A knowledge based framework to support active aging at home based environments

Information and Communication Technologies can support Active Aging strategies in a scenario like the Smart Home. This paper details a person centered distributed framework, called TALISMAN+, whose aim is to promote personal autonomy by taking advantage of knowledge based technologies, sensors networks, mobile devices and internet. The proposed solution can support an elderly person to keep living alone at his house without being obliged to move to a residential center. The framework is composed by five subsystems: a reasoning module that is able to take local decisions at home in order to support active aging, a biomedical variables telemonitorisation platform running on a mobile device, a hybrid reasoning middleware aimed to assess cardiovascular risk in a remote way, a private vision based sensor subsystem, and a secure telematics solution that guarantees confidentiality for personal information. TALISMAN+ framework deployment is being evaluated at a real environment like the Accessible Digital Home.

Active Optical Sensors for Tree Stem Detection and Classification in Nurseries.

Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a row of tree seedlings as a reference for each recorded sensor measurement. The field trials were conducted in a juvenile tree nursery with one-year-old grafted almond trees at Sierra Gold Nurseries, Yuba City, CA, United States. Through these tests and subsequent data processing, each sensor was individually evaluated to characterize their reliability, as well as their advantages and disadvantages for the proposed task. Test results indicated that 95.7% and 99.48% of the trees were successfully detected with the LIDAR and light curtain sensors, respectively. LIDAR correctly classified, between alive or dead tree states at a 93.75% success rate compared to 94.16% for the light curtain sensor. These results can help system designers select the most reliable sensor for the accurate detection and localization of each tree in a nursery, which might allow labor-intensive tasks, such as weeding, to be automated without damaging crops.

Metodología para ejecución y control de calidad para ortofotos, mediante combinación de sensor digital con LIDAR en zonas rurales

La utilización de una cámara fotogramétrica digital redunda en el aumento demostrable de calidad radiométrica debido a la mejor relación señal/ruido y a los 12 bits de resolución radiométrica por cada pixel de la imagen. Simultáneamente se consigue un notable ahorro de tiempo y coste gracias a la eliminación de las fases de revelado y escaneado de la película y al aumento de las horas de vuelo por día. De otra parte, el sistema láser aerotransportado (LIDAR - Light Detection and Ranging) es un sistema con un elevado rendimiento y rentabilidad para la captura de datos de elevaciones para generar un modelo digital del terreno (MDT) y también de los objetos sobre el terreno, permitiendo así alcanzar alta precisión y densidad de información. Tanto el sistema LIDAR como el sistema de cámara fotogramétrica digital se combinan con otras técnicas bien conocidas: el sistema de posicionamiento global (GPS - Global Positioning System) y la orientación de la unidad de medida inercial (IMU - Inertial Measure Units), que permiten reducir o eliminar el apoyo de campo y realizar la orientación directa de los sensores utilizando datos de efemérides precisas de los satélites. Combinando estas tecnologías, se va a proponer y poner en práctica una metodología para generación automática de ortofotos en países de América del Sur. Analizando la precisión de dichas ortofotos comparándolas con fuente de mayor exactitud y con las especificaciones técnicas del Plan Nacional de Ortofotografía Aérea (PNOA) se determinará la viabilidad de que dicha metodología se pueda aplicar a zonas rurales. ABSTRACT Using a digital photogrammetric camera results in a demonstrable increase of the radiometric quality due to a better improved signal/noise ratio and the radiometric resolution of 12 bits per pixel of the image. Simultaneously a significant saving of time and money is achieved thanks to the elimination of the developing and film scanning stages, as well as to the increase of flying hours per day. On the other hand, airborne laser system Light Detection and Ranging (LIDAR) is a system with high performance and yield for the acquisition of elevation data in order to generate a digital terrain model (DTM), as well as objects on the ground which allows to achieve high accuracy and data density. Both the LIDAR and the digital photogrammetric camera system are combined with other well known techniques: global positioning system (GPS) and inertial measurement unit (IMU) orientation, which are currently in a mature evolutionary stage, which allow to reduce and/or remove field support and perform a direct guidance of sensors using specific historic data from the satellites. By combining these technologies, a methodology for automatic generation of orthophotos in South American countries will be proposed and implemented. Analyzing the accuracy of these orthophotos comparing them with more accurate sources and technical specifications of the National Aerial Orthophoto (PNOA), the viability of whether this methodology should be applied to rural areas, will be determined.

