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Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
Title Current Challenges on Polyp Detection in Colonoscopy Videos: From Region Segmentation to Region Classification. a Pattern Recognition-based Approach.ased Approach Type Conference Article
Year 2011 Publication 2nd International Workshop on Medical Image Analysis and Descriptionfor Diagnosis Systems Abbreviated Journal
Volume Issue Pages 62-71
Keywords Medical Imaging, Colonoscopy, Pattern Recognition, Segmentation, Polyp Detection, Region Description, Machine Learning, Real-time.
Abstract In this paper we present our approach on real-time polyp detection in colonoscopy videos. Our method consists of three stages: Image Segmentation, Region Description and Image Classification. Taking into account the constraints of our project, we introduce our segmentation system that is based on the model of appearance of the polyp that we have defined after observing real videos from colonoscopy processes. The output of this stage will ideally be a low number of regions of which one of them should cover the whole polyp region (if there is one in the image). This regions will be described in terms of features and, as a result of a machine learning schema, classified based on the values that they have for the several features that we will use on their description. Although we are still on the early stages of the project, we present some preliminary segmentation results that indicates that we are going in a good direction.
Address Rome, Italy
Corporate Author Thesis
Publisher SciTePress Place of Publication Editor Djemal, Khalifa
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (down) Medium
Area 800 Expedition Conference MIAD
Notes MV;SIAI Approved no
Call Number IAM @ iam @ BSV2011a Serial 1695
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Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
Title Integration of Valley Orientation Distribution for Polyp Region Identification in Colonoscopy Type Conference Article
Year 2011 Publication In MICCAI 2011 Workshop on Computational and Clinical Applications in Abdominal Imaging Abbreviated Journal
Volume 6668 Issue Pages 76-83
Keywords
Abstract This work presents a region descriptor based on the integration of the information that the depth of valleys image provides. The depth of valleys image is based on the presence of intensity valleys around polyps due to the image acquisition. Our proposed method consists of defining, for each point, a series of radial sectors around it and then accumulates the maxima of the depth of valleys image only if the orientation of the intensity valley coincides with the orientation of the sector above. We apply our descriptor to a prior segmentation of the images and we present promising results on polyp detection, outperforming other approaches that also integrate depth of valleys information.
Address Toronto, Canada
Corporate Author Thesis
Publisher Springer Link Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN (down) Medium
Area 800 Expedition Conference ABI
Notes MV;SIAI Approved no
Call Number IAM @ iam @ BSV2011d Serial 1698
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Author Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Petia Radeva; Fernando Azpiroz; Juan Malagelada
Title Device, system and method for automatic detection of contractile activity in an image frame Type Patent
Year 2011 Publication US 2011/0044515 A1 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract A device, system and method for automatic detection of contractile activity of a body lumen in an image frame is provided, wherein image frames during contractile activity are captured and/or image frames including contractile activity are automatically detected, such as through pattern recognition and/or feature extraction to trace image frames including contractions, e.g., with wrinkle patterns. A manual procedure of annotation of contractions, e.g. tonic contractions in capsule endoscopy, may consist of the visualization of the whole video by a specialist, and the labeling of the contraction frames. Embodiments of the present invention may be suitable for implementation in an in vivo imaging system.
Address Pearl Cohen Zedek Latzer, LLP, 1500 Broadway 12th Floor, New York (NY) 10036 (US)
Corporate Author US Patent Office 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 (down) Medium
Area Expedition Conference
Notes MV;OR;MILAB;SIAI Approved no
Call Number IAM @ iam @ SVV2011 Serial 1701
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Author Gerard Lacey; Fernando Vilariño
Title Endoscopy system with motion sensors Type Patent
Year 2011 Publication US 2011/0032347 A1 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract An endoscopy system (1) comprises an endoscope (2) with a camera (3) at its tip. The endoscope extends through an endoscope guide (4) for guiding movement of the endoscope and for measurement of its movement as it enters the body. The guide (4) comprises a generally conical body (5) having a through passage (105) through which the endoscope (2) extends. A motion sensor comprises an optical transmitter (7) and a detector (8) mounted alongside the passage (105) to measure the insertion-withdrawal linear motion and also rotation of the endoscope by the endoscopist's hand. The system (1) also comprises a flexure controller (10) having wheels operated by the endoscopist. The camera (3), the motion sensor (7/8), and the flexure controller (10) are all connected to a processor (11) which feeds a display.
Address Jacobson Holman PPLC; 400 Seventh Street, N.W. Suite 600; Whashington DC 20004 DC
Corporate Author USPTO 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 (down) Medium
Area 800 Expedition Conference
Notes MV;SIAI Approved no
Call Number IAM @ iam @ LaV2011 Serial 1703
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Author Ferran Diego; Daniel Ponsa; Joan Serrat; Antonio Lopez
Title Video Alignment for Change Detection Type Journal Article
Year 2011 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 20 Issue 7 Pages 1858-1869
Keywords video alignment
Abstract In this work, we address the problem of aligning two video sequences. Such alignment refers to synchronization, i.e., the establishment of temporal correspondence between frames of the first and second video, followed by spatial registration of all the temporally corresponding frames. Video synchronization and alignment have been attempted before, but most often in the relatively simple cases of fixed or rigidly attached cameras and simultaneous acquisition. In addition, restrictive assumptions have been applied, including linear time correspondence or the knowledge of the complete trajectories of corresponding scene points; to some extent, these assumptions limit the practical applicability of any solutions developed. We intend to solve the more general problem of aligning video sequences recorded by independently moving cameras that follow similar trajectories, based only on the fusion of image intensity and GPS information. The novelty of our approach is to pose the synchronization as a MAP inference problem on a Bayesian network including the observations from these two sensor types, which have been proved complementary. Alignment results are presented in the context of videos recorded from vehicles driving along the same track at different times, for different road types. In addition, we explore two applications of the proposed video alignment method, both based on change detection between aligned videos. One is the detection of vehicles, which could be of use in ADAS. The other is online difference spotting videos of surveillance rounds.
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 (down) Medium
Area Expedition Conference
Notes ADAS; IF Approved no
Call Number DPS 2011; ADAS @ adas @ dps2011 Serial 1705
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Author Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Xavier Roca
Title Efficient Discriminative Multiresolution Cascade for Real-Time Human Detection Applications Type Journal Article
Year 2011 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 32 Issue 13 Pages 1581-1587
Keywords
Abstract Human detection is fundamental in many machine vision applications, like video surveillance, driving assistance, action recognition and scene understanding. However in most of these applications real-time performance is necessary and this is not achieved yet by current detection methods.

