Land cover information is a fundamental parameter in a wide range of applications like urban growth, land degradation, climate change, food security, environmental sustainability, etc. In this context, remote sensing satellites can provide valuable data to allow the generation of thematic maps. On the other hand, the recent availability of hyperspectral sensors on board aircrafts and drones offers an opportunity to improve the resolution and accuracy of land cover maps. In island territories, where land is usually a scarce resource, the need of very high spatial resolution (VHR) is essential. In this context, we have generated VHR land cover maps using multispectral Worldview data and hyperspectral airborne CASI information. In particular, after corrections and pansharpening enhancements, we have analyzed pixel-based and object-based classification approaches using different input band combinations. We have compared the performance when using multispectral or hyperspectral imagery and its robustness depending on the quality of the training samples considered.

Human hand motion and shape sensing is an area of high interest in medical communities and for human interaction researchers. Measurement of small hand movements could help professionals to quantize the stage of conditions like Parkinson's Disease (PD) and Essential Tremor (ET). Similar data is also useful for designers of human interaction algorithms to infer information about hand pose and gesture recognition. In this paper we present a structured light sensor capable of measuring hand shape and color at 121 FPS. Our algorithm uses a novel structured light method developed by us, called Chebyshev Phase Shifting (CPS). This method uses a digital projector and a camera to create high-resolution color 3D models from sequences of color images. We show how to encode CPS patterns in three RGB images for a reduced acquisition time, enabling high speed capture. We have built a prototype to measure rapid trembling hands. Our results show our prototype accurately captures fast tremors similar to those of PD patients. Color 3D model sequences recorded at high speed with our sensor will be used to study hand kinematic properties in a future.

In this paper, we present a novel computational puzzle solver for square-piece image jigsaw puzzles with no prior information such as piece orientation, anchor pieces or resulting dimension of the puzzle. By "piece" we mean a square dxd block of pixels, where we investigate pieces as small as 7x7 pixels. To reconstruct such challenging puzzles, we aim to search for piece configurations which maximize the size of consensus (i.e. grid or loop) configurations which represent a geometric consensus or agreement among pieces. Pieces are considered for addition to the existing assemblies if these pieces increase the size of the consensus configurations. In contrast to previous puzzle solvers which goal for assemblies maximizing compatibility measures between all pairs of pieces and thus depend heavily on the pairwise compatibility measure used, our new approach reduces the dependency on the pairwise compatibility measures which become increasingly uninformative at small scales and instead exploits geometric agreement among pieces. Our contribution also includes an improved pairwise compatibility measure which exploits directional derivative information along adjoining boundaries of the pieces. For the challenging unknown orientation piece puzzles where the size of pieces is small, we reduce assembly error by up to 75% compared with previous algorithms for standard datasets.

Many mobile collaborative applications use resource positioning to provide services to end-users. Depending on the features of the collaboration activity to be supported, some positioning methods are more suitable than others. Despite ample research in this area, it is not clear which positioning method is more appropriate to support a particular collaboration activity. This paper presents a survey of positioning methods that can be used to support mobile collaboration. It also characterizes and compares these methods in order to determine which ones are more suitable, depending on the type of activity to be supported. This information helps software designers make this decision when they are conceiving a new mobile collaborative system.

We introduce Embedded PS, a new robust and accurate phase shifting algorithm for 3D scanning. The method projects only high frequency sinusoidal patterns in order to reduce errors due to global illumination effects, such as subsurface scattering and interreflections. The frequency set for the projected patterns is specially designed so that our algorithm can extract a set of embedded low frequency sinusoidals with simple math. All the signals, patterns high and embedded low frequencies, are used with temporal phase unwrapping to compute absolute phase values in closed-form, without quantization or approximation via LUT, resulting in fast computation. The absolute phases provide correspondences from projector to camera pixels which enable to recover 3D points using optical triangulation. The algorithm estimates multiple absolute phase values per pixel which are combined to reduce measurement noise while preserving fine details. We prove that embedded periodic signals can be recovered from any periodic signal, not just sinusoidal signals, which may result in further improvements for other 3D imaging methods. Several experiments are presented showing that our algorithm produces more robust and accurate 3D scanning results than state-of-the-art methods for challenging surface materials, with an equal or smaller number of projected patterns and at lower computational cost.

