Information-driven navigation

En los últimos años, hemos presenciado un progreso enorme de la precisión y la robustez de la “Odometría Visual” (VO) y del “Mapeo y la Localización Simultánea” (SLAM). Esta mejora de su funcionamiento ha permitido las primeras implementaciones comerciales relacionadascon la realidad aumentada (AR), la realidad virtual (VR) y la robótica. En esta tesis, desarrollamos nuevos métodos probabilísticos para mejorar la precisión, robustez y eficiencia de estas técnicas. Las contribuciones de nuestro trabajo están publicadas en tres artículos y se complementan con el lanzamiento de “SID-SLAM”, el software que contiene todas nuestras contribuciones, y del “Minimal Texture dataset”.Nuestra primera contribución es un algoritmo para la selección de puntos basado en Teoría de la Información para sistemas RGB-D VO/SLAM basados en métodos directos y/o en características visuales (features). El objetivo es seleccionar las medidas más informativas, para reducir el tama˜no del problema de optimización con un impacto mínimo en la precisión. Nuestros resultados muestran que nuestro nuevo criterio permitereducir el número de puntos hasta tan sólo 24 de ellos, alcanzando la precisión del estado del arte y reduciendo en hasta 10 veces la demanda computacional.El desarrollo de mejores modelos de incertidumbre para las medidas visuales mejoraría la precisión de la estructura y movimiento multi-vista y llevaría a estimaciones más realistas de la incertidumbre del estado en VO/SLAM. En esta tesis derivamos un modelo de covarianza para residuos multi-vista, que se convierte en un elemento crucial de nuestras contribuciones basadas en Teoría de la Información.La odometría visual y los sistemas de SLAM se dividen típicamente en la literatura en dos categorías, los basados en features y los métodos directos, dependiendo del tipo de residuos que son minimizados. En la última parte de la tesis combinamos nuestras dos contribucionesanteriores en la formulación e implementación de SID-SLAM, el primer sistema completo de SLAM semi-directo RGB-D que utiliza de forma integrada e indistinta features y métodos directos, en un sistema completo dirigido con información. Adicionalmente, grabamos ‘‘Minimal Texture”, un dataset RGB-D con un contenido visual conceptualmente simple pero arduo, con un ground truth preciso para facilitar la investigación del estado del arte en SLAM semi-directo.In the last years, we have witnessed an impressive progress in the accuracy and robustness of Visual Odometry (VO) and Simultaneous Localization and Mapping (SLAM). This boost in the performance has enabled the first commercial implementations related to augmented reality (AR), virtual reality (VR) and robotics. In this thesis, we developed new probabilistic methods to further improve the accuracy, robustness and efficiency of VO and SLAM. The contributions of our work are issued in three main publications and complemented with the release of SID-SLAM, the software containing all our contributions, and the challenging Mininal Texture dataset. Our first contribution is an information-theoretic approach to point selection for direct and/or feature-based RGB-D VO/SLAM. The aim is to select only the most informative measurements, in order to reduce the optimization problem with a minimal impact in the accuracy. Our experimental results show that our novel criteria allows us to reduce the number of tracked points down to only 24 of them, achieving state-of-the-art accuracy while reducing 10x the computational demand. Better uncertainty models for visual measurements will impact the accuracy of multi-view structure and motion and will lead to realistic uncertainty estimates of the VO/SLAM states. We derived a novel model for multi-view residual covariances based on perspective deformation, which has become a crucial element in our information-driven approach. Visual odometry and SLAM systems are typically divided in the literature into two categories, feature-based and direct methods, depending on the type of residuals that are minimized. We combined our two previous contributions in the formulation and implementation of SID-SLAM, the first full semi-direct RGB-D SLAM system that uses tightly and indistinctly features and direct methods within a complete information-driven pipeline. Moreover, we recorded Minimal Texture an RGB-D dataset with conceptually simple but challenging content, with accurate ground truth to facilitate state-of-the-art research on semi-direct SLAM.<br /

