Retinal ganglion cell software and FPGA model implementation for object detection and tracking

This paper describes the software and FPGA implementation of a Retinal Ganglion Cell model which detects moving objects. It is shown how this processing, in conjunction with a Dynamic Vision Sensor as its input, can be used to extrapolate information about object position. Software-wise, a system based on an array of these of RGCs has been developed in order to obtain up to two trackers. These can track objects in a scene, from a still observer, and get inhibited when saccadic camera motion happens. The entire processing takes on average 1000 ns/event. A simplified version of this mechanism, with a mean latency of 330 ns/event, at 50 MHz, has also been implemented in a Spartan6 FPGA.European Commission FP7-ICT-600954Ministerio de Economía y Competitividad TEC2012-37868-C04-02Junta de Andalucía P12-TIC-130

Live Demonstration: Retinal ganglion cell software and FPGA implementation for object detection and tracking

This demonstration shows how object detection and tracking are possible thanks to a new implementation which takes inspiration from the visual processing of a particular type of ganglion cell in the retina

Neuromorphic Approach Sensitivity Cell Modeling and FPGA Implementation

Neuromorphic engineering takes inspiration from biology to solve engineering problems using the organizing principles of biological neural computation. This field has demonstrated success in sensor based applications (vision and audition) as well in cognition and actuators. This paper is focused on mimicking an interesting functionality of the retina that is computed by one type of Retinal Ganglion Cell (RGC). It is the early detection of approaching (expanding) dark objects. This paper presents the software and hardware logic FPGA implementation of this approach sensitivity cell. It can be used in later cognition layers as an attention mechanism. The input of this hardware modeled cell comes from an asynchronous spiking Dynamic Vision Sensor, which leads to an end-to-end event based processing system. The software model has been developed in Java, and computed with an average processing time per event of 370 ns on a NUC embedded computer. The output firing rate for an approaching object depends on the cell parameters that represent the needed number of input events to reach the firing threshold. For the hardware implementation on a Spartan6 FPGA, the processing time is reduced to 160 ns/event with the clock running at 50 MHz.Ministerio de Economía y Competitividad TEC2016-77785-PUnión Europea FP7-ICT-60095

Meta-analysis of the effects of soil properties, site factors and experimental conditions on solute transport

Preferential flow is a widespread phenomenon that is known to strongly affect solute transport in soil, but our understanding and knowledge is still poor of the site factors and soil properties that promote it. To investigate these relationships, we assembled a database from the peer-reviewed literature containing information on 733 breakthrough curve experiments under steady-state flow conditions. Most of the collected experiments (585 of the 733 datasets) had been conducted on undisturbed soil columns, although some experiments on repacked soil, clean sands, and glass beads were also included. In addition to the apparent dispersivity, we focused our attention on three indicators of preferential solute transport: namely the 5%-arrival time, the holdback factor, and the ratio of piston-flow and average transport velocities. Our results suggest that, in contrast to the 5%-arrival time and the holdback factor, the piston-flow to transport velocity ratio is not related to preferential macropore transport but rather to the exclusion or retardation of the applied tracer. Confirming that the apparent longitudinal dispersivity is positively correlated with the travel distance of the tracer, our results also illustrate that this relationship is refined if the normalized 5%-tracer arrival time is also taken into account. In particular, we found that the degree of preferential solute transport increases with apparent dispersivity and decreases with travel distance. A similar but weaker relationship was observed between apparent dispersivity, 5%-tracer arrival time, and lateral observation scale, such that the degree of preferential transport increases with lateral observation scale. However, we also found that the travel distance and the lateral observation scale in the investigated dataset are correlated, which makes it difficult to distinguish their influence on these transport characteristics. We also found that the strength of preferential transport increased at larger flow rates and water saturations, which suggests that macropore flow was a more important flow mechanism than heterogeneous flow in the soil matrix. Nevertheless, our data show that heterogeneous flow in the soil matrix also occasionally leads to strong preferential transport. Furthermore, we show that preferential solute transport under steady-state flow depends on soil texture in a threshold-like manner: moderate to strong preferential transport was found to occur only for undisturbed soils that contain more than 8% clay. Preferential flow characteristics were also absent for columns filled with glass beads, clean sands, or sieved soil. No clear effect of land use on the pattern of solute transport could be discerned, probably because the available dataset was too small and too strongly affected by cross-correlations with experimental conditions. Our results suggest that, in developing pedotransfer functions for solute transport properties of soils, it is critically important to account for travel distance, lateral observation scale, and water flow rate and saturation

