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Author Gerard Lacey; Fernando Vilariño edit   pdf
url  openurl
  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 (up) ISBN Medium  
  Area 800 Expedition Conference  
  Notes MV;SIAI Approved no  
  Call Number IAM @ iam @ LaV2011 Serial 1703  
Permanent link to this record
 

 
Author Fernando Vilariño; Panagiota Spyridonos; Petia Radeva; Jordi Vitria; Fernando Azpiroz; Juan Malagelada edit   pdf
url  openurl
  Title Device, system and method for measurement and analysis of contractile activity Type Patent
  Year 2009 Publication US 2009/0202117 A1 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract A method and system for determining intestinal dysfunction condition are provided by classifying and analyzing image frames captured in-vivo. The method and system also relate to the detection of contractile activity in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including contractile activity, and more particularly to measurement and analysis of contractile activity of the GI tract based on image intensity of in vivo image data.  
  Address Pearl Cohen Zedek Latzer  
  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 (up) ISBN Medium  
  Area 800 Expedition Conference  
  Notes MV;OR;MILAB;SIAI Approved no  
  Call Number IAM @ iam @ VSR2009 Serial 1704  
Permanent link to this record
 

 
Author Ferran Diego; Daniel Ponsa; Joan Serrat; Antonio Lopez edit   pdf
openurl 
  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 (up) ISBN Medium  
  Area Expedition Conference  
  Notes ADAS; IF Approved no  
  Call Number DPS 2011; ADAS @ adas @ dps2011 Serial 1705  
Permanent link to this record
 

 
Author Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Xavier Roca edit  doi
openurl 
  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 (up) ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ PGB2011a Serial 1707  
Permanent link to this record
 

 
Author Palaiahnakote Shivakumara; Anjan Dutta; Trung Quy Phan; Chew Lim Tan; Umapada Pal edit  doi
openurl 
  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 (up) ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ SDP2011 Serial 1727  
Permanent link to this record
 

 
Author Victor Ponce; Sergio Escalera; Xavier Baro edit  doi
isbn  openurl
  Title Multi-modal Social Signal Analysis for Predicting Agreement in Conversation Settings Type Conference Article
  Year 2013 Publication 15th ACM International Conference on Multimodal Interaction Abbreviated Journal  
  Volume Issue Pages 495-502  
  Keywords  
  Abstract In this paper we present a non-invasive ambient intelligence framework for the analysis of non-verbal communication applied to conversational settings. In particular, we apply feature extraction techniques to multi-modal audio-RGB-depth data. We compute a set of behavioral indicators that define communicative cues coming from the fields of psychology and observational methodology. We test our methodology over data captured in victim-offender mediation scenarios. Using different state-of-the-art classification approaches, our system achieve upon 75% of recognition predicting agreement among the parts involved in the conversations, using as ground truth the experts opinions.  
  Address Sidney; Australia; December 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 (up) ISBN 978-1-4503-2129-7 Medium  
  Area Expedition Conference ICMI  
  Notes HuPBA;MV Approved no  
  Call Number Admin @ si @ PEB2013 Serial 2488  
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Author Salvatore Tabbone; Oriol Ramos Terrades edit  doi
isbn  openurl
  Title An Overview of Symbol Recognition Type Book Chapter
  Year 2014 Publication Handbook of Document Image Processing and Recognition Abbreviated Journal  
  Volume D Issue Pages 523-551  
  Keywords Pattern recognition; Shape descriptors; Structural descriptors; Symbolrecognition; Symbol spotting  
  Abstract According to the Cambridge Dictionaries Online, a symbol is a sign, shape, or object that is used to represent something else. Symbol recognition is a subfield of general pattern recognition problems that focuses on identifying, detecting, and recognizing symbols in technical drawings, maps, or miscellaneous documents such as logos and musical scores. This chapter aims at providing the reader an overview of the different existing ways of describing and recognizing symbols and how the field has evolved to attain a certain degree of maturity.  
  Address  
  Corporate Author Thesis  
  Publisher Springer London Place of Publication Editor D. Doermann; K. Tombre  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN 978-0-85729-858-4 Medium  
  Area Expedition Conference  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ TaT2014 Serial 2489  
Permanent link to this record
 