This paper presents a new method for human detection based on a multiresolution cascade of Histograms of Oriented Gradients (HOG) that can highly reduce the computational cost of detection search without affecting accuracy. The method consists of a cascade of sliding window detectors. Each detector is a linear Support Vector Machine (SVM) composed of HOG features at different resolutions, from coarse at the first level to fine at the last one.

In contrast to previous methods, our approach uses a non-uniform stride of the sliding window that is defined by the feature resolution and allows the detection to be incrementally refined as going from coarse-to-fine resolution. In this way, the speed-up of the cascade is not only due to the fewer number of features computed at the first levels of the cascade, but also to the reduced number of windows that need to be evaluated at the coarse resolution. Experimental results show that our method reaches a detection rate comparable with the state-of-the-art of detectors based on HOG features, while at the same time the detection search is up to 23 times faster.
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 (down) Medium
Area Expedition Conference
Notes ISE Approved no
Call Number Admin @ si @ PGB2011a Serial 1707
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Author Palaiahnakote Shivakumara; Anjan Dutta; Trung Quy Phan; Chew Lim Tan; Umapada Pal
Title A Novel Mutual Nearest Neighbor based Symmetry for Text Frame Classification in Video Type Journal Article
Year 2011 Publication Pattern Recognition Abbreviated Journal PR
Volume 44 Issue 8 Pages 1671-1683
Keywords
Abstract In the field of multimedia retrieval in video, text frame classification is essential for text detection, event detection, event boundary detection, etc. We propose a new text frame classification method that introduces a combination of wavelet and median moment with k-means clustering to select probable text blocks among 16 equally sized blocks of a video frame. The same feature combination is used with a new Max–Min clustering at the pixel level to choose probable dominant text pixels in the selected probable text blocks. For the probable text pixels, a so-called mutual nearest neighbor based symmetry is explored with a four-quadrant formation centered at the centroid of the probable dominant text pixels to know whether a block is a true text block or not. If a frame produces at least one true text block then it is considered as a text frame otherwise it is a non-text frame. Experimental results on different text and non-text datasets including two public datasets and our own created data show that the proposed method gives promising results in terms of recall and precision at the block and frame levels. Further, we also show how existing text detection methods tend to misclassify non-text frames as text frames in term of recall and precision at both the block and frame levels.
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 (down) Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ SDP2011 Serial 1727
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Author Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez
Title Rank Estimation in Missing Data Matrix Problems Type Journal Article
Year 2011 Publication Journal of Mathematical Imaging and Vision Abbreviated Journal JMIV
Volume 39 Issue 2 Pages 140-160
Keywords
Abstract A novel technique for missing data matrix rank estimation is presented. It is focused on matrices of trajectories, where every element of the matrix corresponds to an image coordinate from a feature point of a rigid moving object at a given frame; missing data are represented as empty entries. The objective of the proposed approach is to estimate the rank of a missing data matrix in order to fill in empty entries with some matrix completion method, without using or assuming neither the number of objects contained in the scene nor the kind of their motion. The key point of the proposed technique consists in studying the frequency behaviour of the individual trajectories, which are seen as 1D signals. The main assumption is that due to the rigidity of the moving objects, the frequency content of the trajectories will be similar after filling in their missing entries. The proposed rank estimation approach can be used in different computer vision problems, where the rank of a missing data matrix needs to be estimated. Experimental results with synthetic and real data are provided in order to empirically show the good performance of the proposed 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 0924-9907 ISBN (down) Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ JSL2011; Serial 1710
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Author Carme Julia; Felipe Lumbreras; Angel Sappa
Title A Factorization-based Approach to Photometric Stereo Type Journal Article
Year 2011 Publication International Journal of Imaging Systems and Technology Abbreviated Journal IJIST
Volume 21 Issue 1 Pages 115-119
Keywords
Abstract This article presents an adaptation of a factorization technique to tackle the photometric stereo problem. That is to recover the surface normals and reflectance of an object from a set of images obtained under different lighting conditions. The main contribution of the proposed approach is to consider pixels in shadow and saturated regions as missing data, in order to reduce their influence to the result. Concretely, an adapted Alternation technique is used to deal with missing data. Experimental results considering both synthetic and real images show the viability of the proposed factorization-based strategy. © 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 115–119, 2011.
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 (down) Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ JLS2011; ADAS @ adas @ Serial 1711
Permanent link to this record
 
