Real-Time Adaptive Multi-Classifier Multi-Resolution Visual Tracking Framework for Unmanned Aerial Vehicles

This paper presents a novel robust visual tracking framework, based on discriminative method, for Unmanned Aerial Vehicles (UAVs) to track an arbitrary 2D/3D target at real-time frame rates, that is called the Adaptive Multi-Classifier Multi-Resolution (AMCMR) framework. In this framework, adaptive Multiple Classifiers (MC) are updated in the (k-1)th frame-based Multiple Resolutions (MR) structure with compressed positive and negative samples, and then applied them in the kth frame-based Multiple Resolutions (MR) structure to detect the current target. The sample importance has been integrated into this framework to improve the tracking stability and accuracy. The performance of this framework was evaluated with the Ground Truth (GT) in different types of public image databases and real flight-based aerial image datasets firstly, then the framework has been applied in the UAV to inspect the Offshore Floating Platform (OFP). The evaluation and application results show that this framework is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant illumination, partial/full target occlusion, blur motion, rapid pose variation and onboard mechanical vibration, among others. To our best knowledge, this is the first work to present this framework for solving the online learning and tracking freewill 2D/3D target problems, and applied it in the UAVs.

A region based approach to background modeling in a wavelet multi-resolution framework

In the field of detection and monitoring of dynamic objects in quasi-static scenes, background subtraction techniques where background is modeled at pixel-level, although showing very significant limitations, are extensively used. In this work we propose a novel approach to background modeling that operates at region-level in a wavelet based multi-resolution framework. Based on a segmentation of the background, characterization is made for each region independently as a mixture of K Gaussian modes, considering the model of the approximation and detail coefficients at the different wavelet decomposition levels. Background region characterization is updated along time, and the detection of elements of interest is carried out computing the distance between background region models and those of each incoming image in the sequence. The inclusion of the context in the modeling scheme through each region characterization makes the model robust, being able to support not only gradual illumination and long-term changes, but also sudden illumination changes and the presence of strong shadows in the scene

Multi-Resolution Texture Coding for Multi-Resolution 3D Meshes

We present an innovative system to encode and transmit textured multi-resolution 3D meshes in a progressive way, with no need to send several texture images, one for each mesh LOD (Level Of Detail). All texture LODs are created from the finest one (associated to the finest mesh), but can be re- constructed progressively from the coarsest thanks to refinement images calculated in the encoding process, and transmitted only if needed. This allows us to adjust the LOD/quality of both 3D mesh and texture according to the rendering power of the device that will display them, and to the network capacity. Additionally, we achieve big savings in data transmission by avoiding altogether texture coordinates, which are generated automatically thanks to an unwrapping system agreed upon by both encoder and decoder.

Multi-resolution model-based traffic sign detection and tracking

In this paper we propose an innovative approach to tackle the problem of traffic sign detection using a computer vision algorithm and taking into account real-time operation constraints, trying to establish intelligent strategies to simplify as much as possible the algorithm complexity and to speed up the process. Firstly, a set of candidates is generated according to a color segmentation stage, followed by a region analysis strategy, where spatial characteristic of previously detected objects are taken into account. Finally, temporal coherence is introduced by means of a tracking scheme, performed using a Kalman filter for each potential candidate. Taking into consideration time constraints, efficiency is achieved two-fold: on the one side, a multi-resolution strategy is adopted for segmentation, where global operation will be applied only to low-resolution images, increasing the resolution to the maximum only when a potential road sign is being tracked. On the other side, we take advantage of the expected spacing between traffic signs. Namely, the tracking of objects of interest allows to generate inhibition areas, which are those ones where no new traffic signs are expected to appear due to the existence of a TS in the neighborhood. The proposed solution has been tested with real sequences in both urban areas and highways, and proved to achieve higher computational efficiency, especially as a result of the multi-resolution approach.

Optimal Multiresolution 3D Level-Set Method for Liver Segmentation incorporating Local Curvature Constraints

Advanced liver surgery requires a precise pre-operative planning, where liver segmentation and remnant liver volume are key elements to avoid post-operative liver failure. In that context, level-set algorithms have achieved better results than others, especially with altered liver parenchyma or in cases with previous surgery. In order to improve functional liver parenchyma volume measurements, in this work we propose two strategies to enhance previous level-set algorithms: an optimal multi-resolution strategy with fine details correction and adaptive curvature, as well as an additional semiautomatic step imposing local curvature constraints. Results show more accurate segmentations, especially in elongated structures, detecting internal lesions and avoiding leakages to close structures