Advancing efficiency and robustness of neural networks for imaging

Enabling machines to see and analyze the world is a longstanding research objective. Advances in computer vision have the potential of influencing many aspects of our lives as they can enable machines to tackle a variety of tasks. Great progress in computer vision has been made, catalyzed by recent progress in machine learning and especially the breakthroughs achieved by deep artificial neural networks. Goal of this work is to alleviate limitations of deep neural networks that hinder their large-scale adoption for real-world applications. To this end, it investigates methodologies for constructing and training deep neural networks with low computational requirements. Moreover, it explores strategies for achieving robust performance on unseen data. Of particular interest is the application of segmenting volumetric medical scans because of the technical challenges it imposes, as well as its clinical importance. The developed methodologies are generic and of relevance to a broader computer vision and machine learning audience. More specifically, this work introduces an efficient 3D convolutional neural network architecture, which achieves high performance for segmentation of volumetric medical images, an application previously hindered by high computational requirements of 3D networks. It then investigates sensitivity of network performance on hyper-parameter configuration, which we interpret as overfitting the model configuration to the data available during development. It is shown that ensembling a set of models with diverse configurations mitigates this and improves generalization. The thesis then explores how to utilize unlabelled data for learning representations that generalize better. It investigates domain adaptation and introduces an architecture for adversarial networks tailored for adaptation of segmentation networks. Finally, a novel semi-supervised learning method is proposed that introduces a graph in the latent space of a neural network to capture relations between labelled and unlabelled samples. It then regularizes the embedding to form a compact cluster per class, which improves generalization.Open Acces

Bathrooms as a Homeless Rights Issue

Bathrooms are a bellwether of equality. Segregated bathrooms were at the center of the Civil Rights Movement. Accessible bathrooms were at the heart of the Disability Rights Movement. Now, gender-neutral bathrooms or bathrooms assigned by gender, rather than sex, are at the heart of the Transgender Rights Movement. This Article is the first to examine the right to access bathrooms as it relates to the homeless community. The Article explores the current paradox where cities, counties, and states provide few, if any, public bathrooms for the homeless community and the public at large while criminalizing public urination and defecation. To better understand this paradox, the Article contains two original multijurisdictional surveys. The first reviews the prohibitions on public urination and defecation in the ten municipalities with the most homeless individuals. The second explores the Freedom of Information Act and Public Record Act responses of those municipalities to requests for information regarding the public bathrooms they operate and potential barriers to use for homeless individuals (e.g., closing in the evenings or particular seasons, charging a fee for entry, being located in buildings requiring identification for entry, etc.). The Article contextualizes the paradox in relation to human dignity, public health, and the historical use of bathroom access as an exercise of power. It contends that the current scheme denies homeless individuals a basic sense of dignity, while undermining the health and safety justification for prohibitions on public urination and defecation by failing to operate public restrooms. The Article further argues that government actors use bathrooms to marginalize the homeless community in the same way that they have used them to marginalize women, people of color, individuals with disabilities, and transgender individuals. In exploring this use of power, the Article argues that prohibitions on public urination and defecation are part of a larger trend of criminalizing homelessness and the evolution of segregation. Finally, the Article evaluates potential solutions to the paradox. The solutions reviewed include increasing the availability and accessibility of public restrooms, leveraging private industry, and reforming or challenging the law. The Article concludes that any long-term solution to the problem requires an examination of the paradox through the lens of the homeless community