Knowing the position of a device at a given time is fundamental to provide services tailored to the current user location. However, not all devices are able to perform positioning by their own, even when positioning systems are available in the environment where the user is located. This article presents a context-aware positioning model that allows devices participating in mobile ad-hoc networks, to sense their context and exchange positioning information with their peers. Thus, nodes knowing their own position could share it with their neighbors, allowing the latter to perform positioning. We discuss the performance of the model in a simulated mobile outdoor environment, populated with different types of devices. Our experiment shows that nodes without positioning capabilities are able estimate their position, although with reduced accuracy compared to those using a direct positioning strategy, such as GPS.

Various Structured Light (SL) methods are used to capture 3D range images, where a number of binary or continuous light patterns are sequentially projected onto a scene of interest, while a digital camera captures images of the illuminated scene. All existing SL methods require the projector and camera to be hardware or software synchronized, with one image captured per projected pattern. A 3D range image is computed from the captured images. The two synchronization methods have disadvantages, which limit the use of SL methods to niche industrial and low quality consumer applications. Unsynchronized Structured Light (USL) is a novel SL method which does not require synchronization of pattern projection and image capture. The light patterns are projected and the images are captured independently, at constant, but possibly different, frame rates. USL synthesizes new binary images as would be decoded from the images captured by a camera synchronized to the projector, reducing the subsequent computation to standard SL. USL works both with global and rolling shutter cameras. USL enables most burst-mode-capable cameras, such as modern smartphones, tablets, DSLRs, and point-and-shoots, to function as high quality 3D snapshot cameras. Beyond the software, which can run in the devices, a separate SL Flash, able to project the sequence of patterns cyclically, during the acquisition time, is needed to enable the functionality.

Left to their own devices, student project teams often divide work along gender-stereotypical lines, leading to differentiated learning experiences and, the literature suggests, differences in self-confidence and persistence. Colleagues teaching a first-semester design course previously introduced an intervention that largely mitigates gender-stereotypical task allocation in that course. In the present study, we demonstrate modest evidence that the impact of this intervention persists into subsequent coursework, suggesting that it may be possible to persistently shift student behaviors away from gender-stereotypical defaults, in turn improving self-confidence, persistence, and outcomes.

This article presents a study on the nodes positioning confidence in mobile collaborative scenarios. The confidence of nodes positioning is an indicator that allows providing appropriate services and information to mobile users. In mobile ad-hoc networks, nodes with positioning capabilities could share their position with their neighbors in order to allow these latter to determine their own location collaboratively and increasing their positioning confidence. We study the fluctuation of this confidence in mobile scenarios populated by nodes with and without positioning capabilities. We analyze the effect of changing the maximum communication range of the nodes, the amount of nodes with positioning capabilities present in the environment. We also studied the impact that produces the degree of nodes mobility. The findings of this study are presented and discussed.

The widespread availability of smartphones with wireless communication and geo-positioning capabilities has open new opportunities to services for casual passersby, e.g. the delivery of advertising when they visit a certain area. Typically such messages are delivered to cellular phones, consuming thus part of the energy of these devices. Since these devices are constrained in battery-energy, disseminating messages using little energy represents a challenge for designers of this type of solutions. This paper presents a study based on simulations that intends to identify good strategies to irradiate messages collaboratively, minimizing the energy consumption in the devices involved in the information exchange. The simulation results show that the best irradiation strategy will depend on the number of devices in the area to be irradiated. Moreover, such a strategy will have more influence if the devices are dispersed. These findings should help designers of mobile collaborative applications based on messages irradiation, to identify the best dissemination strategy depending on the current network context.