Shape basis interpretation for monocular deformable 3D reconstruction

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, we propose a novel interpretable shape model to encode object non-rigidity. We first use the initial frames of a monocular video to recover a rest shape, used later to compute a dissimilarity measure based on a distance matrix measurement. Spectral analysis is then applied to this matrix to obtain a reduced shape basis, that in contrast to existing approaches, can be physically interpreted. In turn, these pre-computed shape bases are used to linearly span the deformation of a wide variety of objects. We introduce the low-rank basis into a sequential approach to recover both camera motion and non-rigid shape from the monocular video, by simply optimizing the weights of the linear combination using bundle adjustment. Since the number of parameters to optimize per frame is relatively small, specially when physical priors are considered, our approach is fast and can potentially run in real time. Validation is done in a wide variety of real-world objects, undergoing both inextensible and extensible deformations. Our approach achieves remarkable robustness to artifacts such as noisy and missing measurements and shows an improved performance to competing methods.Peer ReviewedPostprint (author's final draft

INDICATORS OF URBAN SUSTAINABILITY IN MEXICO

The principal objective of this project is to summarize the characteristics that define urban sustainability in Mexican cities; its basic principles and the advantages of their application in the development of future cities, as well as the description of the indicators of urban sustainability that directly affect the development of communities, from households, colonies or neighbourhoods to cities or regions. The project’s method is based on the analysis of bibliographical information and the revision of some practical cases that refer to the development of sustainable indicators in urban environment.Indicators, sustainability, urbanism, development, cities.

On equilibrium existence in infinite horizon economies

In sequential economies with finite or infinite-lived real assets in positive net supply, we introduce constraints on the amount of borrowing in terms of the market value of physical endowments. We show that, when utility functions are either unbounded and separable in states of nature or separable in commodities, these borrowing constraints not only preclude Ponzi schemes but also induce endogenous Radner bounds on short-sales. Therefore, we obtain existence of equilibrium. Moreover, equilibrium also exists when both assets are numerarie and utility functions are quasilinear in the commodity used as numerarie.Equilibrium, Infinite horizon incomplete markets, Infinite-lived real assets.

Propuesta de instrumento de evaluación de procesos y resultados del programa de prevención de la antisocialidad de la Preceptoría Juvenil de Reintegración Social de Texcoco del año 2014

Los elementos que debe considerar la propuesta de Evaluación por Procesos del Programa de Prevención de la Antisocialidad son los procedimientos, las interacciones y el contenido del Programa. Esto debido a que en la evaluación se detectó que el contenido del Programa presenta varios problemas tanto en el diseño como en la ejecución, que no permiten que las actividades se realicen de manera eficaz. La pregunta se contestó tomando como base todos los elementos que influyen para que no se logren las metas del Programa. Se revisó el contenido del programa, el procedimiento que se lleva a cabo para realizar cada una de las estrategias establecidas en los subprogramas y las interacciones que se dan en la organización (internas y externas) para ejecutarlas. En lo relacionado a los resultados es necesario considerar tanto los alcances del programa como las deficiencias del mismo. Al identificar las deficiencias en los procesos, se podrán tomar medidas para subsanar los errores que se presentan y modificarlos para lograr mejores resultados. En cuanto al alcance se puede identificar si los resultados logrados realmente están atendiendo el problema por el que fue creado este Programa

Coupled Extraction/Re-Extraction Method for the Chemical Speciation of Nickel in NaturalWaters

Chemical fractionation and speciation of metals species in natural waters and its relation with bioavailability have received increased attention in recent years. A simple liquid membranes method, based on coupled liquid extraction and re-extraction processes, is proposed to separate and quantify the species of nickel present in water samples. A simplex optimization of chemical variables, such as carrier concentration in the organic solution and nitric acid concentration in the receiving solution, was performed and, under optimized conditions, the extraction system was applied to determine nickel species in water samples at natural level concentrations. A linear relationship was established between extraction e cacy and the concentration of dissolved organic carbon in the samples, allowing the separation and determination of labile and non-labile nickel fractions, since the latter was not transported through the organic solution acting as liquid membrane. When the total and labile concentrations of metals were analyzed in real samples with di erent salinities, no significant di erences were found between the results obtained and those from well-established methods. An average relative error of 1.50 and 2.37 was obtained for total Ni concentration and labile fraction, respectively. Finally, a comparison with the theoretical speciation data calculated with the softwareWinHumic V was successfully performed. Thus, the proposed method allows the simultaneous determination of labile and non-labile nickel fractions, presented as a simple alternative to nickel fractionation in natural waters

Vehicle pose estimation using G-Net: multi-class localization and depth estimation

In this paper we present a new network architecture, called G-Net, for 3D pose estimation on RGB images which is trained in a weakly supervised manner. We introduce a two step pipeline based on region-based Convolutional neural networks (CNNs) for feature localization, bounding box refinement based on non-maximum-suppression and depth estimation. The G-Net is able to estimate the depth from single monocular images with a self-tuned loss function. The combination of this predicted depth and the presented two-step localization allows the extraction of the 3D pose of the object. We show in experiments that our method achieves good results compared to other state-of-the-art approaches which are trained in a fully supervised manner.Peer ReviewedPostprint (author's final draft

Image collection pop-up: 3D reconstruction and clustering of rigid and non-rigid categories

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper introduces an approach to simultaneously estimate 3D shape, camera pose, and object and type of deformation clustering, from partial 2D annotations in a multi-instance collection of images. Furthermore, we can indistinctly process rigid and non-rigid categories. This advances existing work, which only addresses the problem for one single object or, if multiple objects are considered, they are assumed to be clustered a priori. To handle this broader version of the problem, we model object deformation using a formulation based on multiple unions of subspaces, able to span from small rigid motion to complex deformations. The parameters of this model are learned via Augmented Lagrange Multipliers, in a completely unsupervised manner that does not require any training data at all. Extensive validation is provided in a wide variety of synthetic and real scenarios, including rigid and non-rigid categories with small and large deformations. In all cases our approach outperforms state-of-the-art in terms of 3D reconstruction accuracy, while also providing clustering results that allow segmenting the images into object instances and their associated type of deformation (or action the object is performing).Postprint (author's final draft