Inertial-aided Visual Perception of Geometry and Semantics

We describe components of a visual perception system to understand the geometry and semantics of the three-dimensional scene by utilizing monocular cameras and inertial measurement units (IMUs). The use of the two sensor modalities is motivated by the wide availability of the camera-IMU sensor packages present in mobile devices from phones to cars, and their complementary sensing capabilities: IMUs can track the motion of the sensor platform over a short period of time accurately, and provide a scaled and gravity-aligned global reference frame, while cameras can capture rich photometric signatures of the scene, and provide relative motion constraints between images up to scale. We first show that visual 3D reconstruction can be improved by leveraging the global orientation frame -- easily inferred from inertials. In the gravity-aligned global orientation frame, a shape prior can be imposed in depth prediction from a single image, where the normal vectors to surfaces of objects of certain classes tend to align with gravity or orthogonal to it. Adding such a prior to baseline methods for monocular depth prediction yields improvements beyond the state-of-the-art and illustrates the power of utilizing inertials in 3D reconstruction. The global reference provided by inertials is not only gravity-aligned but also scaled, which is exploited in depth completion: We describe a method to infer dense metric depth from camera motion and sparse depth as estimated using a visual-inertial odometry system. Unlike other scenarios using point clouds from lidar or structured light sensors, we have few hundreds to few thousand points, insufficient to inform the topology of the scene. Our method first constructs a piecewise planar scaffolding of the scene, and then uses it to infer dense depth using the image along with the sparse points. We use a predictive cross-modal criterion, akin to “self-supervision,” measuring photometric consistency across time, forward-backward pose consistency, and geometric compatibility with the sparse point cloud. We also launch the first visual-inertial + depth dataset (dubbed ``VOID''), which we hope will foster additional exploration into combining the complementary strengths of visual and inertial sensors. To compare our method to prior work, we adopt the unsupervised KITTI depth completion benchmark, and show state-of-the-art performance on it.In addition to dense geometry, the camera-IMU sensor package can also be used to recover the semantics of the scene. We present two methods to augment a point cloud map with class-labeled objects represented in the form of either scaled and oriented bounding boxes or CAD models. The tradeoff of the two shape representation resides in their generality and capability to model detailed structures. While being more generic, 3D bounding boxes fail to model the details of the objects, whereas CAD models preserve the finest shape details but require more computation and are limited to previously seen objects. Nevertheless, both methods populate an unknown environment with 3D objects placed in a Euclidean reference frame inferred causally and on-line using monocular video along with inertial sensors. Besides, both methods include bottom-up and top-down components, whereby deep networks trained for detection provide likelihood scores for object hypotheses provided by a nonlinear filter, whose state serves as memory. We test our methods on KITTI and SceneNN datasets, and also introduce the VISMA dataset, which contains ground truth pose, point-cloud map, and object models, along with time-stamped inertial measurements.To reduce the drift of the visual-inertial SLAM system -- a building block of all the visual perception systems we have built, we introduce an efficient loop closure detection approach based on the idea of hierarchical pooling of image descriptors. We also open-sourced a full-fledged SLAM system equipped with mapping and loop closure capabilities. The code is publicly available at https://github.com/ucla-vision/xivo

National Geographics: Toward a “Federalism Function” of American Tort Law

This Article will situate the federalism function among existing scholarly frameworks and assess the “contoured” approach to federal and state power balancing across the existing subject matter of torts. Part II will assess conflicting characterizations of tort law as on one hand “private” and on the other “public” law. Part III will define and explain competing functions of tort law with an eye to whether federalism fits the common criteria of these coexisting objectives, goals, purposes, and methods for adjudication. In Part IV, the Article will explore historical and contemporary roles of federalism to understand why this process becomes so deeply implicated in the resolution of civil justice claims. Part V will explore patterns in modern tort federalization to draw observations about the way this process partakes in American nationhood and legal culture. Its first subpart explores federalization in the name of constitutional rights initially with respect to free speech in the theories of defamation, privacy, and emotional distress. It then looks to federalization under due process jurisprudence in public takings and civil damage awards. The second subpart reviews federal preemption—the displacement of state common law actions by express or implied national legislative purpose. That discussion will take the reader through preemption approaches in transportation and auto safety, food and drug regulation, environmental protection, and employment claims. Although jurisprudence across these discrete industries has cross-pollinated in recent decades, viewing them serially in this fashion, hopefully, will make better sense of the sociocultural logics underpinning preemption—even if the rules themselves still appear quite nebulous today. Finally, Part VI will offer a discussion of these various substantive areas to support the general proposition that current struggles to balance state and federal authority—the federalism function—form a legitimate new policy function of torts today

The Medvedev years : an examination of the external forces & internal dynamics affecting the Kremlin's foreign policy decisions

