Analysis of panoramio photo tags in order to extract land use information

In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

Using social semantic knowledge to improve annotations in personal photo collections

Instituto Politécnico de Lisboa (IPL) e Instituto Superior de Engenharia de Lisboa (ISEL)apoio concedido pela bolsa SPRH/PROTEC/67580/2010, que apoiou parcialmente este trabalho

PHOTO STORE : Galeria virtual d'imatges

Ofereix a l'usuari la possibilitat de crear la seva pròpia galeria virtual d'imatges, i de classificar-les en àlbums dividits en categories per oferir una catalogació molt més específica. Els àlbums els subdividim públics per aque qualsevol visitant del web (registrat o no) pugui tenir la possibilitat d'accedir-hi,visualitzar i imprimir les fotos; o privats per a l'ús exclusiu de l'usuari que els publica.

Large-Area Photo-Mosaics Using Global Alignment and Navigation Data

Seafloor imagery is a rich source of data for the study of biological and geological processes. Among several applications, still images of the ocean floor can be used to build image composites referred to as photo-mosaics. Photo-mosaics provide a wide-area visual representation of the benthos, and enable applications as diverse as geological surveys, mapping and detection of temporal changes in the morphology of biodiversity. We present an approach for creating globally aligned photo-mosaics using 3D position estimates provided by navigation sensors available in deep water surveys. Without image registration, such navigation data does not provide enough accuracy to produce useful composite images. Results from a challenging data set of the Lucky Strike vent field at the Mid Atlantic Ridge are reported

Selección automática de imágenes. Photo- Storytelling

En este proyecto se estudia como generar un resumen de una colección de fotografías seleccionándolas automáticamente.Se construye un sistema capaz de permitir a un usuario subir una colección de imágenes a una plataforma web, que estás sean procesadas y posteriormente darle la opción de generar un resumen automático de su colección personal.Realizar la selección automática de imágenes es una tarea muy compleja debido a todos los factores a tener en cuenta a la hora de escogerlas. Eventos temporales, estética de las imágenes, personajes que deben o no aparecer en la selección son algunos de los factores importantes y que hay que tener muy en cuenta a la hora de realizar la selección automática.En este proyecto veremos cómo se ha construido el sistema, cómo se ha implementado el algoritmo de selección automática y las mejoras que se han llevado a cabo para mejorarlo en precisión y tiempo de ejecución.Para la evaluación del algoritmo implementado se han realizado pruebas con usuarios que nos han permitido detectar algunos de los problemas del algoritmo.Finalmente, se presentan las conclusiones y el trabajo futuro.

Proteomics of methylene blue photo-treated plasma before and after removal of the dye by an absorbent filter.

Methylene blue (MB) and light are used for virus inactivation of plasma for transfusion. However, the presence of MB has been the subject of concern, and efforts have been made to efficiently remove the dye after photo-treatment. For this study, plasma was collected by apheresis from 10 donors (group A), then treated using the MacoPharma THERAFLEX procedure (MB; 1 microM, and light exposure; 180 J/cm(2)) (group B), and finally filtered in order to remove the dye (group C). Proteins were analyzed by two-dimensional electrophoresis, and peptides showing modifications were characterized by mass spectrometry. Clottable and antigenic fibrinogen levels, as well as fibrin polymerization time were measured. Analyses of the gels focused on a region corresponding to pI between 4.5 and 6.5, and M(r) from 7000 to 58 000. In this area, 387 +/- 47 spots matched, and four of these spots presented significant modifications. They corresponded to changes of the gamma-chain of fibrinogen, of transthyretin, and of apolipoprotein A-I, respectively. A decrease of clottable fibrinogen and a prolongation of fibrin polymerization time were observed in groups B and C. Removal of MB by filtration was not responsible for additional protein alterations. The effect of over-treatment of plasma by very high concentrations of MB (50 microM) in association with prolonged light exposure (3 h) was also analyzed, and showed complex alterations of most of the plasma proteins, including fibrinogen gamma-chain, transthyretin, and apolipoprotein A-I. Our data indicates that MB treatment at high concentration and prolonged illumination severely injure plasma proteins. By contrast, at the MB concentration used to inactivate viruses, damages are apparently very restricted.