Multi-sensor background subtraction by fusing multiple region-based probabilistic classifiers

In the recent years, the computer vision community has shown great interest on depth-based applications thanks to the performance and flexibility of the new generation of RGB-D imagery. In this paper, we present an efficient background subtraction algorithm based on the fusion of multiple region-based classifiers that processes depth and color data provided by RGB-D cameras. Foreground objects are detected by combining a region-based foreground prediction (based on depth data) with different background models (based on a Mixture of Gaussian algorithm) providing color and depth descriptions of the scene at pixel and region level. The information given by these modules is fused in a mixture of experts fashion to improve the foreground detection accuracy. The main contributions of the paper are the region-based models of both background and foreground, built from the depth and color data. The obtained results using different database sequences demonstrate that the proposed approach leads to a higher detection accuracy with respect to existing state-of-the-art techniques.

Multi-textured 3D humanoid reconstruction through passive and active automatic techniques = Reconstrucción de humanoides 3D multi-texturados mediante técnicas pasivas y activas automáticas

The proliferation of video games and other applications of computer graphics in everyday life demands a much easier way to create animatable virtual human characters. Traditionally, this has been the job of highly skilled artists and animators that painstakingly model, rig and animate their avatars, and usually have to tune them for each application and transmission/rendering platform. The emergence of virtual/mixed reality environments also calls for practical and costeffective ways to produce custom models of actual people. The purpose of the present dissertation is bringing 3D human scanning closer to the average user. For this, two different techniques are presented, one passive and one active. The first one is a fully automatic system for generating statically multi-textured avatars of real people captured with several standard cameras. Our system uses a state-of-the-art shape from silhouette technique to retrieve the shape of subject. However, to deal with the lack of detail that is common in the facial region for these kind of techniques, which do not handle concavities correctly, our system proposes an approach to improve the quality of this region. This face enhancement technique uses a generic facial model which is transformed according to the specific facial features of the subject. Moreover, this system features a novel technique for generating view-independent texture atlases computed from the original images. This static multi-texturing system yields a seamless texture atlas calculated by combining the color information from several photos. We suppress the color seams due to image misalignments and irregular lighting conditions that multi-texturing approaches typically suffer from, while minimizing the blurring effect introduced by color blending techniques. The second technique features a system to retrieve a fully animatable 3D model of a human using a commercial depth sensor. Differently to other approaches in the current state of the art, our system does not require the user to be completely still through the scanning process, and neither the depth sensor is moved around the subject to cover all its surface. Instead, the depth sensor remains static and the skeleton tracking information is used to compensate the user’s movements during the scanning stage. RESUMEN La popularización de videojuegos y otras aplicaciones de los gráficos por ordenador en el día a día requiere una manera más sencilla de crear modelos virtuales humanos animables. Tradicionalmente, estos modelos han sido creados por artistas profesionales que cuidadosamente los modelan y animan, y que tienen que adaptar específicamente para cada aplicación y plataforma de transmisión o visualización. La aparición de los entornos de realidad virtual/mixta aumenta incluso más la demanda de técnicas prácticas y baratas para producir modelos 3D representando personas reales. El objetivo de esta tesis es acercar el escaneo de humanos en 3D al usuario medio. Para ello, se presentan dos técnicas diferentes, una pasiva y una activa. La primera es un sistema automático para generar avatares multi-texturizados de personas reales mediante una serie de cámaras comunes. Nuestro sistema usa técnicas del estado del arte basadas en shape from silhouette para extraer la forma del sujeto a escanear. Sin embargo, este tipo de técnicas no gestiona las concavidades correctamente, por lo que nuestro sistema propone una manera de incrementar la calidad en una región del modelo que se ve especialmente afectada: la cara. Esta técnica de mejora facial usa un modelo 3D genérico de una cara y lo modifica según los rasgos faciales específicos del sujeto. Además, el sistema incluye una novedosa técnica para generar un atlas de textura a partir de las imágenes capturadas. Este sistema de multi-texturización consigue un atlas de textura sin transiciones abruptas de color gracias a su manera de mezclar la información de color de varias imágenes sobre cada triángulo. Todas las costuras y discontinuidades de color debidas a las condiciones de iluminación irregulares son eliminadas, minimizando el efecto de desenfoque de la interpolación que normalmente introducen este tipo de métodos. La segunda técnica presenta un sistema para conseguir un modelo humano 3D completamente animable utilizando un sensor de profundidad. A diferencia de otros métodos del estado de arte, nuestro sistema no requiere que el usuario esté completamente quieto durante el proceso de escaneado, ni mover el sensor alrededor del sujeto para cubrir toda su superficie. Por el contrario, el sensor se mantiene estático y el esqueleto virtual de la persona, que se va siguiendo durante el proceso, se utiliza para compensar sus movimientos durante el escaneado.

SoxR, a [2Fe-2S] transcription factor, is active only in its oxidized form.

