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Author Joan Serrat; Felipe Lumbreras; Idoia Ruiz edit   pdf
url  openurl
  Title Learning to measure for preshipment garment sizing Type Journal Article
  Year 2018 Publication Measurement Abbreviated Journal MEASURE  
  Volume 130 Issue Pages 327-339  
  Keywords (down) Apparel; Computer vision; Structured prediction; Regression  
  Abstract Clothing is still manually manufactured for the most part nowadays, resulting in discrepancies between nominal and real dimensions, and potentially ill-fitting garments. Hence, it is common in the apparel industry to manually perform measures at preshipment time. We present an automatic method to obtain such measures from a single image of a garment that speeds up this task. It is generic and extensible in the sense that it does not depend explicitly on the garment shape or type. Instead, it learns through a probabilistic graphical model to identify the different contour parts. Subsequently, a set of Lasso regressors, one per desired measure, can predict the actual values of the measures. We present results on a dataset of 130 images of jackets and 98 of pants, of varying sizes and styles, obtaining 1.17 and 1.22 cm of mean absolute error, respectively.  
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  Notes ADAS; MSIAU; 600.122; 600.118 Approved no  
  Call Number Admin @ si @ SLR2018 Serial 3128  
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Author David Geronimo; Antonio Lopez; Angel Sappa; Thorsten Graf edit   pdf
url  doi
openurl 
  Title Survey on Pedestrian Detection for Advanced Driver Assistance Systems Type Journal Article
  Year 2010 Publication IEEE Transaction on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI  
  Volume 32 Issue 7 Pages 1239–1258  
  Keywords (down) ADAS, pedestrian detection, on-board vision, survey  
  Abstract Advanced driver assistance systems (ADASs), and particularly pedestrian protection systems (PPSs), have become an active research area aimed at improving traffic safety. The major challenge of PPSs is the development of reliable on-board pedestrian detection systems. Due to the varying appearance of pedestrians (e.g., different clothes, changing size, aspect ratio, and dynamic shape) and the unstructured environment, it is very difficult to cope with the demanded robustness of this kind of system. Two problems arising in this research area are the lack of public benchmarks and the difficulty in reproducing many of the proposed methods, which makes it difficult to compare the approaches. As a result, surveying the literature by enumerating the proposals one-after-another is not the most useful way to provide a comparative point of view. Accordingly, we present a more convenient strategy to survey the different approaches. We divide the problem of detecting pedestrians from images into different processing steps, each with attached responsibilities. Then, the different proposed methods are analyzed and classified with respect to each processing stage, favoring a comparative viewpoint. Finally, discussion of the important topics is presented, putting special emphasis on the future needs and challenges.  
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  ISSN 0162-8828 ISBN Medium  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ GLS2010 Serial 1340  
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Author Meysam Madadi; Sergio Escalera; Jordi Gonzalez; Xavier Roca; Felipe Lumbreras edit  doi
openurl 
  Title Multi-part body segmentation based on depth maps for soft biometry analysis Type Journal Article
  Year 2015 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 56 Issue Pages 14-21  
  Keywords (down) 3D shape context; 3D point cloud alignment; Depth maps; Human body segmentation; Soft biometry analysis  
  Abstract This paper presents a novel method extracting biometric measures using depth sensors. Given a multi-part labeled training data, a new subject is aligned to the best model of the dataset, and soft biometrics such as lengths or circumference sizes of limbs and body are computed. The process is performed by training relevant pose clusters, defining a representative model, and fitting a 3D shape context descriptor within an iterative matching procedure. We show robust measures by applying orthogonal plates to body hull. We test our approach in a novel full-body RGB-Depth data set, showing accurate estimation of soft biometrics and better segmentation accuracy in comparison with random forest approach without requiring large training data.  