Local optimal scale in a hierarchical segmentation method for satellite image: an OBIA approach for the agricultural landscape

Overrecentdecades,remotesensinghasemergedasaneffectivetoolforimprov- ing agriculture productivity. In particular, many works have dealt with the problem of identifying characteristics or phenomena of crops and orchards on different scales using remote sensed images. Since the natural processes are scale dependent and most of them are hierarchically structured, the determination of optimal study scales is mandatory in understanding these processes and their interactions. The concept of multi-scale/multi- resolution inherent to OBIA methodologies allows the scale problem to be dealt with. But for that multi-scale and hierarchical segmentation algorithms are required. The question that remains unsolved is to determine the suitable scale segmentation that allows different objects and phenomena to be characterized in a single image. In this work, an adaptation of the Simple Linear Iterative Clustering (SLIC) algorithm to perform a multi-scale hierarchi- cal segmentation of satellite images is proposed. The selection of the optimal multi-scale segmentation for different regions of the image is carried out by evaluating the intra- variability and inter-heterogeneity of the regions obtained on each scale with respect to the parent-regions defined by the coarsest scale. To achieve this goal, an objective function, that combines weighted variance and the global Moran index, has been used. Two different kinds of experiment have been carried out, generating the number of regions on each scale through linear and dyadic approaches. This methodology has allowed, on the one hand, the detection of objects on different scales and, on the other hand, to represent them all in a sin- gle image. Altogether, the procedure provides the user with a better comprehension of the land cover, the objects on it and the phenomena occurring.

ITEM: Inter-Texture Error Measurement for 3D Meshes

We introduce a simple and innovative method to compare any two texture maps, regardless of their sizes, aspect ratios, or even masks, as long as they are both meant to be mapped onto the same 3D mesh. Our system is based on a zero-distortion 3D mesh unwrapping technique which compares two new adapted texture atlases with the same mask but different texel colors, and whose every texel covers the same area in 3D. Once these adapted atlases are created, we measure their difference with ITEM-RMSE, a slightly modified version of the standard RMSE defined for images. ITEM-RMSE is more meaningful and reliable than RMSE because it only takes into account the texels inside the mask, since they are the only ones that will actually be used during rendering. Our method is not only very useful to compare the space efficiency of different texture atlas generation algorithms, but also to quantify texture loss in compression schemes for multi-resolution textured 3D meshes.

Minimal template size for Iris-Recognition

A method to achieve improvement in template size for an iris-recognition system is reported. To achieve this result, the biological characteristics of the human iris have been studied. Processing has been performed by image processing techniques, isolating the iris and enhancing the area of study, after which multi resolution analysis is made. Reduction of the pattern obtained has been obtained via statistical study.

Design of a Semi-analytical Method to Describe Plasma-Wall Interactions

Electric probes are objects immersed in the plasma with sharp boundaries which collect of emit charged particles. Consequently, the nearby plasma evolves under abrupt imposed and/or naturally emerging conditions. There could be localized currents, different time scales for plasma species evolution, charge separation and absorbing-emitting walls. The traditional numerical schemes based on differences often transform these disparate boundary conditions into computational singularities. This is the case of models using advection-diffusion differential equations with source-sink terms (also called Fokker-Planck equations). These equations are used in both, fluid and kinetic descriptions, to obtain the distribution functions or the density for each plasma species close to the boundaries. We present a resolution method grounded on an integral advancing scheme by using approximate Green's functions, also called short-time propagators. All the integrals, as a path integration process, are numerically calculated, what states a robust grid-free computational integral method, which is unconditionally stable for any time step. Hence, the sharp boundary conditions, as the current emission from a wall, can be treated during the short-time regime providing solutions that works as if they were known for each time step analytically. The form of the propagator (typically a multivariate Gaussian) is not unique and it can be adjusted during the advancing scheme to preserve the conserved quantities of the problem. The effects of the electric or magnetic fields can be incorporated into the iterative algorithm. The method allows smooth transitions of the evolving solutions even when abrupt discontinuities are present. In this work it is proposed a procedure to incorporate, for the very first time, the boundary conditions in the numerical integral scheme. This numerical scheme is applied to model the plasma bulk interaction with a charge-emitting electrode, dealing with fluid diffusion equations combined with Poisson equation self-consistently. It has been checked the stability of this computational method under any number of iterations, even for advancing in time electrons and ions having different time scales. This work establishes the basis to deal in future work with problems related to plasma thrusters or emissive probes in electromagnetic fields.