 
Author Carme Julia; Felipe Lumbreras; Angel Sappa edit  doi
openurl 
  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 (up) ISBN 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; Josepa Mauri; Petia Radeva; Joao Sanchez edit  doi
openurl 
  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 (up) ISBN Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ SCP2011 Serial 1712  
Permanent link to this record
 

 
Author Olivier Penacchio; C. Alejandro Parraga edit  url
openurl 
  Title What is the best criterion for an efficient design of retinal photoreceptor mosaics? Type Journal Article
  Year 2011 Publication Perception Abbreviated Journal PER  
  Volume 40 Issue Pages 197  
  Keywords  
  Abstract The proportions of L, M and S photoreceptors in the primate retina are arguably determined by evolutionary pressure and the statistics of the visual environment. Two information theory-based approaches have been recently proposed for explaining the asymmetrical spatial densities of photoreceptors in humans. In the first approach Garrigan et al (2010 PLoS ONE 6 e1000677), a model for computing the information transmitted by cone arrays which considers the differential blurring produced by the long-wavelength accommodation of the eye’s lens is proposed. Their results explain the sparsity of S-cones but the optimum depends weakly on the L:M cone ratio. In the second approach (Penacchio et al, 2010 Perception 39 ECVP Supplement, 101), we show that human cone arrays make the visual representation scale-invariant, allowing the total entropy of the signal to be preserved while decreasing individual neurons’ entropy in further retinotopic representations. This criterion provides a thorough description of the distribution of L:M cone ratios and does not depend on differential blurring of the signal by the lens. Here, we investigate the similarities and differences of both approaches when applied to the same database. Our results support a 2-criteria optimization in the space of cone ratios whose components are arguably important and mostly unrelated.
[This work was partially funded by projects TIN2010-21771-C02-1 and Consolider-Ingenio 2010-CSD2007-00018 from the Spanish MICINN. CAP was funded by grant RYC-2007-00484]
 
  Address  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number Admin @ si @ PeP2011a Serial 1719  
Permanent link to this record
 

 
Author C. Alejandro Parraga; Olivier Penacchio; Maria Vanrell edit  openurl
  Title Retinal Filtering Matches Natural Image Statistics at Low Luminance Levels Type Journal Article
  Year 2011 Publication Perception Abbreviated Journal PER  
  Volume 40 Issue Pages 96  
  Keywords  
  Abstract The assumption that the retina’s main objective is to provide a minimum entropy representation to higher visual areas (ie efficient coding principle) allows to predict retinal filtering in space–time and colour (Atick, 1992 Network 3 213–251). This is achieved by considering the power spectra of natural images (which is proportional to 1/f2) and the suppression of retinal and image noise. However, most studies consider images within a limited range of lighting conditions (eg near noon) whereas the visual system’s spatial filtering depends on light intensity and the spatiochromatic properties of natural scenes depend of the time of the day. Here, we explore whether the dependence of visual spatial filtering on luminance match the changes in power spectrum of natural scenes at different times of the day. Using human cone-activation based naturalistic stimuli (from the Barcelona Calibrated Images Database), we show that for a range of luminance levels, the shape of the retinal CSF reflects the slope of the power spectrum at low spatial frequencies. Accordingly, the retina implements the filtering which best decorrelates the input signal at every luminance level. This result is in line with the body of work that places efficient coding as a guiding neural principle.  
  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 (up) ISBN Medium  
  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number Admin @ si @ PPV2011 Serial 1720  
Permanent link to this record
 

