentation of a single image is in general a highly underconstrained problem. A frequent approach to solve it is to somehow provide prior knowledge or constraints on how the objects of interest look like (in terms of their shape, size, color, location or structure). Image co-segmentation trades the need for such knowledge for something much easier to obtain, namely, additional images showing the object from other viewpoints. Now the segmentation problem is posed as one of differentiating the similar object regions in all the images from the more varying background. In this paper, for the first time, we extend this approach to video segmentation: given two or more video sequences showing the same object (or objects belonging to the same class) moving in a similar manner, we aim to outline its region in all the frames. In addition, the method works in an unsupervised manner, by learning to segment at testing time. We compare favorably with two state-of-the-art methods on video segmentation and report results on benchmark videos.  
  Address Daejeon, 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 978-3-642-37443-2 Medium  
  Area Expedition Conference ACCV  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RSL2012d Serial 2153  
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Author Cristhian Aguilera; M.Ramos; Angel Sappa edit   pdf
doi  isbn
openurl 
  Title Simulated Annealing: A Novel Application of Image Processing in the Wood Area Type Book Chapter
  Year 2012 Publication Simulated Annealing – Advances, Applications and Hybridizations Abbreviated Journal  
  Volume Issue (up) Pages 91-104  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor Marcos de Sales Guerra Tsuzuki  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-953-51-0710-1 Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ ARS2012 Serial 2156  
Permanent link to this record
 

 
Author Monica Piñol; Angel Sappa; Ricardo Toledo edit   pdf
doi  isbn
openurl 
  Title MultiTable Reinforcement for Visual Object Recognition Type Conference Article
  Year 2012 Publication 4th International Conference on Signal and Image Processing Abbreviated Journal  
  Volume 221 Issue (up) Pages 469-480  
  Keywords  
  Abstract This paper presents a bag of feature based method for visual object recognition. Our contribution is focussed on the selection of the best feature descriptor. It is implemented by using a novel multi-table reinforcement learning method that selects among five of classical descriptors (i.e., Spin, SIFT, SURF, C-SIFT and PHOW) the one that best describes each image. Experimental results and comparisons are provided showing the improvements achieved with the proposed approach.  
  Address Coimbatore, India  
  Corporate Author Thesis  
  Publisher Springer India Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 1876-1100 ISBN 978-81-322-0996-6 Medium  
  Area Expedition Conference ICSIP  
  Notes ADAS Approved no  
  Call Number Admin @ si @ PST2012 Serial 2157  
Permanent link to this record
 

 
Author Mohammad Rouhani; Angel Sappa edit  doi
isbn  openurl
  Title Non-Rigid Shape Registration: A Single Linear Least Squares Framework Type Conference Article
  Year 2012 Publication 12th European Conference on Computer Vision Abbreviated Journal  
  Volume 7578 Issue (up) Pages 264-277  
  Keywords  
  Abstract This paper proposes a non-rigid registration formulation capturing both global and local deformations in a single framework. This formulation is based on a quadratic estimation of the registration distance together with a quadratic regularization term. Hence, the optimal transformation parameters are easily obtained by solving a liner system of equations, which guarantee a fast convergence. Experimental results with challenging 2D and 3D shapes are presented to show the validity of the proposed framework. Furthermore, comparisons with the most relevant approaches are provided.  
  Address Florencia  
  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 978-3-642-33785-7 Medium  
  Area Expedition Conference ECCV  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RoS2012a Serial 2158  
Permanent link to this record
 

 
Author Miguel Oliveira; V.Santos; Angel Sappa edit  openurl
  Title Short term path planning using a multiple hypothesis evaluation approach for an autonomous driving competition Type Conference Article
  Year 2012 Publication IEEE 4th Workshop on Planning, Perception and Navigation for Intelligent Vehicles Abbreviated Journal  
  Volume Issue (up) Pages  
  Keywords  
  Abstract  
  Address Algarve; Portugal  
  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 PPNIV  
  Notes ADAS Approved no  
  Call Number Admin @ si @ OSS2012c Serial 2159  
Permanent link to this record
 