Event Guided Depth Sensing

Active depth sensors like structured light, lidar, and time-of-flight systems sample the depth of the entire scene uniformly at a fixed scan rate. This leads to limited spatiotemporal resolution where redundant static information is over-sampled and precious motion information might be under-sampled. In this paper, we present an efficient bio-inspired event-camera-driven depth estimation algorithm. In our approach, we dynamically illuminate areas of interest densely, depending on the scene activity detected by the event camera, and sparsely illuminate areas in the field of view with no motion. The depth estimation is achieved by an event-based structured light system consisting of a laser point projector coupled with a second event-based sensor tuned to detect the reflection of the laser from the scene. We show the feasibility of our approach in a simulated autonomous driving scenario and real indoor sequences using our prototype. We show that, in natural scenes like autonomous driving and indoor environments, moving edges correspond to less than 10% of the scene on average. Thus our setup requires the sensor to scan only 10% of the scene, which could lead to almost 90% less power consumption by the illumination source. While we present the evaluation and proof-of-concept for an event-based structured-light system, the ideas presented here are applicable for a wide range of depth sensing modalities like LIDAR, time-of-flight, and standard stereo

Event Guided Depth Sensing

Active depth sensors like structured light, lidar, and time-of-flight systems sample the depth of the entire scene uniformly at a fixed scan rate. This leads to limited spatiotemporal resolution where redundant static information is over-sampled and precious motion information might be under-sampled. In this paper, we present an efficient bio-inspired event-camera-driven depth estimation algorithm. In our approach, we dynamically illuminate areas of interest densely, depending on the scene activity detected by the event camera, and sparsely illuminate areas in the field of view with no motion. The depth estimation is achieved by an event-based structured light system consisting of a laser point projector coupled with a second event-based sensor tuned to detect the reflection of the laser from the scene. We show the feasibility of our approach in a simulated autonomous driving scenario and real indoor sequences using our prototype. We show that, in natural scenes like autonomous driving and indoor environments, moving edges correspond to less than 10% of the scene on average. Thus our setup requires the sensor to scan only 10% of the scene, which could lead to almost 90% less power consumption by the illumination source. While we present the evaluation and proof-of-concept for an event-based structured-light system, the ideas presented here are applicable for a wide range of depth sensing modalities like LIDAR, time-of-flight, and standard stereo

Event-based Shape from Polarization

State-of-the-art solutions for Shape-from-Polarization (SfP) suffer from a speed-resolution tradeoff: they either sacrifice the number of polarization angles measured or necessitate lengthy acquisition times due to framerate constraints, thus compromising either accuracy or latency. We tackle this tradeoff using event cameras. Event cameras operate at microseconds resolution with negligible motion blur, and output a continuous stream of events that precisely measures how light changes over time asynchronously. We propose a setup that consists of a linear polarizer rotating at high-speeds in front of an event camera. Our method uses the continuous event stream caused by the rotation to reconstruct relative intensities at multiple polarizer angles. Experiments demonstrate that our method outperforms physics-based baselines using frames, reducing the MAE by 25% in synthetic and real-world dataset. In the real world, we observe, however, that the challenging conditions (i.e., when few events are generated) harm the performance of physics-based solutions. To overcome this, we propose a learning-based approach that learns to estimate surface normals even at low event-rates, improving the physics-based approach by 52% on the real world dataset. The proposed system achieves an acquisition speed equivalent to 50 fps (>twice the framerate of the commercial polarization sensor) while retaining the spatial resolution of 1MP. Our evaluation is based on the first large-scale dataset for event-based SfPComment: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, 202

Influencia de la concentración de nutrientes y la herviboría sobre la estructura y la función de una comunidad algal