 
Author Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez edit   pdf
doi  openurl
  Title Determining the Best Suited Semantic Events for Cognitive Surveillance Type Journal Article
  Year 2011 Publication Expert Systems with Applications Abbreviated Journal EXSY  
  Volume 38 Issue 4 Pages 4068–4079  
  Keywords Cognitive surveillance; Event modeling; Content-based video retrieval; Ontologies; Advanced user interfaces  
  Abstract State-of-the-art systems on cognitive surveillance identify and describe complex events in selected domains, thus providing end-users with tools to easily access the contents of massive video footage. Nevertheless, as the complexity of events increases in semantics and the types of indoor/outdoor scenarios diversify, it becomes difficult to assess which events describe better the scene, and how to model them at a pixel level to fulfill natural language requests. We present an ontology-based methodology that guides the identification, step-by-step modeling, and generalization of the most relevant events to a specific domain. Our approach considers three steps: (1) end-users provide textual evidence from surveilled video sequences; (2) transcriptions are analyzed top-down to build the knowledge bases for event description; and (3) the obtained models are used to generalize event detection to different image sequences from the surveillance domain. This framework produces user-oriented knowledge that improves on existing advanced interfaces for video indexing and retrieval, by determining the best suited events for video understanding according to end-users. We have conducted experiments with outdoor and indoor scenes showing thefts, chases, and vandalism, demonstrating the feasibility and generalization of this proposal.  
  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 (up) ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ FBR2011a Serial 1722  
Permanent link to this record
 

 
Author Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez edit   pdf
doi  openurl
  Title Augmenting Video Surveillance Footage with Virtual Agents for Incremental Event Evaluation Type Journal Article
  Year 2011 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 32 Issue 6 Pages 878–889  
  Keywords  
  Abstract The fields of segmentation, tracking and behavior analysis demand for challenging video resources to test, in a scalable manner, complex scenarios like crowded environments or scenes with high semantics. Nevertheless, existing public databases cannot scale the presence of appearing agents, which would be useful to study long-term occlusions and crowds. Moreover, creating these resources is expensive and often too particularized to specific needs. We propose an augmented reality framework to increase the complexity of image sequences in terms of occlusions and crowds, in a scalable and controllable manner. Existing datasets can be increased with augmented sequences containing virtual agents. Such sequences are automatically annotated, thus facilitating evaluation in terms of segmentation, tracking, and behavior recognition. In order to easily specify the desired contents, we propose a natural language interface to convert input sentences into virtual agent behaviors. Experimental tests and validation in indoor, street, and soccer environments are provided to show the feasibility of the proposed approach in terms of robustness, scalability, and semantics.  
  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 (up) ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ FBR2011b Serial 1723  
Permanent link to this record
 

 
Author Albert Ali Salah; Theo Gevers; Nicu Sebe; Alessandro Vinciarelli edit  openurl
  Title Computer Vision for Ambient Intelligence Type Journal Article
  Year 2011 Publication Journal of Ambient Intelligence and Smart Environments Abbreviated Journal JAISE  
  Volume 3 Issue 3 Pages 187-191  
  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 (up) ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ SGS2011a Serial 1725  
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Author Farhan Riaz; Fernando Vilariño; Mario Dinis-Ribeiro; Miguel Coimbraln edit   pdf
doi  isbn
openurl 
  Title Identifying Potentially Cancerous Tissues in Chromoendoscopy Images Type Conference Article
  Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 6669 Issue Pages 709-716  
  Keywords Endoscopy, Computer Assisted Diagnosis, Gradient.  
  Abstract The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered.  
  Address Las Palmas de Gran Canaria. Spain  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Berlin Editor J. Vitria, J.M. Sanches, and M. Hernandez  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN 978-3-642-21256-7 Medium  
  Area 800 Expedition Conference IbPRIA  
  Notes MV;SIAI Approved no  
  Call Number Admin @ si @ RVD2011; IAM @ iam @ RVD2011 Serial 1726  
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