 
Author Marina Alberti; Simone Balocco; Xavier Carrillo; Josepa Mauri; Petia Radeva edit   pdf
doi  isbn
openurl 
  Title Automatic Non-Rigid Temporal Alignment of IVUS Sequences Type Conference Article
  Year 2012 Publication 15th International Conference on Medical Image Computing and Computer Assisted Intervention Abbreviated Journal  
  Volume 1 Issue (up) Pages 642-650  
  Keywords  
  Abstract Clinical studies on atherosclerosis regression/progression performed by Intravascular Ultrasound analysis require the alignment of pullbacks of the same patient before and after clinical interventions. In this paper, a methodology for the automatic alignment of IVUS sequences based on the Dynamic Time Warping technique is proposed. The method is adapted to the specific IVUS alignment task by applying the non-rigid alignment technique to multidimensional morphological signals, and by introducing a sliding window approach together with a regularization term. To show the effectiveness of our method, an extensive validation is performed both on synthetic data and in-vivo IVUS sequences. The proposed method is robust to stent deployment and post dilation surgery and reaches an alignment error of approximately 0.7 mm for in-vivo data, which is comparable to the inter-observer variability.  
  Address Nice, France  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin, Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-33414-6 Medium  
  Area Expedition Conference MICCAI  
  Notes MILAB Approved no  
  Call Number Admin @ si @ ABC2012 Serial 2168  
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Author Onur Ferhat edit   pdf
openurl 
  Title Eye-Tracking with Webcam-Based Setups: Implementation of a Real-Time System and an Analysis of Factors Affecting Performance Type Report
  Year 2012 Publication CVC Technical Report Abbreviated Journal  
  Volume 172 Issue (up) Pages  
  Keywords Computer vision, eye-tracking, gaussian process, feature selection, optical flow  
  Abstract In the recent years commercial eye-tracking hardware has become more common, with the introduction of new models from several brands that have better performance and easier setup procedures. A cause and at the same time a result of this phenomenon is the popularity of eye-tracking research directed at marketing, accessibility and usability, among others.
One problem with these hardware components is scalability, because both the price and the necessary expertise to operate them makes it practically impossible in the large scale. In this work, we analyze the feasibility of a software eye-tracking system based on a single, ordinary webcam. Our aim is to discover the limits of such a system and to see whether it provides acceptable performances.
The significance of this setup is that it is the most common setup found in consumer environments, off-the-shelf electronic devices such as laptops, mobile phones and tablet computers. As no special equipment such as infrared lights, mirrors or zoom lenses are used; setting up and calibrating the system is easier compared to other approaches using these components.
Our work is based on the open source application Opengazer, which provides a good starting point for our contributions. We propose several improvements in order to push the system's performance further and make it feasible as a robust, real-time device. Then we carry out an elaborate experiment involving 18 human subjects and 4 different system setups. Finally, we give an analysis of the results and discuss the effects of setup changes, subject differences and modifications in the software.
 
  Address Bellaterra  
  Corporate Author Computer Vision Center Thesis Master's thesis  
  Publisher Place of Publication Editor Fernando Vilariño  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MV Approved no  
  Call Number Admin @ si @ Fer2012; IAM @ iam @ Fer2012 Serial 2165  
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Author Pedro Martins; Paulo Carvalho; Carlo Gatta edit   pdf
openurl 
  Title Stable Salient Shapes Type Conference Article
  Year 2012 Publication International Conference on Digital Image Computing: Techniques and Applications Abbreviated Journal  
  Volume Issue (up) Pages  
  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 DICTA  
  Notes MILAB Approved no  
  Call Number Admin @ si @ MCG2012b Serial 2166  
Permanent link to this record
 

 
Author Jaume Gibert; Ernest Valveny; Horst Bunke; Alicia Fornes edit   pdf
doi  isbn
openurl 
  Title On the Correlation of Graph Edit Distance and L1 Distance in the Attribute Statistics Embedding Space Type Conference Article
  Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal  
  Volume 7626 Issue (up) Pages 135-143  
  Keywords  
  Abstract Graph embeddings in vector spaces aim at assigning a pattern vector to every graph so that the problems of graph classification and clustering can be solved by using data processing algorithms originally developed for statistical feature vectors. An important requirement graph features should fulfil is that they reproduce as much as possible the properties among objects in the graph domain. In particular, it is usually desired that distances between pairs of graphs in the graph domain closely resemble those between their corresponding vectorial representations. In this work, we analyse relations between the edit distance in the graph domain and the L1 distance of the attribute statistics based embedding, for which good classification performance has been reported on various datasets. We show that there is actually a high correlation between the two kinds of distances provided that the corresponding parameter values that account for balancing the weight between node and edge based features are properly selected.  
  Address  
  Corporate Author Thesis  
  Publisher Springer-Berlag, Berlin Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-34165-6 Medium  
  Area Expedition Conference SSPR&SPR  
  Notes DAG Approved no  
  Call Number Admin @ si @ GVB2012c Serial 2167  
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Author Rui Hua; Oriol Pujol; Francesco Ciompi; Marina Alberti; Simone Balocco; Josepa Mauri; Petia Radeva edit   pdf
openurl 
  Title Stent Strut Detection by Classifying a Wide Set of IVUS Features Type Conference Article
  Year 2012 Publication Computed Assisted Stenting Workshop Abbreviated Journal  
  Volume Issue (up) Pages  
  Keywords  
  Abstract  
  Address Nice, France  
  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 STENT  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ HPC2012 Serial 2169  
Permanent link to this record
 

 
Author Adela Barbulescu; Wenjuan Gong; Jordi Gonzalez; Thomas B. Moeslund; Xavier Roca edit   pdf
url  isbn
openurl 
  Title 3D Human Pose Estimation Using 2D Body Part Detectors Type Conference Article
  Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue (up) Pages 2484 - 2487  
  Keywords  
  Abstract Automatic 3D reconstruction of human poses from monocular images is a challenging and popular topic in the computer vision community, which provides a wide range of applications in multiple areas. Solutions for 3D pose estimation involve various learning approaches, such as support vector machines and Gaussian processes, but many encounter difficulties in cluttered scenarios and require additional input data, such as silhouettes, or controlled camera settings. We present a framework that is capable of estimating the 3D pose of a person from single images or monocular image sequences without requiring background information and which is robust to camera variations. The framework models the non-linearity present in human pose estimation as it benefits from flexible learning approaches, including a highly customizable 2D detector. Results on the HumanEva benchmark show how they perform and influence the quality of the 3D pose estimates.  
  Address Tsubuka, 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 ISE Approved no  
  Call Number Admin @ si @ BGG2012 Serial 2172  
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