 
Author Jose Seabra; Francesco Ciompi; Oriol Pujol; J. Mauri; Petia Radeva; Joao Sanchez
Title Rayleigh Mixture Model for Plaque Characterization in Intravascular Ultrasound Type Journal Article
Year 2011 Publication IEEE Transactions on Biomedical Engineering Abbreviated Journal TBME
Volume 58 Issue 5 Pages 1314-1324
Keywords
Abstract Vulnerable plaques are the major cause of carotid and coronary vascular problems, such as heart attack or stroke. A correct modeling of plaque echomorphology and composition can help the identification of such lesions. The Rayleigh distribution is widely used to describe (nearly) homogeneous areas in ultrasound images. Since plaques may contain tissues with heterogeneous regions, more complex distributions depending on multiple parameters are usually needed, such as Rice, K or Nakagami distributions. In such cases, the problem formulation becomes more complex, and the optimization procedure to estimate the plaque echomorphology is more difficult. Here, we propose to model the tissue echomorphology by means of a mixture of Rayleigh distributions, known as the Rayleigh mixture model (RMM). The problem formulation is still simple, but its ability to describe complex textural patterns is very powerful. In this paper, we present a method for the automatic estimation of the RMM mixture parameters by means of the expectation maximization algorithm, which aims at characterizing tissue echomorphology in ultrasound (US). The performance of the proposed model is evaluated with a database of in vitro intravascular US cases. We show that the mixture coefficients and Rayleigh parameters explicitly derived from the mixture model are able to accurately describe different plaque types and to significantly improve the characterization performance of an already existing methodology.
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 (down) Medium
Area Expedition Conference
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ SCP2011 Serial 1712
Permanent link to this record
 
 
Author Maria Salamo; Sergio Escalera
Title Increasing Retrieval Quality in Conversational Recommenders Type Journal Article
Year 2011 Publication IEEE Transactions on Knowledge and Data Engineering Abbreviated Journal TKDE
Volume 99 Issue Pages 1-1
Keywords
Abstract IF JCR CCIA 2.286 2009 24/103
JCR Impact Factor 2010: 1.851
A major task of research in conversational recommender systems is personalization. Critiquing is a common and powerful form of feedback, where a user can express her feature preferences by applying a series of directional critiques over the recommendations instead of providing specific preference values. Incremental Critiquing is a conversational recommender system that uses critiquing as a feedback to efficiently personalize products. The expectation is that in each cycle the system retrieves the products that best satisfy the user’s soft product preferences from a minimal information input. In this paper, we present a novel technique that increases retrieval quality based on a combination of compatibility and similarity scores. Under the hypothesis that a user learns Turing the recommendation process, we propose two novel exponential reinforcement learning approaches for compatibility that take into account both the instant at which the user makes a critique and the number of satisfied critiques. Moreover, we consider that the impact of features on the similarity differs according to the preferences manifested by the user. We propose a global weighting approach that uses a common weight for nearest cases in order to focus on groups of relevant products. We show that our methodology significantly improves recommendation efficiency in four data sets of different sizes in terms of session length in comparison with state-of-the-art approaches. Moreover, our recommender shows higher robustness against noisy user data when compared to classical approaches
Address
Corporate Author Thesis
Publisher IEEE Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1041-4347 ISBN (down) Medium
Area Expedition Conference
Notes MILAB; HuPBA Approved no
Call Number Admin @ si @ SaE2011 Serial 1713
Permanent link to this record
 
