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Carla Maria Modena

Permanent researcher
  • Phone: 0461314508
  • FBK Povo
Short bio

Carla Maria Modena received her degree in Mathematics from the University of Trento in 1985. In 1986, she worked as research assistant (Wissenschaftlicher Mitarbeiter) in Ökonometrie at the Institut für Volkswirtschaftslehre, Universität Regensburg, Germany.
She joined ITC-irst, now FBK (Trento - Italy) in 1987, where she works with the Technologies of Vision (TeV) research unit.

She is interested in text detection and extraction for document image understanding (DIU and OCR) and for scene understanding (TIS). She works mainly on computer vision with applicative tasks (for example, traffic scene analyis, people re-identification). To prevent the risk of reinventing the wheel, she pays a close attention to the state-of-the art before starting each task in which she is involved in, using her ability to fully exploit the net resources and to analyse trends in upcoming conferences.

She is a member of IAPR-GIRPR.

Research interests
text localization in scene object detection people re-identification video surveillance
Publications
  1. Conci, N.; De Natale, F.G.B.; Messelodi, S.; Modena, C.M.; Verza, M.; Fioravanti, R.,
    IEEE International Smart Cities Conference (ISC2),
    IEEE,
    2016
    , (IEEE International Smart Cities Conference (ISC2),
    Trento, Italy,
    12/09/2016 - 15/09/2016)
  2. Messelodi, Stefano; Modena, Carla Maria,
    in «IMAGE AND VISION COMPUTING»,
    vol. 44,
    2015
    , pp. 44 -
    58
  3. Messelodi, Stefano; Modena, Carla Maria; Porzi, Lorenzo; Chippendale, Paul,
    i-Street: Detection, identification, augmentation of street plates in a touristic mobile application,
    Image Analysis and Processing — ICIAP 2015,
    Springer International Publishing,
    vol.9280,
    2015
    , pp. 194-
    204
    , (18th International Conference on Image Analysis and Processing,
    Genoa, Italy,
    September 7-11, 2015)
  4. Chippendale P.; Tomaselli V.; D'Alto V.; Urlini G.; Modena C.M.; Messelodi S.; Strano M.; Alce G.; Hermodsson K.; Razafimahazo M.; Michel T.; Farinella G.,
    ECCV 2014 Workshops,
    Springer,
    vol.8927,
    2014
    , pp. 375-
    390
    , (Second Workshop on Assistive Computer Vision and Robotics - ACVR at ECCV,
    Zurich, Switzerland,
    September)
  5. S. Messelodi; C.M. Modena,
    in «MULTIMEDIA TOOLS AND APPLICATIONS»,
    vol. 63,
    n. 2,
    2013
    , pp. 521 -
    545
  6. Porzi L.; Messelodi S.; Modena C.M.; Ricci E.,
    ACM Multimedia 2013,
    ACM,
    2013
    , pp. 19-
    24
    , (IMMPD'13: 3rd ACM International Workshop on Interactive Multimedia on Mobile & Portable Devices,
    Barcelona, Spain,
    22 October 2013)
  7. Zanin M.; Messelodi S.; Modena C.M.,
    DIPLODOC road stereo sequence,
    In this note we describe a road stereo sequence acquired, stored and labelled for evaluation purposes in the DIPLODOC project. The sequence, covering different scenarios, and its ground-truth, is made freely available on the web as a common base for the evaluation of road and obstacle detection algorithms.,
    2013
  8. A. Pnevmatikakis; N. Katsarakis; P. Chippendale; C. Andreatta; S. Messelodi; C.M. Modena; F. Tobia,
    Proceedings of the 2010 ACM workshop on Social, adaptive and personalized multimedia interaction and access - SAPMIA 2010,
    New York, NY,
    ACM,
    2010
    , pp. 67-
    72
    , (ACMMM International Multimedia Conference,
    Firenze, Italy,
    from 10/29/2010 to 10/29/2010)
  9. C.M. Modena,
    Segmentation of sport videos by embedded text reading,
    This report presents a module for athlete recognition in broadcast videos as part of a video entertainment application. The aim is to identify athletes by means of name or number as printed on their uniform and extract the video clips where the desired athlete is visible. Using an adaptation of a previously published algorithm we extract text from each single frame and we read it by means of an optical character recognizer (OCR). The OCRed text is then compared with an a-priori known list of athletes' names or numbers to provide a score of the presence of each athlete in that frame. Presence plausibility is then checked by a temporal persistence analysis of names/numbers extracted from subsequent frames.

    Performed experiments show that the method is promising and can provide a useful input for a module for the identification of the athlete presence in a frame.

    ,
    2010
  10. C. M. Modena; S. Messelodi,
    Recognition and tracking of embedded text in sport videos: a case study,
    Abstract - We present an athlete recognition module designed for broadcast videos, forming part of a system designed for the personalization of sport video broadcast. The aim of this module is the identification of athletes in the scene through the reading of names or numbers printed on their uniforms and to identify frames where athletes are visible. Using an adaptation of a previously published algorithm we extract text from individual frames and then read these candidates by means of an optical character recognizer (OCR). The OCR-ed text is then compared to an a-priori list of athletes' names (or numbers), to provide a presence score for each athlete. Text regions are subsequently tracked in following frames using a template matching technique. In this way blurred or distorted text, normally unreadable by the OCR, can also be exploited to provide a denser labelling of the video sequences.,
    2010

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