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  Notes HuPBA; ISE; ADAS; 600.076;600.049; 600.063; 600.054; 302.018;MILAB Approved no  
  Call Number Admin @ si @ MEG2015 Serial 2588  
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Author Aura Hernandez-Sabate; Debora Gil; Jaume Garcia; Enric Marti edit   pdf
doi  openurl
  Title Image-based Cardiac Phase Retrieval in Intravascular Ultrasound Sequences Type Journal Article
  Year 2011 Publication IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control Abbreviated Journal T-UFFC  
  Volume 58 Issue 1 Pages 60-72  
  Keywords (down) 3-D exploring; ECG; band-pass filter; cardiac motion; cardiac phase retrieval; coronary arteries; electrocardiogram signal; image intensity local mean evolution; image-based cardiac phase retrieval; in vivo pullbacks acquisition; intravascular ultrasound sequences; longitudinal motion; signal extrema; time 36 ms; band-pass filters; biomedical ultrasonics; cardiovascular system; electrocardiography; image motion analysis; image retrieval; image sequences; medical image processing; ultrasonic imaging  
  Abstract Longitudinal motion during in vivo pullbacks acquisition of intravascular ultrasound (IVUS) sequences is a major artifact for 3-D exploring of coronary arteries. Most current techniques are based on the electrocardiogram (ECG) signal to obtain a gated pullback without longitudinal motion by using specific hardware or the ECG signal itself. We present an image-based approach for cardiac phase retrieval from coronary IVUS sequences without an ECG signal. A signal reflecting cardiac motion is computed by exploring the image intensity local mean evolution. The signal is filtered by a band-pass filter centered at the main cardiac frequency. Phase is retrieved by computing signal extrema. The average frame processing time using our setup is 36 ms. Comparison to manually sampled sequences encourages a deeper study comparing them to ECG signals.  
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  ISSN 0885-3010 ISBN Medium  
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  Notes IAM;ADAS Approved no  
  Call Number IAM @ iam @ HGG2011 Serial 1546  
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Author Felipe Lumbreras; Joan Serrat edit  openurl
  Title Segmentation of petrographical images of marbles Type Journal Article
  Year 1996 Publication Computers and Geosciences. 22(5):547–558 Abbreviated Journal  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ LuS1996b Serial 82  
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Author J. Pladellorens; Joan Serrat; A. Castell; M.J. Yzuel edit  openurl
  Title Using mathematical morphology to determine left ventricular contours. Type Journal
  Year 1993 Publication Physics in Medicine and Biology. Abbreviated Journal  
  Volume 37 Issue Pages 1877––1894  
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  Call Number ADAS @ adas @ PSC1993 Serial 146  
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Author J. Pladellorens; M.J. Yzuel; J. Castell; Joan Serrat edit  openurl
  Title Calculo automatico del volumen del ventriculo izquierdo. Comparacion con expertos. Type Journal
  Year 1993 Publication Optica Pura y Aplicada. Abbreviated Journal  
  Volume 26 Issue 3 Pages 685–691  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ PYC1993 Serial 149  
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Author A. Pujol; Jordi Vitria; Felipe Lumbreras; Juan J. Villanueva edit  doi
openurl 
  Title Topological principal component analysis for face encoding and recognition Type Journal Article
  Year 2001 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 22 Issue 6-7 Pages 769–776  
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  Abstract IF: 0.552  
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  Notes ADAS;OR;MV Approved no  
  Call Number ADAS @ adas @ PVL2001 Serial 155  
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Author A.F. Sole; S. Ngan; G. Sapiro; X. Hu; Antonio Lopez edit   pdf
openurl 
  Title Anisotropic 2-D and 3-D Averaging of fMRI Signals Type Journal Article
  Year 2001 Publication IEEE Transactions on Medical Imaging, 20(2): 86–93 (IF: 3.142) Abbreviated Journal  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ SNS2001 Serial 165  
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Author Daniel Ponsa; Robert Benavente; Felipe Lumbreras; J. Martinez; Xavier Roca edit  openurl
  Title Quality control of safety belts by machine vision inspection for real-time production Type Journal
  Year 2003 Publication Optical Engineering, 42:1114–1120 (IF: 0.877) Abbreviated Journal  
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  Notes ADAS;ISE;CIC Approved no  
  Call Number ADAS @ adas @ PRL2003 Serial 399  
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