 
Author Sergio Escalera; David Masip; Eloi Puertas; Petia Radeva; Oriol Pujol
Title Online Error-Correcting Output Codes Type Journal Article
Year 2011 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 32 Issue 3 Pages 458-467
Keywords
Abstract IF JCR CCIA 1.303 2009 54/103
This article proposes a general extension of the error correcting output codes framework to the online learning scenario. As a result, the final classifier handles the addition of new classes independently of the base classifier used. In particular, this extension supports the use of both online example incremental and batch classifiers as base learners. The extension of the traditional problem independent codings one-versus-all and one-versus-one is introduced. Furthermore, two new codings are proposed, unbalanced online ECOC and a problem dependent online ECOC. This last online coding technique takes advantage of the problem data for minimizing the number of dichotomizers used in the ECOC framework while preserving a high accuracy. These techniques are validated on an online setting of 11 data sets from UCI database and applied to two real machine vision applications: traffic sign recognition and face recognition. As a result, the online ECOC techniques proposed provide a feasible and robust way for handling new classes using any base classifier.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication North Holland Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0167-8655 ISBN (down) Medium
Area Expedition Conference
Notes MILAB;OR;HuPBA;MV Approved no
Call Number Admin @ si @ EMP2011 Serial 1714
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Author Eduard Vazquez; Ramon Baldrich; Joost Van de Weijer; Maria Vanrell
Title Describing Reflectances for Colour Segmentation Robust to Shadows, Highlights and Textures Type Journal Article
Year 2011 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI
Volume 33 Issue 5 Pages 917-930
Keywords
Abstract The segmentation of a single material reflectance is a challenging problem due to the considerable variation in image measurements caused by the geometry of the object, shadows, and specularities. The combination of these effects has been modeled by the dichromatic reflection model. However, the application of the model to real-world images is limited due to unknown acquisition parameters and compression artifacts. In this paper, we present a robust model for the shape of a single material reflectance in histogram space. The method is based on a multilocal creaseness analysis of the histogram which results in a set of ridges representing the material reflectances. The segmentation method derived from these ridges is robust to both shadow, shading and specularities, and texture in real-world images. We further complete the method by incorporating prior knowledge from image statistics, and incorporate spatial coherence by using multiscale color contrast information. Results obtained show that our method clearly outperforms state-of-the-art segmentation methods on a widely used segmentation benchmark, having as a main characteristic its excellent performance in the presence of shadows and highlights at low computational cost.
Address Los Alamitos; CA; USA;
Corporate Author Thesis
Publisher IEEE Computer Society Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0162-8828 ISBN (down) Medium
Area Expedition Conference
Notes CIC Approved no
Call Number Admin @ si @ VBW2011 Serial 1715
Permanent link to this record
 
 
Author Ariel Amato; Mikhail Mozerov; Andrew Bagdanov; Jordi Gonzalez
Title Accurate Moving Cast Shadow Suppression Based on Local Color Constancy detection Type Journal Article
Year 2011 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 20 Issue 10 Pages 2954 - 2966
Keywords
Abstract This paper describes a novel framework for detection and suppression of properly shadowed regions for most possible scenarios occurring in real video sequences. Our approach requires no prior knowledge about the scene, nor is it restricted to specific scene structures. Furthermore, the technique can detect both achromatic and chromatic shadows even in the presence of camouflage that occurs when foreground regions are very similar in color to shadowed regions. The method exploits local color constancy properties due to reflectance suppression over shadowed regions. To detect shadowed regions in a scene, the values of the background image are divided by values of the current frame in the RGB color space. We show how this luminance ratio can be used to identify segments with low gradient constancy, which in turn distinguish shadows from foreground. Experimental results on a collection of publicly available datasets illustrate the superior performance of our method compared with the most sophisticated, state-of-the-art shadow detection algorithms. These results show that our approach is robust and accurate over a broad range of shadow types and challenging video conditions.
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 1057-7149 ISBN (down) Medium
Area Expedition Conference
Notes ISE Approved no
Call Number Admin @ si @ AMB2011 Serial 1716
Permanent link to this record
 
 
Author Arjan Gijsenij; Theo Gevers; Joost Van de Weijer
Title Computational Color Constancy: Survey and Experiments Type Journal Article
Year 2011 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 20 Issue 9 Pages 2475-2489
Keywords computational color constancy;computer vision application;gamut-based method;learning-based method;static method;colour vision;computer vision;image colour analysis;learning (artificial intelligence);lighting
Abstract Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-the- art methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available data sets. Finally, various freely available methods, of which some are considered to be state-of-the-art, are evaluated on two data sets.
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 1057-7149 ISBN (down) Medium
Area Expedition Conference
Notes ISE;CIC Approved no
Call Number Admin @ si @ GGW2011 Serial 1717
Permanent link to this record