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Stefano Messelodi

Head of Unit
  • Phone: 0461314509
  • FBK Povo
Short bio

Stefano Messelodi was born in Arco (Italy) in 1961. He graduated in computer science from the University of Milan (Italy).  Since 1986 he is working in FBK (ITC-irst), Trento, Italy, where he coordinated the Technologies of Vision research unit till 2012. His research interests include text localization in scene, semantic image labelling and dynamic scene understanding. He served as a reviewer for several journals and conferences. He is a member of IEEE Society and International Association for Pattern Recognition.
He currently coordinates the research unit TeV.

Research interests
people re-identification text localization in scene document image analysis traffic analysis
  1. G. Cattoni; S. Messelodi; C. M. Modena,
    Vision-based bicycle/motorcycle classification with Support Vector Machines,
    Classification of vehicles plays an important role in a traffic monitoring system. In this paper we present a feature-based classifier, which can distinguish bicycles from motorcycles in real world traffic scenes.
    Basically, the algorithm extracts some visual features focusing on the region corresponding to the wheels of vehicle. It splits the problem into two sub-cases depending on the computed motion direction. The classification is performed by means of a non-linear Support Vector Machine. Tests lead to a successful classification rate of 93% on video sequences taken from different road junctions in an urban environment
  2. C. Andreatta; M. Lecca; S. Messelodi,
    Memory based object recognition in images,
    MEMORI is a system for the detection and recognition of objects, stored in a database, within digital images taken as an input. It aims to provide a content-based indexing scheme which exploits the semantic information contained in the images. Object detection is achieved by segmenting the input image using color and textural information, and grouping the obtained regions by analyzing their adjacency relationships and their visual similarity to the objects in the database. The database is the memory of the system and consists of objects depicted by a set of different views, each of them described by a feature vector encoding color, texture and shape information. The same description is computed for the region groups candidated to represent an object and is compared, by an object classifier, with the database objects. The final result is a number of image regions each associated to one or more object classes with a confidence score,
  3. Michele Zanin; Stefano Messelodi; Carla Maria Modena,
    Mantova, Italy,
    17/09/2003 - 19/09/2003,
  4. Stefano Messelodi; Carla Maria Modena,
    Extraction of Polygonal Frames from Color Documents for Page Decomposition,
    Graphic accents are often used in the design of complex documents in order to emphasize particular information. Words or illustrations are surrounded by a border line or highlighted by means of a colored background. This paper presents a method for the automatic extraction of document layout items, called {\em frames}, having polygonal shape and/or a uniformly colored background. As frames break the normal text flow, frame detection is a fundamental step of the document layout analysis in a document understanding system. The presented method relies on a color region growing algorithm and on straight edges extractor. The shape analysis of the obtained regions permits to localize the frames with their attributes. In order to reduce computation time and to return only specific patterns, the method exploits information about a model of the frames to be detected such as shape, skew or size, possibly supplied by the user or depending on the specific document class. The presented algorithm is assessed on a page databases containing more than 675 framed items. The evaluation is based on a novel tree matching method that takes into account the frame hierarchy and their shape,
  5. Stefano Messelodi; Carla Maria Modena,
    Low Level Processing of Color Document Images,
    Color is an extremely useful cue that is used for adding information in documents. Document image understanding takes advantage from the implicit or explicit knowledge on the use of color in document production. This knowledge has to be exploited starting from the low level tasks. In this report low level image processing functions, particularly suited for the processing of scanned color documents images, are considered and analyzed in a brief survey. Extensions of some edge detection and edge preserving smoothing algorithms to the color domain are introduced,
  6. Stefano Messelodi; Carla Maria Modena,
    vol. 32,
    n. 5,
    , pp. 789 -
  7. Stefano Messelodi; Carla Maria Modena,
    10th International Workshop on Database & Expert Systems Applications,
    , pp. 534-
    , (10th International Workshop on Database & Expert Systems Applications,
    Florence, Italy,
    30/08/1999 - 03/09/1999)
  8. Nicola Veneri; Stefano Messelodi; Bruno Crespi,
    A Memory based Approach to Sensory Motor Coordination,
    vol. 10,
    n. 5/6,
    , pp. 269 -
  9. Roldano Cattoni; Tarcisio Coianiz; Stefano Messelodi; Carla Maria Modena,
    Document Image Understanding (DIU) is an interesting research area with a large variety of challenging applications. Researchers have worked from decades on this topic, as witnessed by the scientific literature. The main purpose of the present report is to describe the current status of DIU with particular attention to two subprocesses: document skew angle estimation and page decomposition. Several algorithms proposed in the literature are synthetically described. They are included in a novel classification scheme. Some methods proposed for the evaluation of page decomposition algorithms are described. Critical discussions are reported about the current status of the field and about the open problems. Some considerations about the logical layout analysis are also reported.,
  10. Carla Maria Modena; Stefano Messelodi,
    Progetto CODICE*: Alcune considerazioni sulle modalità di valutazione del sistema,
    Queste note raccolgono alcune considerazioni relative alla definizione delle modalità di valutazione del sistema di analisi ed interpretazione di documenti complessi in via di sviluppo nell’ambito del progetto CODICE. Viene messo in evidenza che la possibilità di definire metodi di valutazione generali è attuabile solo per alcune sottoparti del sistema se non per specifiche procedure, mentre la definizione di una validazione globale richiede che sia fissato lo scenario applicativo,