A Multiresolution Image Alignment Technique Based on Direct Methods for Pose Estimation of Aerial Vehicles

In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi-Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles' state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle's state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle's state for more than one minute, at real-time frame rates based, only on visual information.

Determinación de la amplificación sísmica local en el Campus Sur UPM mediante la técnica de sismología de microtremores ReMi.

En el Campus Sur de la Universidad Politécnica de Madrid se ha llevado a cabo un proyecto para obtener una caracterización del subsuelo mediante ensayos ReMi, en colaboración con el departamento de Geofísica del Instituto Geográfico Nacional. La técnica ReMi (Refraction Microtremor) permite, mediante ensayos geofísicos realizados localmente sobre el terreno,obtener los parámetros físicos del mismo, que resultan de especial interés en el ámbito de la ingeniería civil. Esta técnica se caracteriza por englobarse dentro de la sísmica pasiva, muy empleada en prospección geofísica y basada en la obtención del modelo subyacente de distribución de velocidades de propagación de la onda S en función de la profundidad, con la ventaja de aprovechar el ruido sísmico ambiental como fuente de energía. Fue desarrollada en el Laboratorio Sismológico de Nevada (EEUU) por Louie (2001), con el objetivo de presentar una técnica innovadora en la obtención de las velocidades de propagación de manera experimental. Presenta ciertas ventajas, como la observación directa de la dispersión de ondas superficiales,que da un buen resultado de la velocidad de onda S, siendo un método no invasivo, de bajo coste y buena resolución, aplicable en entornos urbanos o sensibles en los que tanto otras técnicas sismológicas como otras variedades de prospección presentan dificultades. La velocidad de propagación de la onda S en los 30 primeros metros VS30, es ampliamente reconocida como un parámetro equivalente válido para caracterizar geotécnicamente el subsuelo y se halla matemáticamente relacionada con la velocidad de propagación de las ondas superficiales a observar mediante la técnica ReMi. Su observación permite el análisis espectral de los registros adquiridos, obteniéndose un modelo representado por la curva de dispersión de cada emplazamiento, de modo que mediante una inversión se obtiene el modelo de velocidad de propagación en función de la profundidad. A través de estos modelos, pueden obtenerse otros parámetros de interés sismológico. Estos resultados se representan sobre mapas isométricos para obtener una relación espacial de los mismos, particularmente conocido como zonación sísmica. De este análisis se extrae que la VS30 promedio del Campus no es baja en exceso, correspondiéndose a posteriori con los resultados de amplificación sísmica, período fundamental de resonancia del lugar y profundidad del sustrato rocoso. En última instancia se comprueba que los valores de amplificación sísmica máxima y el período al cual se produce posiblemente coincidan con los períodos fundamentales de resonancia de algunos edificios del Campus. ABSTRACT In South Campus at Polytechnic University of Madrid, a project has been carried out to obtain a proper subsoil description by applying ReMi tests, in collaboration with the Department of Geophysics of the National Geographic Institute. Through geophysical tests conducted locally, the ReMi (Refraction Microtremor) technique allows to establish the physical parameters of soil, which are of special interest in the field of civil engineering. This technique is part of passive seismic methods, often used in geophysical prospecting. It focuses in obtaining the underlying model of propagation velocity distribution of the shear wave according to depth and has the advantage of being able to use seismic ambient noise as a source of energy. It was developed in the Nevada Seismological Laboratory (USA) by Louie (2001) as an innovative technique for obtaining propagation velocities experimentally. It has several other advantages, including the direct observation of the dispersion of surface waves, which allows to reliably measure S wave velocity. This is a non-invasive, low cost and good resolution method, which can be applied in urban or sensitive environments where other prospection methods present difficulties. The propagation velocity of shear waves in the first 30 meters Vs30 is widely recognized as a valid equivalent parameter to geotechnically characterize the subsurface. It is mathematically related to surface wave's velocity of propagation, which are to observe using REMI technique. Spectral analysis of acquired data sets up a model represented by the dispersion curve at each site, so that, using an inversion process, propagation velocity model in relation to depth is obtained. Through this models, other seismologically interesting parameters can be obtained. These results are represented on isometric maps in order to obtain a spatial relationship between them, a process which is known as seismic zonation. This analysis infers that Vs30 at South Campus is not alarmingly low , corresponding with subsequent results of seismic amplification, fundamental period of resonance of soil and depth of bedrock. Ultimately, it's found that calculated values of soil's fundamental periods at which maximum seismic amplification occurs, may possibly match fundamental periods of some Campus buildings.