Saliency Methods for Object Discovery Based on Image and Depth Segmentation

Object discovery is a recent paradigm in computer and robotic vision where the process of interpreting an image starts by proposing a set of candidate regions that potentially correspond to objects; these candidates can be validated later on by object recognition modules or by robot interaction. In this thesis, we propose a novel method for object discovery that works on single RGB-D images and aims at achieving higher recall than current state-of-the-art methods with fewer candidates. Our approach uses saliency as a cue to roughly estimate the location and extent of the objects, and segmentation processes in order to identify the candidates' precise boundaries. We investigate the performance of four different segmentation methods based on colour, depth, an early and a late fusion of colour and depth, and conclude that the late fusion is the most successful. The object candidates are sorted according to a novel ranking strategy based on a combination of features such as 3D convexity and saliency. We evaluate our method and compare it to other state-of-the-art approaches in object discovery on challenging real world sequences from three different public datasets containing a high degree of clutter. The results show that our approach consistently outperforms the other methods. In the second part of this thesis, we turn to streams of images. Here, our goal is to generate as few object candidates per frame as necessary in order to find as many objects as possible throughout the sequence. Therefore, we propose to extend our object discovery system with a so called spatial inhibition of return mechanism to inhibit object candidates that correspond to objects that have already been generated in the past. The challenge here is to inhibit the candidates consistently with viewpoint change, and therefore, we root our inhibition of return mechanism in 3D spatial coordinates. In the final part of this thesis we show an application of our object discovery method to the task of salient object segmentation. The results show that our method achieves state-of-the-art performance

Fast Object Learning and Dual-arm Coordination for Cluttered Stowing, Picking, and Packing

Robotic picking from cluttered bins is a demanding task, for which Amazon Robotics holds challenges. The 2017 Amazon Robotics Challenge (ARC) required stowing items into a storage system, picking specific items, and packing them into boxes. In this paper, we describe the entry of team NimbRo Picking. Our deep object perception pipeline can be quickly and efficiently adapted to new items using a custom turntable capture system and transfer learning. It produces high-quality item segments, on which grasp poses are found. A planning component coordinates manipulation actions between two robot arms, minimizing execution time. The system has been demonstrated successfully at ARC, where our team reached second places in both the picking task and the final stow-and-pick task. We also evaluate individual components.Comment: In: Proceedings of the International Conference on Robotics and Automation (ICRA) 201

Semantic segmentation priors for object discovery

© 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.Reliable object discovery in realistic indoor scenes is a necessity for many computer vision and service robot applications. In these scenes, semantic segmentation methods have made huge advances in recent years. Such methods can provide useful prior information for object discovery by removing false positives and by delineating object boundaries. We propose a novel method that combines bottom-up object discovery and semantic priors for producing generic object candidates in RGB-D images. We use a deep learning method for semantic segmentation to classify colour and depth superpixels into meaningful categories. Separately for each category, we use saliency to estimate the location and scale of objects, and superpixels to find their precise boundaries. Finally, object candidates of all categories are combined and ranked. We evaluate our approach on the NYU Depth V2 dataset and show that we outperform other state-of-the-art object discovery methods in terms of recall.Peer ReviewedPostprint (author's final draft

Avances en aspectos de seguridad aplicados a sistemas de voto electrónico

El debate sobre las fortalezas y debilidades del voto electrónico se encuentra en un momento de fuerte polémica, no solamente en la sociedad en general, sino también en el ámbito académico. Las argumentaciones a favor y en contra de su aplicación son muy diversas. Los que opinan a favor, se basan en la velocidad con la que se conocen los resultados y en la (supuesta) exactitud del proceso. Los que se oponen, afirman que resulta imposible asegurar la transparencia de los sistemas de voto electrónico. La postura asumida por este equipo de investigación, es que se trata de un sistema de seguridad crítica, y que la confianza del electorado es de máxima importancia para lograr su aceptación, tal como afirman McGaley y Gibson en [1]: “Un sistema de votación es tan bueno como el público cree que es”. Este grupo de trabajo percibe estos sistemas como objetos de investigación, por lo tanto, está dedicado al análisis y evaluación de las condiciones de seguridad que deben cumplir y también al estudio de las soluciones que diferentes autores han propuesto hasta el momento, para intentar generar un modelo que facilite el desarrollo de un sistema robusto y confiable. Se siguen, en forma paralela, dos líneas de trabajo que representan esquemas diferentes que pueden aplicarse a los sistemas de voto electrónico: a. Basado en criptografía homomórfica. b. Basado en criptografía One Time Pad. En este trabajo se exponen los avances que se llevaron a cabo para cada una de las mencionadas líneas.Eje: Seguridad informática.Red de Universidades con Carreras en Informátic

Un sistema de voto electrónico para la FCEyN (UNLPam)

