M. Lo Brutto
University of Palermo
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Publication
Featured researches published by M. Lo Brutto.
International Journal of Heritage in the Digital Era | 2012
M. Lo Brutto; Paola Meli
In archaeological Cultural Heritage study 3D modelling has become a very useful process to obtain indispensable data for documentation and visualization. Nowadays the continuous request to achieve photorealistic 3D models has led to testing different techniques and methodologies to speed up both data acquisition and the data processing phase. There are many examples of surveys conducted with the use of range-based and image-based techniques, but, in the last few years, the scientific research has been increasingly moving towards automatic procedures using Computer Vision approach to reduce time during data processing. Computer Vision approach offers a great opportunity for archaeological survey since it can be very easily used by existing Computer Vision interfaces such as 3D web services and open source or low cost software. The aim of this work is to evaluate the performance offered by Computer Vision interfaces for 3D survey of archaeological ruins using some 3D web-service tools and a low cost softwar...
International Journal of Heritage in the Digital Era | 2012
M. Lo Brutto; A. Borruso; A. D'Argenio
The use of UAV systems for surveying archaeological sites is becoming progressively more common due to the considerable potential in terms of rapidity of survey, costs and accuracy. The paper presents the first results of the photogrammetric survey of the archaeological site of Himera in Sicily (Italy) using by UAV systems. A complete documentation of the site through the production of a DSM and an ortho image were carried out. The research further evaluated two different image processing workflows: a typical photogrammetric approach and a computer vision approach. An ortho image of the archaeological site with a very high resolution was obtained.
PROCEEDINGS OF SPIE, THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING | 2017
Claudia Pipitone; Antonino Maltese; Gino Dardanelli; Fulvio Capodici; M. Lo Brutto; G. La Loggia
The matching between reservoirs’ water edge and digital elevation model’s (DEM) contour lines allowed determining the water level at the acquisition date of satellite images. A preliminary study was conducted on the Castello dam (Magazzolo Lake), between Alessandria della Rocca and Bivona (Agrigento, south-Italy). The accuracy assessment of the technique was than evaluated from the comparison between classified and reference objects using similarity metrics about the shape, theme, edge and position, through the plugin STEP of open source software GIS. Moreover, an independent GIS technique was implemented to evaluate the water level, based on a distances’ array between existing contour lines and nodes extracted from vectorised classification images. Results have shown the potentiality of the techniques when applied on an ideal case; advantages and disadvantages when the images are characterized by clear sky, and limits when images are acquired during not ideal atmospheric conditions.
3D-ARCH 2007: "Virtual Reconstruction and Visualization of Complex Architectures" | 2007
Fabrizio Agnello; M. Lo Brutto
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2012
M. Lo Brutto; M. Spera
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2017
M. Lo Brutto; R. Sciortino; Alessandra Garraffa
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2017
M. Lo Brutto; Gino Dardanelli; D. Ebolese; G. Milazzo; Claudia Pipitone; R. Sciortino
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2018
D. Ebolese; Gino Dardanelli; M. Lo Brutto; R. Sciortino
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2018
M. Lo Brutto; D. Ebolese; Gino Dardanelli
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2017
D. Ebolese; M. Lo Brutto; A. Burgio