Probabilistic RGB-D Odometry based on Points, Lines and Planes Under Depth Uncertainty

This work proposes a robust visual odometry method for structured environments that combines point features with line and plane segments, extracted through an RGB-D camera. Noisy depth maps are processed by a probabilistic depth fusion framework based on Mixtures of Gaussians to denoise and derive the depth uncertainty, which is then propagated throughout the visual odometry pipeline. Probabilistic 3D plane and line fitting solutions are used to model the uncertainties of the feature parameters and pose is estimated by combining the three types of primitives based on their uncertainties. Performance evaluation on RGB-D sequences collected in this work and two public RGB-D datasets: TUM and ICL-NUIM show the benefit of using the proposed depth fusion framework and combining the three feature-types, particularly in scenes with low-textured surfaces, dynamic objects and missing depth measurements.Comment: Major update: more results, depth filter released as opensource, 34 page

Low-wage employment in Portugal: a mixed logit approach

In this paper, we examine the determinants of low-wage employment in Portugal. For this purpose, we use a data file of the European Community Household Panel (ECHP) for the years 1998 and 1999. In order to take into account unobserved heterogeneity in the data, a random-parameter logit model is used to analyse the probability of a worker receiving a low wage. The results indicate that the consideration that the effects of the explanatory variables are the same across all individuals, such as is assumed in most of the literature may be misleading. From the policy perspective, this implies that the use of a single instrument in order to combat low-wage employment is inappropriate to satisfy the whole population. In view of this, policies tailored by clusters would be more appropriate.low-wage employment, random-parameter logit model, public policy.

Service design for innovation in small and medium businesses

An innovation program designed and implemented with two Peruvian small, medium business in health and hotel industries focused on value creation goal while developing products and services innovation. For insights, ideas generation, solutions validation and prototyping proposals at the front-end open innovation strategy were used both indirect and direct methods; trends research, customer journey mapping, ethnography, interaction with users with depth interviews and dynamic group sessions. The research sought both to test the program and deploy the methods developed in business to advance capabilities for knowledge management and iterative processes. As a result small and medium businesses can develop Services Design according to their human and financial limitations using processes based on four axes; scanning the environment immersion learning, gamification, Lean and Design Thinking. The research concluded there are alternative paths that take into account and involve greater collaboration of users that businesses can explore and exploit. Innovation processes do not have to be long, uncertain or expensive for small and medium businesses.Un programa de innovación con dos pequeñas y medianas empresas peruanas, en la industria de la salud y hotelera, fue diseñado e implementado con el objetivo de creación de valor a través de la innovación de productos y servicios. Para Insights, la generación de ideas, la validación de soluciones y la propuesta de creación de prototipos en la estrategia de innovación abierta frontend se utilizaron métodos indirectos y directos; investigación de tendencias, mapeo del viaje del cliente, etnografía, interacción con usuarios con entrevistas en profundidad y sesiones dinámicas de grupo. La investigación buscó probar el programa e implementar los métodos desarrollados en las empresas para mejorar las capacidades de gestión del conocimiento y procesos iterativos. Como resultado, las pequeñas y medianas empresas pueden diseñar servicios de acuerdo con sus limitaciones humanas y financieras utilizando procesos basados en cuatro ejes; escaneo del entorno de la empresa, observación y entrevistas en profundidad, gamificación, Lean y Design Thinking. La investigación concluyó que hay caminos alternativos que tienen en cuenta e implican una mayor colaboración de los usuarios que las empresas pueden explorar y explotar. Los procesos de innovación no tienen que ser largos, inciertos ni costosos para las pequeñas y medianas empresas

Cell aging preserves cellular immortality in the presence of lethal levels of damage.

Cellular aging, a progressive functional decline driven by damage accumulation, often culminates in the mortality of a cell lineage. Certain lineages, however, are able to sustain long-lasting immortality, as prominently exemplified by stem cells. Here, we show that Escherichia coli cell lineages exhibit comparable patterns of mortality and immortality. Through single-cell microscopy and microfluidic techniques, we find that these patterns are explained by the dynamics of damage accumulation and asymmetric partitioning between daughter cells. At low damage accumulation rates, both aging and rejuvenating lineages retain immortality by reaching their respective states of physiological equilibrium. We show that both asymmetry and equilibrium are present in repair mutants lacking certain repair chaperones, suggesting that intact repair capacity is not essential for immortal proliferation. We show that this growth equilibrium, however, is displaced by extrinsic damage in a dosage-dependent response. Moreover, we demonstrate that aging lineages become mortal when damage accumulation rates surpass a threshold, whereas rejuvenating lineages within the same population remain immortal. Thus, the processes of damage accumulation and partitioning through asymmetric cell division are essential in the determination of proliferative mortality and immortality in bacterial populations. This study provides further evidence for the characterization of cellular aging as a general process, affecting prokaryotes and eukaryotes alike and according to similar evolutionary constraints

Age structure landscapes emerge from the equilibrium between aging and rejuvenation in bacterial populations.

The physiological asymmetry between daughters of a mother bacterium is produced by the inheritance of either old poles, carrying non-genetic damage, or newly synthesized poles. However, as bacteria display long-term growth stability leading to physiological immortality, there is controversy on whether asymmetry corresponds to aging. Here we show that deterministic age structure landscapes emerge from physiologically immortal bacterial lineages. Through single-cell microscopy and microfluidic techniques, we demonstrate that aging and rejuvenating bacterial lineages reach two distinct states of growth equilibria. These equilibria display stabilizing properties, which we quantified according to the compensatory trajectories of continuous lineages throughout generations. Finally, we show that the physiological asymmetry between aging and rejuvenating lineages produces complex age structure landscapes, resulting in a deterministic phenotypic heterogeneity that is neither an artifact of starvation nor a product of extrinsic damage. These findings indicate that physiological immortality and cellular aging can both be manifested in single celled organisms

Information Retrieval: Recent Advances and Beyond

In this paper, we provide a detailed overview of the models used for information retrieval in the first and second stages of the typical processing chain. We discuss the current state-of-the-art models, including methods based on terms, semantic retrieval, and neural. Additionally, we delve into the key topics related to the learning process of these models. This way, this survey offers a comprehensive understanding of the field and is of interest for for researchers and practitioners entering/working in the information retrieval domain

Deep Learning for Spacecraft Pose Estimation from Photorealistic Rendering

On-orbit proximity operations in space rendezvous, docking and debris removal require precise and robust 6D pose estimation under a wide range of lighting conditions and against highly textured background, i.e., the Earth. This paper investigates leveraging deep learning and photorealistic rendering for monocular pose estimation of known uncooperative spacecrafts. We first present a simulator built on Unreal Engine 4, named URSO, to generate labeled images of spacecrafts orbiting the Earth, which can be used to train and evaluate neural networks. Secondly, we propose a deep learning framework for pose estimation based on orientation soft classification, which allows modelling orientation ambiguity as a mixture of Gaussians. This framework was evaluated both on URSO datasets and the ESA pose estimation challenge. In this competition, our best model achieved 3rd place on the synthetic test set and 2nd place on the real test set. Moreover, our results show the impact of several architectural and training aspects, and we demonstrate qualitatively how models learned on URSO datasets can perform on real images from space.Comment: * Adding more related work and reference