The central question of this thesis is what forces and personal dynamics ultimately shape the Kremlin’s responses to foreign policy issues. The legacies of Mikhail Gorbachev and Boris Yeltsin are traced from the Soviet democratization during the 1980’s and the constitutional empowerment of the Russian presidency during the 1990’s. These two coexistent forces of empowering the average citizen in a country in which the President is the most powerful authority in decision-making are examined.The forces of the Kremlin affect the current inner circle of Siloviki, Technocrats, and Yeltsin Liberals who are integral members of the policy formulation. Vladimir Putin and his handpicked successor, Dmitry Medvedev, were now at the helm of a government with these three groups of bureaucrats from 2008 to 2012. The Medvedev presidency was confronted with challenges in the post-Soviet space, which included Georgian military operations against Russia and an anti-Russian leader in Kyrgyzstan. In addition to this, the Kremlin was faced with the decisions to enforce sanctions against rogue regimes pursuing nuclear capability, specifically Iran and North Korea. The Arab Spring of 2011 brought with it momentous change in the Middle East and the Russian Federation was forced to decide whether to consent to sanctions against the Khadafy regime in Libya and the Assad regime in Syria.The six foreign policy decisions in this thesis illuminate the Kremlin’s internal dynamics as well as the handling of the external political forces enacted by Mikhail Gorbachev and Boris Yeltsin. Graham Allison’s Governmental Politics Model, which analyzes foreign policy from a personal perspective of the chief decision-makers, is used throughout this body of doctoral research

Information Bottleneck

The celebrated information bottleneck (IB) principle of Tishby et al. has recently enjoyed renewed attention due to its application in the area of deep learning. This collection investigates the IB principle in this new context. The individual chapters in this collection: • provide novel insights into the functional properties of the IB; • discuss the IB principle (and its derivates) as an objective for training multi-layer machine learning structures such as neural networks and decision trees; and • offer a new perspective on neural network learning via the lens of the IB framework. Our collection thus contributes to a better understanding of the IB principle specifically for deep learning and, more generally, of information–theoretic cost functions in machine learning. This paves the way toward explainable artificial intelligence

Ways of escape : modern transformations of leisure and travel

This thesis challenges the conventional assumptions that leisure and travel are associated with experience of freedom and escape. It argues that leisure behaviour has been shaped by programmes of moral regulation. The thesis argues that these programmes are deeply rooted. For comparative purposes, moral regulation in the middle ages and the sixteenth and seventeenth centuries are discussed. However, the main historical focus is on moral regulation in bourgeois society. It is argued that bourgeois culture sought to divide modern society into segments of experience: Private life was divided from public life, work from leisure, the female role from the male role, the bourgeois class from the working class, and so forth. The underlying aim behind these divisions was self realization. Through the `rational' bourgeois ordering of things it was hoped that the individual would maximize his or her capacities. Leisure and travel were part of the programme of self making. So far from being `free activities' they were self conscious activities geared to the aim of self realization. This thesis argues that there was a contradiction between the ambition of bourgeois culture which was to create a permanent rational order of things, and the action of modernity, which operated to neutralize or overturn bourgeois divisions. This contradiction is explored in the second chapter where the leisure of bourgeois women is discussed. The chapter attacks the feminist orthodoxy in the sociology of leisure which maintains that women's influence in leisure and travel is negligible. It examines the experience of bourgeois women in the nineteenth and early twentieth centuries. It submits that modernity operated not merely to subordinate women but also to activate them. Examples of the influence of women in shaping the aesthetics of metropolitan culture are discussed to illustrate the point. The thesis maintains that modernity is still the essential context for understanding leisure and travel experience. Chapter three attempts to compare modernity and postmodernity. In chapters four and five examples of leisure and travel forms in the last twenty five years are discussed in order to test the fashionable postmodern proposition that we have now moved into a condition of postmodernity. The thesis closes with an attempt to drawn the main themes of the thesis together. It reassesses the contradiction between the ambition of bourgeois society and the action of modernity. It concludes that the debate on modernity and postmodernity does not suggest the emergence of a new social condition. Rather its main effect has been to help us to understand the action of modernity more clearly