SoxR protein is known to function both as a sensor and as a transcriptional activator for a superoxide response regulon in Escherichia coli. The activity of SoxR was tested by its ability to enable the transcription of its target gene, soxS, in vitro. The activity of the oxidized form was lost when its [2Fe-2S] clusters were reduced by dithionite under anaerobic conditions, and it was rapidly restored by autooxidation. This result is consistent with the hypothesis that induction of the regulon is effected by the univalent oxidation of the Fe-S centers of SoxR. In vivo, this oxidation may be caused by an alteration of the redox balance of electron chain intermediates that normally maintains soxR in an inactive, reduced state. Oxidized SoxR was about twice as effective as reduced SoxR in protecting the soxS operator from endonucleolytic cleavage. However, this difference could not account for a greater than 50-fold difference in their activities and therefore could not support a model in which oxidation activates SoxR by enabling it to bind to DNA. NADPH, ferredoxin, flavodoxin, or ferredoxin (flavodoxin):NADP+ reductase could not reduce SoxR directly in vitro at a measurable rate. The midpoint potential for SoxR was measured at -283 mV.

A molecular sensor system based on genetically engineered alkaline phosphatase.

Binding and signaling proteins based on Escherichia coli alkaline phosphatase (AP; EC 3.1.3.1) were designed for the detection of antibodies. Hybrid proteins were constructed by using wild-type AP and point mutants of AP [Asp-101 --> Ser (D101S) and Asp-153 --> Gly (D153G)]. The binding function of the hybrid proteins is provided by a peptide epitope inserted between amino acids 407 and 408 in AP. Binding of anti-epitope antibodies to the hybrid proteins modulates the enzyme activity of the hybrids; upon antibody binding, enzyme activity can increase to as much as 300% of the level of activity in the absence of antibody or can decrease as much as 40%, depending on the presence or absence of the point mutations in AP. The fact that modulation is altered from inhibition to activation by single amino acid changes in the active site of AP suggests that the mechanism for modulation is due to structural alterations upon antibody binding. Modulation is a general phenomenon. The properties of the system are demonstrated by using two epitopes, one from the V3 loop of human immunodeficiency virus type 1 gp120 protein and one from hepatitis C virus core protein, and corresponding monoclonal antibodies. The trend of modulation is consistent for all hybrids; those in wild-type AP are inhibited by antibody, while those in the AP mutants are activated by antibody. This demonstrates that modulation of enzyme activity of the AP-epitope hybrid proteins is not specific to either a particular epitope sequence or a particular antibody-epitope combination.

Three-dimensional planar object tracking with sub-pixel accuracy

Subpixel techniques are commonly used to increase the spatial resolution in tracking tasks. Object tracking with targets of known shape permits obtaining information about object position and orientation in the three-dimensional space. A proper selection of the target shape allows us to determine its position inside a plane and its angular and azimuthal orientation under certain limits. Our proposal is demonstrated both numerical and experimentally and provides an increase the accuracy of more than one order of magnitude compared to the nominal resolution of the sensor. The experiment has been performed with a high-speed camera, which simultaneously provides high spatial and temporal resolution, so it may be interesting for some applications where this kind of targets can be attached, such as vibration monitoring and structural analysis.

Traffic based energy consumption optimisation to improve the lifetime and performance of ad hoc wireless sensor networks

Ad hoc wireless sensor networks (WSNs) are formed from self-organising configurations of distributed, energy constrained, autonomous sensor nodes. The service lifetime of such sensor nodes depends on the power supply and the energy consumption, which is typically dominated by the communication subsystem. One of the key challenges in unlocking the potential of such data gathering sensor networks is conserving energy so as to maximize their post deployment active lifetime. This thesis described the research carried on the continual development of the novel energy efficient Optimised grids algorithm that increases the WSNs lifetime and improves on the QoS parameters yielding higher throughput, lower latency and jitter for next generation of WSNs. Based on the range and traffic relationship the novel Optimised grids algorithm provides a robust traffic dependent energy efficient grid size that minimises the cluster head energy consumption in each grid and balances the energy use throughout the network. Efficient spatial reusability allows the novel Optimised grids algorithm improves on network QoS parameters. The most important advantage of this model is that it can be applied to all one and two dimensional traffic scenarios where the traffic load may fluctuate due to sensor activities. During traffic fluctuations the novel Optimised grids algorithm can be used to re-optimise the wireless sensor network to bring further benefits in energy reduction and improvement in QoS parameters. As the idle energy becomes dominant at lower traffic loads, the new Sleep Optimised grids model incorporates the sleep energy and idle energy duty cycles that can be implemented to achieve further network lifetime gains in all wireless sensor network models. Another key advantage of the novel Optimised grids algorithm is that it can be implemented with existing energy saving protocols like GAF, LEACH, SMAC and TMAC to further enhance the network lifetimes and improve on QoS parameters. The novel Optimised grids algorithm does not interfere with these protocols, but creates an overlay to optimise the grids sizes and hence transmission range of wireless sensor nodes.

