Wearable Structured Light System in Non-Rigid Configuration

Traditionally, structured light methods have been studied in rigid configurations. In these configurations the position and orientation between the light emitter and the camera are fixed and known beforehand. In this paper we break with this rigidness and present a new structured light system in non-rigid configuration. This system is composed by a wearable standard perspective camera and a simple laser emitter. Our non-rigid configuration permits free motion of the light emitter with respect to the camera. The point-based pattern emitted by the laser permits us to easily establish correspondences between the image from the camera and a virtual one generated from the light emitter. Using these correspondences, our method computes rotation and translation up to scale of the planes of the scene where the point pattern is projected and reconstructs them. This constitutes a very useful tool for navigation applications in indoor environments, which are mainly composed of planar surfaces

Detection and modelling of staircases using a wearable depth sensor

In this paper we deal with the perception task of a wearable navigation assistant. Specifically, we have focused on the detection of staircases because of the important role they play in indoor navigation due to the multi-floor reaching possibilities they bring and the lack of security they cause, specially for those who suffer from visual deficiencies. We use the depth sensing capacities of the modern RGB-D cameras to segment and classify the different elements that integrate the scene and then carry out the stair detection and modelling algorithm to retrieve all the information that might interest the user, i.e. the location and orientation of the staircase, the number of steps and the step dimensions. Experiments prove that the system is able to perform in real-time and works even under partial occlusions of the stairway

Non-central panorama indoor dataset

Omnidirectional images are one of the main sources of information for learning-based scene understanding algorithms. However, annotated datasets of omnidirectional images cannot keep the pace of these learning-based algorithms development. Among the different panoramas and in contrast to standard central ones, non-central panoramas provide geometrical information in the distortion of the image from which we can retrieve 3D information of the environment. However, due to the lack of commercial non-central devices, up until now there was no dataset of these kind of panoramas. In this data paper, we present the first dataset of non-central panoramas for indoor scene understanding. The dataset is composed of 2574 RGB non-central panoramas taken in around 650 different rooms. Each panorama has associated a depth map and annotations to obtain the layout of the room from the image as a structural edge map, list of corners in the image, the 3D corners of the room and the camera pose. The images are taken from photorealistic virtual environments and pixel-wise automatically annotated

Atlanta scaled layouts from non-central panoramas

In this work we present a novel approach for 3D layout recovery of indoor environments using a non-central acquisition system. From a single non-central panorama, full and scaled 3D lines can be independently recovered by geometry reasoning without additional nor scale assumptions. However, their sensitivity to noise and complex geometric modeling has led these panoramas and required algorithms being little investigated. Our new pipeline aims to extract the boundaries of the structural lines of an indoor environment with a neural network and exploit the properties of non-central projection systems in a new geometrical processing to recover scaled 3D layouts. The results of our experiments show that we improve state-of-the-art methods for layout recovery and line extraction in non-central projection systems. We completely solve the problem both in Manhattan and Atlanta environments, handling occlusions and retrieving the metric scale of the room without extra measurements. As far as the authors’ knowledge goes, our approach is the first work using deep learning on non-central panoramas and recovering scaled layouts from single panoramas

Preventive plan hamstring in football kid

El propósito de nuestro estudio es trabajar en un programa de prevención de lesiones en isquiotibiales en jóvenes futbolistas de la etapa infantil (13-14 años), realizando un pretest a todos los sujetos (4 grupos), aplicando un entrenamiento de ADM isquiotibial diferente, y volviendo a hacer un posterior postest transcurridas 10 semanas de entrenamientos, para comprobar qué grupo mejora más trasladando esas mejoras al entrenamiento específico. Para llevar a cabo nuestro estudio hemos requerido 44 jugadores de la categoría infantil. La muestra se clasificó por grupo trabajo por pareja (n1=13), trabajo en parejas + trabajo excéntrico (Hamstrings Nordics) (n2=10), trabajo SGA (n3=7) y trabajo SGA + trabajo excéntrico (Hamstrings Nordics) (n4=14), siendo cada grupo un equipo diferente. Los resultados obtenidos de este estudio son que con cualquier tipo de entrenamiento de ADM vamos a mejorar esta cualidad, sin grandes diferencias entre los diferentes grupos

Building an enhanced vocabulary of the robot environment with a ceiling pointing camera

