Optical Flow Tutorial
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Variational Methods
Author: Maïtine Bergounioux
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2017-01-11
With a focus on the interplay between mathematics and applications of imaging, the first part covers topics from optimization, inverse problems and shape spaces to computer vision and computational anatomy. The second part is geared towards geometric control and related topics, including Riemannian geometry, celestial mechanics and quantum control. Contents: Part I Second-order decomposition model for image processing: numerical experimentation Optimizing spatial and tonal data for PDE-based inpainting Image registration using phase・amplitude separation Rotation invariance in exemplar-based image inpainting Convective regularization for optical flow A variational method for quantitative photoacoustic tomography with piecewise constant coefficients On optical flow models for variational motion estimation Bilevel approaches for learning of variational imaging models Part II Non-degenerate forms of the generalized Euler・Lagrange condition for state-constrained optimal control problems The Purcell three-link swimmer: some geometric and numerical aspects related to periodic optimal controls Controllability of Keplerian motion with low-thrust control systems Higher variational equation techniques for the integrability of homogeneous potentials Introduction to KAM theory with a view to celestial mechanics Invariants of contact sub-pseudo-Riemannian structures and Einstein・Weyl geometry Time-optimal control for a perturbed Brockett integrator Twist maps and Arnold diffusion for diffeomorphisms A Hamiltonian approach to sufficiency in optimal control with minimal regularity conditions: Part I Index
Handbook of Mathematical Models in Computer Vision
Author: Nikos Paragios
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-01-16
Abstract Biological vision is a rather fascinating domain of research. Scientists of various origins like biology, medicine, neurophysiology, engineering, math ematics, etc. aim to understand the processes leading to visual perception process and at reproducing such systems. Understanding the environment is most of the time done through visual perception which appears to be one of the most fundamental sensory abilities in humans and therefore a significant amount of research effort has been dedicated towards modelling and repro ducing human visual abilities. Mathematical methods play a central role in this endeavour. Introduction David Marr's theory v^as a pioneering step tov^ards understanding visual percep tion. In his view human vision was based on a complete surface reconstruction of the environment that was then used to address visual subtasks. This approach was proven to be insufficient by neuro-biologists and complementary ideas from statistical pattern recognition and artificial intelligence were introduced to bet ter address the visual perception problem. In this framework visual perception is represented by a set of actions and rules connecting these actions. The emerg ing concept of active vision consists of a selective visual perception paradigm that is basically equivalent to recovering from the environment the minimal piece information required to address a particular task of interest.
Using Robots in Hazardous Environments
There have been major recent advances in robotic systems that can replace humans in undertaking hazardous activities in demanding or dangerous environments. Published in association with the CLAWAR (Climbing and Walking Robots and Associated Technologies Association) (www.clawar.org), this important book reviews the development of robotic systems for de-mining and other risky activities such as fire-fighting.Part one provides an overview of the use of robots for humanitarian de-mining work. Part two discusses the development of sensors for mine detection whilst Part thee reviews developments in both teleoperated and autonomous robots. Building on the latter, Part four concentrates on robot autonomous navigation. The final part of the book reviews research on multi-agent-systems (MAS) and the multi-robotics-systems (MRS), promising tools that take into account modular design of mobile robots and the use of several robots in multi-task missions.With its distinguished editors and international team of contributors, Using robots in hazardous environments: landmine detection, de-mining and other applications is a standard reference for all those researching the use of robots in hazardous environments as well as government and other agencies wishing to use robots for dangerous tasks such as landmine detection and disposal. - Reviews the development of robotic systems for de-mining and other risky activities - Discusses the development and applications of sensors for mine detection using different robotic systems - Examines research on multi-agent-systems and multi-robotics systems