Un mismo conjunto de algas puede generar diferentes ensamblados finales estables en función del ambiente (lago, laguna, etc.) en que se desarrollen. En este trabajo se pretende averiguar qué mecanismos están afectando simultáneamente al conjunto de especies para que se produzca una selección de ellas apropiada a cada ambiente acuático, y cómo la variabilidad de la respuesta se ve reflejada en la estructura y función de la comunidad (biomasa total, fotosíntesis y respiración). Se ha ensayado la formación de una comunidad algal a partir de la disposición simultánea de 8 especies de algas cosmopolitas de agua dulce de morfología bien distinta (Cosmarium contractum, Cryptomonas ovata, Euglena gracilis, Limnothrix redekei, Monoraphidium contortum, Pediastrum tetras, Planktothrix agardhii y Scenedesmus acutus) en distintos tipos de medio de cultivo. Los tratamientos han sido cuatro: mayor y menor concentración de nutrientes (N y P) y presencia o no de Daphnia magna, Keratella cochlearis y Brachionus calicyflorus. Se han ensayado, además, sistemas de competencia entre algas y se ha averiguado la viabilidad de estas especies como inóculos tras un período de senescencia. La presencia de herbívoros (depredación) y la concentración de nutrientes (competencia), son los mecanismos que aislada o sin enérgicamente afectan al ensamblado de microalgas determinando diferentes estados alternativos desde un mismo conjunto de microalgas. Pero el efecto de estos mecanismos es a su vez diferente en función de las propiedades de las microalgas implicadas como son su tamaño, su tasa de crecimiento y la viabilidad de cada especie como inóculo. La presencia de herbívoros y la oligotrofia reducen la biomasa de productores primarios pero aumentan la diversidad relajando la competencia y aumentando la incertidumbre sobre el final alcanzado. Se demuestra además que las variaciones en la estructura de la comunidad se reflejan directamente en su función, afectando en última instancia a la producción primaria y la respiración.The same pool of algae can generate different final stable assemblages depending on the environment (lake, lagoon, etc.) where they develop. In this work we attempt to ascertain the mechanisms that simultaneously affect the species to appropriately select them for each aquatic environment, and how the variability in the response is reflected in the community structure and function (total biomass, photosynthesis and respiration). An algal community has been formed assembling 8 species of freshwater cosmopolite algae which have quite different morphologies (Cosmarium contractum, Cryptomonas ovata, Euglena gracilis, Limnothrix redekei, Monoraphidium contortum, Pediastrum tetras, Planktothrix agardhii and Scenedesmus acutus) using several kinds of culture media. The treatments were four: low and high nutrient concentrations (N and P) and presence and absence of Daphnia magna, Keratella cochlearis, and Brachionus calicyflorus. The competition between pairs of algae has been studied and also the viability of the species as inoculum after a senescence period. The presence of herbivores (predation) and the nutrient concentration (competition) are the mechanisms that by themselves or sinergically affect the microalgae assemblages originating different alternative states from the same pool of species. But the effect of these mechanisms is different depending on the algal properties such as size, growth rate, and viability as inoculum. The presence of herbivores and the oligotrophic conditions reduce the primary producers' biomass but increase diversity due to relaxation of competition and increase the uncertainty of final states. It is also shown that the variations in the community structure are directly reflected on the function, affecting primary production and respiration

Cambodian Higher Education Governance: The Politics of Global Summitry and Clientelism

This chapter uses the concepts of “global summitry” and “clientelism” to theorize higher education governance in Cambodia. After reviewing the history of higher education since the 1960s, the chapter analyzes the country’s experiences amid regional attempts to harmonize standards, degree structures, quality assurance systems, and credit systems in Southeast Asia. Rather than explicit intervention into Cambodia’s higher education sector as has been historically common, the contemporary order transmits policy and governance practices through various regional and international forums, creating a seemingly homogenous system of higher education. External influence through global summitry, however, must be paired with a recognition of the prevalence of clientelism. By exploring the case of the Accreditation Council of Cambodia, higher education governance is shown to reproduce the engrained system of clientelism, empowering elites and contributing further to systems of informal patronage. The chapter concludes with recent (up to April 2016) developments in higher education governance, offering some observations and obstacles for future development in the sector