Mobile robots are of great help for automatic monitoring tasks in different environments. One of the first tasks that needs to be addressed when creating these kinds of robotic systems is modeling the robot environment. This work proposes a pipeline to build an enhanced visual model of a robot environment indoors. Vision based recognition approaches frequently use quantized feature spaces, commonly known as Bag of Words (BoW) or vocabulary representations. A drawback using standard BoW approaches is that semantic information is not considered as a criteria to create the visual words. To solve this challenging task, this paper studies how to leverage the standard vocabulary construction process to obtain a more meaningful visual vocabulary of the robot work environment using image sequences. We take advantage of spatio-temporal constraints and prior knowledge about the position of the camera. The key contribution of our work is the definition of a new pipeline to create a model of the environment. This pipeline incorporates (1) tracking information to the process of vocabulary construction and (2) geometric cues to the appearance descriptors. Motivated by long term robotic applications, such as the aforementioned monitoring tasks, we focus on a configuration where the robot camera points to the ceiling, which captures more stable regions of the environment. The experimental validation shows how our vocabulary models the environment in more detail than standard vocabulary approaches, without loss of recognition performance. We show different robotic tasks that could benefit of the use of our visual vocabulary approach, such as place recognition or object discovery. For this validation, we use our publicly available data-set

Implementación de un sistema de escenarios futuros sobre el mapa de usos de suelo de Andalucía.

La Consejería de Medio Ambiente (CMA) ha puesto en marcha un estudio para la generación de cartografía prospectiva de usos de suelo en la Andalucía del siglo XXI. El objeto de este proyecto es explorar y analizar la posible evolución a medio-largo plazo de los usos del suelo y sus implicaciones ambientales, en un contexto de cambio global según diferentes escenarios. Los estudios prospectivos tales como, la construcción de escenarios, permiten iluminar la toma de decisiones. La distribución de los usos de suelo influye en el crecimiento y desarrollo de nuestra sociedad y representa un elemento importante para predecir los impactos ambientales. Actualmente la CMA dispone de una cartografía con los más elevados niveles de detalle y precisión espacial, que cumple los estándares cartográficos internacionales, y que cubre los últimos 50 años en la evolución de los usos del suelo en nuestra región. El poder anticipar, bajo diferentes supuestos de desarrollo socioeconómico, la evolución y la distribución de los usos del suelo en el futuro, supondría avanzar y complementar esta línea de trabajo. La integración de estos factores se ha llevado a cabo mediante autómatas celulares utilizados para modelar los cambios de uso y el desarrollo urbano.The Environmental Ministry of the Andalusian Regional Government has initiated a study to generate prospective mapping of land uses in Andalusia in the XXI century. The goal of this project is to explore and analyze medium to long- term land uses changes and their environmental implications according to different scenarios in the context of global change. Predicting land use change under such scenarios will provide valuable information to decision makers. The distribution of the land uses influences in the growth and development of our society and thus represents a crucial element to predict future environmental impacts. The Environmental Ministry of Andalusia currently has maps available that depict land use changes in the region over the past 50 years and contain the highest level of detail and spatial precision according to international cartographic standards. The power to predict the growth and distribution of future land uses under different assumptions of socioeconomic development will advance and complement this work. The integration of these factors is carried out based on cellular automata applied to model land use changes and urban development

Exploiting line metric reconstruction from non-central circular panoramas

In certain non-central imaging systems, straight lines are projected via a non-planar surface encapsulating the 4 degrees of freedom of the 3D line. Consequently the geometry of the 3D line can be recovered from a minimum of four image points. However, with classical non-central catadioptric systems there is not enough effective baseline for a practical implementation of the method. In this paper we propose a multi-camera system configuration resembling the circular panoramic model which results in a particular non-central projection allowing the stitching of a non-central panorama. From a single panorama we obtain well-conditioned 3D reconstruction of lines, which are specially interesting in texture-less scenarios. No previous information about the direction or arrangement of the lines in the scene is assumed. The proposed method is evaluated on both synthetic and real images

Effect of self-healing additions on the development of mechanical strength of cement paste

Important research efforts have been recently focused on the development of self-healing cement composites. The healing mechanism, implemented within the material, must be automatically initiated as soon as the first signs of damage appear at the micro-scale. For doing so, two different additions have been developed to incorporate them simultaneously into the cementitious matrix: silica microcapsules containing an epoxy sealing compound (CAP) and nanosilica particles functionalized with amine groups (NS). As a first step to the development of a self-healing concrete with these two additions, their pozzolanic activity has been measured by an accelerated test. The high values of fixed lime obtained at 28 days (85% for CAP, 93% for NS and 88% for a mix of them) suggest that they are suitable for construction materials’ applications. Furthermore, the behaviour of the additions in an ordinary Portland cement paste with 20 wt.% of commercial micro-silica has been studied, considering the partial substitution of micro-silica by CAP, NS and their mix. High values of compressive strength (>60 MPa) have been obtained in all cases after 28 days of hydration. However, while the addition of CAP induces a reduction of the compressive strength of the 24% with respect to the reference material, the addition of NS gives rise to a slight enhancement of the strength (5%) due to a pozzolanic reaction confirmed by X-ray diffraction data. Finally, in the presence of both CAP and NS, the beneficial effect of the nanosilica is counteracted by the microcapsules and a reduction of 28% is obtained for the compressive strength