Interferometric sensor interrogation using an arrayed waveguide grating

We experimentally investigate the use of an arrayed waveguide grating (AWG) to interrogate interferometric sensors. A single broad-band light source is used to illuminate the system. Reflected spectral information is directed to an AWG with integral photodetectors providing 40 electrical outputs. We show that using the dual-wavelength technique we can measure the length of a Fabry-Perot cavity by determining the optical phase changes of the scanned interferometric pattern, which produced a maximum unambiguous range of 1440 mum with an active sensor and a maximum unambiguous range of 300 mum with the introduction of a second processing interferometer, which allows the sensor to be passive.

Interferometric sensor interrogation using an arrayed waveguide grating

We experimentally investigate the use of an arrayed waveguide grating (AWG) to interrogate interferometric sensors. A single broad-band light source is used to illuminate the system. Reflected spectral information is directed to an AWG with integral photodetectors providing 40 electrical outputs. We show that using the dual-wavelength technique we can measure the length of a Fabry-Pérot cavity by determining the optical phase changes of the scanned interferometric pattern, which produced a maximum unambiguous range of 1440 μm with an active sensor and a maximum unambiguous range of 300 μm with the introduction of a second processing interferometer, which allows the sensor to be passive. © 2005 IEEE.

Interferometric and fibre Bragg grating sensor interrogation using an arrayed waveguide grating

We investigate the use of an arrayed waveguide grating (AWG) to interrogate both fibre Bragg grating (FBG) and interferometric sensors. A broadband light source is used to illuminate both the FBG and interferometric sensors. Reflected spectral information is directed to an AWG with integral photodetectors providing 40 electrical outputs. To interrogate interferometric sensors we investigated the dual wavelength technique to measure the distance of a Fabry-Perot cavity, which produced a maximum unambiguous range of 1440μm with an active sensor. Three methods are described to interrogate FBG sensors. The first technique makes use of the reflected light intensity in an AWG channel passband from a narrow bandwidth grating, giving a usable range of 500με and a dynamic strain resolution of 96nε/√Hz at 30Hz. The second approach utilises wide gratings larger than the channel spacing of the AWG; by monitoring the intensity present in corresponding AWG channels an improved range of 1890με was achieved. The third method improves the dynamic range by utilising a heterodyne approach based on interferometric wavelength shift detection providing a dynamic strain resolution of 17nε/√Hz at 30Hz.

Resonant cavity time-division-multiplexed fiber Bragg grating sensor interrogator

The first resonant-cavity time-division-multiplexed (TDM) fiber Bragg grating sensor interrogation system is reported. This novel design uses a pulsed semiconductor optical amplifier in a cyclic manner to function as the optical source, amplifier, and modulator. Compatible with a range of standard wavelength detection techniques, this optically gated TDM system allows interrogation of low reflectivity "commodity" sensors spaced just 2 m apart, using a single active component. Results demonstrate an exceptional optical signal-to-noise ratio of 36 dB, a peak signal power of over +7 dBm, and no measurable crosstalk between sensors. Temperature tuning shows that the system is fully stable with a highly linear response. © 2004 IEEE.

Self-organising zooms for decentralised redundancy management in visual sensor networks

When visual sensor networks are composed of cameras which can adjust the zoom factor of their own lens, one must determine the optimal zoom levels for the cameras, for a given task. This gives rise to an important trade-off between the overlap of the different cameras’ fields of view, providing redundancy, and image quality. In an object tracking task, having multiple cameras observe the same area allows for quicker recovery, when a camera fails. In contrast having narrow zooms allow for a higher pixel count on regions of interest, leading to increased tracking confidence. In this paper we propose an approach for the self-organisation of redundancy in a distributed visual sensor network, based on decentralised multi-objective online learning using only local information to approximate the global state. We explore the impact of different zoom levels on these trade-offs, when tasking omnidirectional cameras, having perfect 360-degree view, with keeping track of a varying number of moving objects. We further show how employing decentralised reinforcement learning enables zoom configurations to be achieved dynamically at runtime according to an operator’s preference for maximising either the proportion of objects tracked, confidence associated with tracking, or redundancy in expectation of camera failure. We show that explicitly taking account of the level of overlap, even based only on local knowledge, improves resilience when cameras fail. Our results illustrate the trade-off between maintaining high confidence and object coverage, and maintaining redundancy, in anticipation of future failure. Our approach provides a fully tunable decentralised method for the self-organisation of redundancy in a changing environment, according to an operator’s preferences.