Evaluation of CNN architectures for gait recognition based on optical flow maps

This work targets people identification in video based on the way they walk (\ie gait) by using deep learning architectures. We explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (\ie optical flow components). The low number of training samples for each subject and the use of a test set containing subjects different from the training ones makes the search of a good CNN architecture a challenging task.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Pyramidal Fisher Motion for Multiview Gait Recognition

Submitted to International Conference on Pattern Recognition, ICPR, 2014The goal of this paper is to identify individuals by analyzing their gait. Instead of using binary silhouettes as input data (as done in many previous works) we propose and evaluate the use of motion descriptors based on densely sampled short-term trajectories. We take advantage of state-of-the-art people detectors to define custom spatial configurations of the descriptors around the target person. Thus, obtaining a pyramidal representation of the gait motion. The local motion features (described by the Divergence-Curl-Shear descriptor) extracted on the different spatial areas of the person are combined into a single high-level gait descriptor by using the Fisher Vector encoding. The proposed approach, coined Pyramidal Fisher Motion, is experimentally validated on the recent `AVA Multiview Gait' dataset. The results show that this new approach achieves promising results in the problem of gait recognition

Western Mediterranean precipitation over the last 300 years from instrumental observations

The paper reports the results of the analysis of the 14 longest precipitation instrumental series, covering the last 300 years, that have been recovered in six subareas of the Western Mediterranean basin, i.e., Portugal, Northern and Southern Spain, Southern France, Northern and Southern Italy. This study extends back by one century our knowledge about the instrumental precipitation over theWestern Mediterranean, and by two centuries in some specific subareas. All the time series show repeated swings. No specific trends have been found over the whole period, except in a few cases, but with modest time changes and sometimes having opposite tendency. The same can be said for the most recent decades although with some more marked departures from the average. The correlation between the various Mediterranean subareas is generally not significant, or almost uncorrelated. The Wavelet Spectral Analysis applied to the precipitation identifies only a minor 56-year cycle in autumn, i.e., the same return period that has been found in literature for the Sea Surface Temperature over North Atlantic. A comparison with a gridded dataset reconstruction based on mixed multiproxy and instrumental observations, shows that the grid reconstruction is in good agreement with the observed data for the period after 1900, less for the previous period

Super Five Brane Hamiltonian and the Chiral Degrees of Freedom

We construct the Hamiltonian of the super five brane in terms of its physical degrees of freedom. It does not depend on the inverse of the induced metric. Consequently, some singular configurations are physically admissible, implying an interpretation of the theory as a multiparticle one. The symmetries of the theory are analyzed from the canonical point of view in terms of the first and second class constraints. In particular it is shown how the chiral sector may be canonically reduced to its physical degrees of freedom.Comment: 16 pages, typos correcte

A robust model for rapidly varying flows over movable bottom with suspended and bedload transport: modelling and numerical approach

We propose a coupled model for suspended and bedload sediment transport in the shallow water framework. The model is deduced under hydrostatic pressure assumptions and will not assume any Bossinesq hypothesis. The numerical resolution is carried out in a segregated way. First the underlying system of conservation laws is solved by using a first order path-conservative Riemann solver. Then, the source terms corresponding with the erosion and depositions rates are approximated in a semi-implicit way. The final scheme preserves the positivity of the density. Several numerical experiments were carried out in order to validate the model and the numerical scheme. The results obtained are in good agreement with the experimental data

Solving shallow-water systems in 2D domains using Finite Volume methods and multimedia SSE instructions

AbstractThe goal of this paper is to construct efficient parallel solvers for 2D hyperbolic systems of conservation laws with source terms and nonconservative products. The method of lines is applied: at every intercell a projected Riemann problem along the normal direction is considered which is discretized by means of well-balanced Roe methods. The resulting 2D numerical scheme is explicit and first-order accurate. In [M.J. Castro, J.A. García, J.M. González, C. Pares, A parallel 2D Finite Volume scheme for solving systems of balance laws with nonconservative products: Application to shallow flows, Comput. Methods Appl. Mech. Engrg. 196 (2006) 2788–2815] a domain decomposition method was used to parallelize the resulting numerical scheme, which was implemented in a PC cluster by means of MPI techniques.In this paper, in order to optimize the computations, a new parallelization of SIMD type is performed at each MPI thread, by means of SSE (“Streaming SIMD Extensions”), which are present in common processors. More specifically, as the most costly part of the calculations performed at each processor consists of a huge number of small matrix and vector computations, we use the Intel© Integrated Performance Primitives small matrix library. To make easy the use of this library, which is implemented using assembler and SSE instructions, we have developed a C++ wrapper of this library in an efficient way. Some numerical tests were carried out to validate the performance of the C++ small matrix wrapper. The specific application of the scheme to one-layer Shallow-Water systems has been implemented on a PC’s cluster. The correct behavior of the one-layer model is assessed using laboratory data

Fisher Motion Descriptor for Multiview Gait Recognition

The goal of this paper is to identify individuals by analyzing their gait. Instead of using binary silhouettes as input data (as done in many previous works) we propose and evaluate the use of motion descriptors based on densely sampled short-term trajectories. We take advantage of state-of-the-art people detectors to de ne custom spatial con gurations of the descriptors around the target person, obtaining a rich representation of the gait motion. The local motion features (described by the Divergence-Curl-Shear descriptor [1]) extracted on the di erent spatial areas of the person are combined into a single high-level gait descriptor by using the Fisher Vector encoding [2]. The proposed approach, coined Pyramidal Fisher Motion, is experimentally validated on `CASIA' dataset [3] (parts B and C), `TUM GAID' dataset [4], `CMU MoBo' dataset [5] and the recent `AVA Multiview Gait' dataset [6]. The results show that this new approach achieves state-of-the-art results in the problem of gait recognition, allowing to recognize walking people from diverse viewpoints on single and multiple camera setups, wearing di erent clothes, carrying bags, walking at diverse speeds and not limited to straight walking paths

Productividad de la rotación anual raigrás- maíz en galicia: evaluación durante cinco años en regadío y secano y bajo dos sistemas de siembra

Es un estudio sobre la productividad de la rotación anual raigrás- maíz en galicia: evaluación durante cinco años en regadío y secano y bajo dos sistemas de siembr