Horn-schunck optical flow with a multi-scale strategy

[EN] The seminal work of Horn and Schunck [8] is the first variational method for optical flow estimation. It introduced a novel framework where the optical flow is computed as the solution of a minimization problem. From the assumption that pixel intensities do not change over time, the optical flow constraint equation is derived. This equation relates the optical flow with the derivatives of the image. There are infinitely many vector fields that satisfy the optical flow constraint, thus the problem is ill-posed. To overcome this problem, Horn and Schunck introduced an additional regularity condition that restricts the possible solutions. Their method minimizes both the optical flow constraint and the magnitude of the variations of the flow field, producing smooth vector fields. One of the limitations of this method is that, typically, it can only estimate small motions. In the presence of large displacements, this method fails when the gradient of the image is not smooth enough. In this work, we describe an implementation of the original Horn and Schunck method and also introduce a multi-scale strategy in order to deal with larger displacements. For this multi-scale strategy, we create a pyramidal structure of downsampled images and change the optical flow constraint equation with a nonlinear formulation. In order to tackle this nonlinear formula, we linearize it and solve the method iteratively in each scale. In this sense, there are two common approaches: one that computes the motion increment in the iterations, like in ; or the one we follow, that computes the full flow during the iterations, like in. The solutions are incrementally refined ower the scales. This pyramidal structure is a standard tool in many optical flow methods.

Wind-driven cross-equatorial flow in the Indian ocean

Máster en Oceanografía

Parallel implementation of a robust optical flow technique

[EN] The accuracy and performance of current variational optical ow methods have considerably increased during the last years. The complexity of these techniques is high and enough care has to be taken for the implementation. The aim of this work is to present a comprehensible implementation of recent variational optical flow methods. We start with an energy model that relies on brightness and gradient constancy terms and a ow-based smoothness term. We minimize this energy model and derive an e cient implicit numerical scheme. In the experimental results, we evaluate the accuracy and performance of this implementation with the Middlebury benchmark database. We show that it is a competitive solution with respect to current methods in the literature. In order to increase the performance, we use a simple strategy to parallelize the execution on multi-core processors.

Metabolic and thermodynamic responses to dehydration-induced reductions in muscle blood flow in exercising humans

[EN] 1. The present study examined whether reductions in muscle blood flow with exercise-induced dehydration would reduce substrate delivery and metabolite and heat removal to and from active skeletal muscles during prolonged exercise in the heat. A second aim was to examine the effects of dehydration on fuel utilisation across the exercising leg and identify factors related to fatigue. 2. Seven cyclists performed two cycle ergometer exercise trials in the heat (35 C; 61 +/- 2 % of maximal oxygen consumption rate, VO2,max), separated by 1 week. During the first trial (dehydration, DE), they cycled until volitional exhaustion (135 +/- 4 min, mean +/- s.e.m.), while developing progressive DE and hyperthermia (3.9 +/- 0.3 % body weight loss and 39.7 +/- 0.2 C oesophageal temperature, Toes). On the second trial (control), they cycled for the same period of time maintaining euhydration by ingesting fluids and stabilising Toes at 38.2 +/- 0.1 degrees C. 3. After 20 min of exercise in both trials, leg blood flow (LBF) and leg exchange of lactate, glucose, free fatty acids (FFA) and glycerol were similar. During the 20 to 135 +/- 4 min period of exercise, LBF declined significantly in DE but tended to increase in control. Therefore, after 120 and 135 +/- 4 min of DE, LBF was 0.6 +/- 0.2 and 1.0 +/- 0.3 l min-1 lower (P < 0.05), respectively, compared with control. 4. The lower LBF after 2 h in DE did not alter glucose or FFA delivery compared with control. However, DE resulted in lower (P < 0.05) net FFA uptake and higher (P < 0.05) muscle glycogen utilisation (45 %), muscle lactate accumulation (4.6-fold) and net lactate release (52 %), without altering net glycerol release or net glucose uptake. 5. In both trials, the mean convective heat transfer from the exercising legs to the body core ranged from 6.3 +/- 1.7 to 7.2 +/- 1.3 kJ min-1, thereby accounting for 35-40 % of the estimated rate of heat production ( approximately 18 kJ min-1). 6. At exhaustion in DE, blood lactate values were low whereas blood glucose and muscle glycogen levels were still high. Exhaustion coincided with high body temperature ( approximately 40 C). 7. In conclusion, the present results demonstrate that reductions in exercising muscle blood flow with dehydration do not impair either the delivery of glucose and FFA or the removal of lactate during moderately intense prolonged exercise in the heat. However, dehydration during exercise in the heat elevates carbohydrate oxidation and lactate production. A major finding is that more than one-half of the metabolic heat liberated in the contracting leg muscles is dissipated directly to the surrounding environment. The present results indicate that hyperthermia, rather than altered metabolism, is the main factor underlying the early fatigue with dehydration during prolonged exercise in the heat.

A dynamic model of oceanic sulfur (DMOS) applied to the Sargasso Sea: Simulating the dimethylsulfide (DMS) summer paradox

[EN]A new one-dimensional model of DMSP/DMS dynamics (DMOS) is developed and applied to the Sargasso Sea in order to explain what drives the observed dimethylsulfide (DMS) summer paradox: a summer DMS concentration maximum concurrent with a minimum in the biomass of phytoplankton, the producers of the DMS precursor dimethylsulfoniopropionate (DMSP). Several mechanisms have been postulated to explain this mismatch: a succession in phytoplankton species composition towards higher relative abundances of DMSP producers in summer; inhibition of bacterial DMS consumption by ultraviolet radiation (UVR); and direct DMS production by phytoplankton due to UVR-induced oxidative stress. None of these hypothetical mechanisms, except for the first one, has been tested with a dynamic model. We have coupled a new sulfur cycle model that incorporates the latest knowledge on DMSP/DMS dynamics to a preexisting nitrogen/carbon-based ecological model that explicitly simulates the microbial-loop. This allows the role of bacteria in DMS production and consumption to be represented and quantified. The main improvements of DMOS with respect to previous DMSP/DMS models are the explicit inclusion of: solar-radiation inhibition of bacterial sulfur uptakes; DMS exudation by phytoplankton caused by solar-radiation-induced stress; and uptake of dissolved DMSP by phytoplankton. We have conducted a series of modeling experiments where some of the DMOS sulfur paths are turned “off” or “on,” and the results on chlorophyll-a, bacteria, DMS, and DMSP (particulate and dissolved) concentrations have been compared with climatological data of these same variables. The simulated rate of sulfur cycling processes are also compared with the scarce data available from previous works. All processes seem to play a role in driving DMS seasonality. Among them, however, solar-radiation-induced DMS exudation by phytoplankton stands out as the process without which the model is unable to produce realistic DMS simulations and reproduce the DMS summer paradox.