This paper describes a methodology to extract a consistent human settlement extent layer using Landsat data and its implementation in the Google Earth Engine platform. The approach allows the extraction of human settlement extents by means of the existing Landsat 5 and 7 data sets, allowing to check their evolution at 30-m spatial resolution. Since human settlements are the main proxy to people geographical distribution and to building locations, this layer may serve as a mean to disaggregate people/building counts at the regional/national level. The approach is tested in several parts of the world against existing ground truth data at the same spatial resolution in Brazil and China, as well as against extents manually extracted from VHR data in three different geographical areas: 1) Brazil; 2) South East China; and 3) Indonesia.Index Terms-Global mapping, Landsat, normalized difference spectral vector (NDSV), urban remote sensing.

In recent years, UV-induced fluorescence (UVIFL) photography has proven to be very effective when studying the surface of historical musical instruments, such as violins. This technique makes it possible to highlight superficial details not clearly perceptible with visible light (e.g., retouchings, superficial distribution of varnishes, or wear). The data retrieved are also an important guide for further noninvasive spectroscopic analyses used when the chemical composition of the surface needs to be investigated. However, UVIFL imagery interpretation of a historical violin is no trivial task. In fact, constant playing and the multiple restorations over the centuries have produced very complex surfaces. This work presents an automatic tool designed to facilitate this kind of analysis. Using a quantized histogram in HSV color space, the distribution of the main fluorescence colors on an instrument’s surface can be highlighted, recurrence of the same color in different areas of the same violin can be detected, or different violins can be compared. UVIFL images of seven Stradivarius violins kept in the Museo del Violino in Cremona, Italy, were used as a test set. The results achieved endorse the validity of the proposed approach.

In the present work, we had the opportunity to study the coating systems of three different coeval violins, namely “Spagnoletti”, “Stauffer”, and “Principe Doria”, made by Giuseppe Guarneri “del Gesù” in 1734. These three violins were non-invasively investigated by reflection Fourier transform infrared spectroscopy and X-ray fluorescence. These two techniques were combined for the first time with a 3D laser scanner. The analytical campaign enabled the characterization of the materials and their distribution within the stratigraphy, mainly composed of varnish and, when present, of a proteinaceous ground coat. Some restoration materials were also identified, suggesting the application of different maintenance treatments undertaken during their history. The preliminary information about morphological and geometrical differences between the three coeval violins were acquired through the 3D laser scanner in order to observe similarities and differences in the design features among the three violins.

Hand detection and gesture recognition are two of the most studied topics in human-computer interaction (HCI). The increasing availability of sensors able to provide real-time depth measurements, such as time-of-flight cameras or the more recent Kinect, has helped researchers to find more and more efficient solutions for these issues. With the main aim to implement effective gesture-based interaction systems, this study presents an approach to hand detection and tracking that exploits two different video streams: the depth one and the colour one. Both hand and gesture recognition are based only on geometrical and colour constraints, and no learning phase is needed. The use of a Kalman filter to track hands guarantees system robustness also in presence of many persons in the scene. The entire procedure is designed to maintain a low computational cost and is optimised to efficiently execute HCI tasks. As use cases two common applications are described: a virtual keyboard and a three-dimensional object manipulation virtual environment. These applications have been tested with a representative sample of non-trained users to assess the usability and flexibility of the system.

Abstract. The number of systems exploiting Time-of-Flight (ToF) cameras for gesture recognition has greatly increased in the last years, confirming a very positive trend of this technology within the field of Human-Computer Interaction. In this work we present a new kind of application for the interaction with a virtual keyboard which is based on the use of an ordinary RGB webcam and a ToF camera. Our approach can be subdivided into two steps: firstly a segmentation of the entire body of the user is achieved exploiting only the ToF data; then the extraction of hands and head is obtained applying color information on the retrieved clusters. The final tracking step, based on the Kalman filter, is able to recognize the chosen hand also in presence of a second hand or the head. Tests, carried out with users of different ages, showed interesting results and a quick learning curve.