La utilización del voto electrónico sigue siendo un tema que genera fuertes controversias. En los ámbitos políticos, se utiliza la dicotomía planteada contra el voto manual como un elemento de permanentes disputas. Desde hace varios años este equipo de trabajo propone un análisis imparcial de los costos y beneficios de implementar este tipo de sistemas, proponiendo métodos y técnicas que permitan que un sistema de voto electrónico responda a exigencias del más alto nivel y publicando periódicamente sus avances (por ejemplo, [1], [2], [3] y [4]). Se afirma que un sistema de E-Voting no solamente debe ser absolutamente seguro, sino que además, tal característica debe ser plenamente comprobable. Pero no sólo para los expertos en la materia; también para todos los votantes que participen de un proceso electoral. La confiabilidad del sistema no solamente debe apuntar a la integridad de los resultados obtenidos, sino que aparecen otros aspectos que deben observarse, como por ejemplo la confidencialidad del elector (que debe protegerse indefinidamente) y la velocidad con la que se obtienen los resultados finales. En consecuencia, se propone implementar un sistema de voto electrónico que pudiera aplicarse en la Facultad de Ciencias Exactas y Naturales de la Universidad Nacional de La Pampa, a través de un nuevo proyecto de investigación que será presentado durante 2021 y que tendrá una duración de cinco años. Se busca implementar todos los avances realizados en publicaciones previas y agregar elementos novedosos en algunos puntos, tal como lo describe el presente documento.Eje: Seguridad informática.Red de Universidades con Carreras en Informátic

Performance of Different Catalysts for the In Situ Cracking of the Oil-Waxes Obtained by the Pyrolysis of Polyethylene Film Waste

The author Lucía Quesada acknowledges the financial support provided by the Ministry of Education (Spain) through Research Grant FPU18/01293.Currently, society is facing a great environmental problem, due to the large amount of plastic waste generated, most of which is not subjected to any type of treatment. In this work, polyethylene film waste from the non-selectively collected fraction was catalytically pyrolyzed at 500 ◦C, 20 ◦C/min for 2 h, in a discontinuous reactor using nitrogen as an inert gas stream. The main objective of this paper is to find catalysts that decrease the viscosity of the liquid fraction, since this property is quite meaningful in thermal pyrolysis. For this purpose, the three products of catalytic pyrolysis, the gaseous fraction, the solid fraction and the liquid fraction, were separated, obtaining the yield values. After that, the aspect of the liquid fraction was studied, differentiating which catalysts produced a larger quantity of waxy fraction and which ones did not. The viscosity of these samples was measured in order to confirm the catalysts that helped to obtain a less waxy fraction. The results showed that the zeolites Y and the zeolites β used in this study favor the obtaining of a compound with a smaller amount of waxes than for example catalysts such as FCC, ZSM-5 or SnCl2.Ministry of Education (Spain) FPU18/01293Department of Chemical Engineering, University of Granad

Realidad virtual y adiestramiento en sistemas críticos

La complejidad de los ejercicios de adiestramiento en un ámbito tan exigente como el de la defensa – tanto en medidas de seguridad, como en los costos asociados a una operación de instrucción – convierte a estas prácticas en una actividad crítica. Los costos asociados a dichas actividades, aumentan a medida que se asciende en el grado de exposición, del personal al que se desea dar instrucción, a procedimientos cercanos al uso de material bélico o sistemas de armas. A través de la inclusión de tecnologías de simulación y virtualización se busca reducir dichos factores. Utilizándolas para dar contexto y aportar valor agregado, sumando una cuota de realismo a bajo costo y riesgo controlado – tanto humano como material –, para dar apoyo a las operaciones de adiestramiento. Por eso, desde el proyecto SATAC se propuso la utilización de tecnologías de Realidad Virtual, considerando sus ventajas. El fin de esta integración será aportar realismo y complejidad al proyecto sin la necesidad de realizar despliegues adicionales de material y con riesgos mínimos para los participantes, potenciando a las operaciones convencionales con simulaciones vivas, virtuales y constructivas (Live, virtual, constructive – LVC–).Eje: Innovación en Sistemas de Software.Red de Universidades con Carreras en Informática (RedUNCI

Biosorption kinetics of Cd(II), Cr(III) and Pb(II) in aqueous solutions by olive stone

A by-product from olive oil production, olive stone, was investigated for the removal of Cd (II), Cr (III) and Pb (II) from aqueous solutions. The kinetics of biosorption are studied, analyzing the effect of the initial concentration of metal and temperature. Pseudo-first-order, pseudo-second-order, Elovich and intraparticle diffusion models have been used to represent the kinetics of the process and obtain the main kinetic parameters. The results show that the pseudo-second order model is the one that best describes the biosorption of the three metal ions for all the range of experimental conditions investigated. For the three metal ions, the maximum biosoption capacity and the initial biosorption rate increase when the initial metal concentration rises. However, the kinetic constant decreases when the initial metal concentration increases. The temperature effect on biosorption capacity for Cd (II) and Cr (III) is less significant; however, for Pb (II) the effect of temperature is more important, especially when temperature rises from 25 to 40ºC. The biosorption capacity at mmol/g of olive stone changes in the following order: Cr>Cd>Pb. Thus, for an initial concentration of 220 mg/ℓ, a maximum sorption capacity of 0.079 mmol/g for Cr (III), 0.065 mmol/g for Cd (II) and 0.028 mmol/g for Pb (II) has been obtained.The authors are grateful to the Ministerio de Educación y Ciencia for the financial support received (Projet CTM2005-03957/TECNO) for the realization of this work