388,173 research outputs found

    Hyperspectral Modeling of Material Appearance: General Framework, Challenges and Prospects

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    The main purpose of this tutorial is to address theoretical and practical issues involved in the development of predictive material appearancemodels for interdisciplinary applications within and outside the visible spectral domain. We examine the specific constraints and pitfalls found in each of the key stages of the model development framework, namely data collection, design and evaluation, and discuss alternatives to enhance the effectiveness of the entire process. Although predictive material appearance models developed by computer graphics researchers are usually aimed at realistic image synthesis applications, they also provide valuable support for a myriad of advanced investigations in related areas, such as computer vision, image processing and pattern recognition, which rely on the accurate analysis and interpretation of material appearance attributes in the hyperspectral domain. In fact, their scope of contributions goes beyond the realm of traditional computer science applications. For example, predictive light transport simulations, which are essential for the development of these models, are also regularly beingused by physical and life science researchers to understand andpredict material appearance changes prompted by mechanisms which cannot be fully studied using standard ``wet'' experimental procedures.For completeness, this tutorial also provides an overview of such synergistic research efforts and in silico investigations, which are illustrated by case studies involving the use of hyperspectral material appearance models

    People detection based on appearance and motion models

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    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. A. Garcia-Martin, A. Hauptmann, and J. M. Martínez "People detection based on appearance and motion models", in 8th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2011, p. 256-260The main contribution of this paper is a new people detection algorithm based on motion information. The algorithm builds a people motion model based on the Implicit Shape Model (ISM) Framework and the MoSIFT descriptor. We also propose a detection system that integrates appearance, motion and tracking information. Experimental results over sequences extracted from the TRECVID dataset show that our new people motion detector produces results comparable to the state of the art and that the proposed multimodal fusion system improves the obtained results combining the three information sources.This work has been partially supported by the Cátedra UAM-Infoglobal ("Nuevas tecnologías de vídeo aplicadas a sistemas de video-seguridad") and by the Universidad Autónoma de Madrid (“FPI-UAM: Programa propio de ayudas para la Formación de Personal Investigador”

    The Evolution of Stop-motion Animation Technique Through 120 Years of Technological Innovations

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    Stop-motion animation history has been put on paper by several scholars and practitioners who tried to organize 120 years of technological innovations and material experiments dealing with a huge literature. Bruce Holman (1975), Neil Pettigrew (1999), Ken Priebe (2010), Stefano Bessoni (2014), and more recently AdriĂĄn Encinas Salamanca (2017), provided the most detailed even tough partial attempts of systematization, and designed historical reconstructions by considering specific periods of time, film lengths or the use of stop-motion as special effect rather than an animation technique. This article provides another partial historical reconstruction of the evolution of stop-motion and outlines the main events that occurred in the development of this technique, following criteria based on the innovations in the technology of materials and manufacturing processes that have influenced the fabrication of puppets until the present day. The systematization follows a chronological order and takes into account events that changed the technique of a puppets’ manufacturing process as a consequence of the use of either new fabrication processes or materials. Starting from the accident that made the French film-pioneer Georges MĂ©liĂšs discover the trick of the replacement technique at the end of the nineteenth century, the reconstruction goes through 120 years of experiments and films. “Build up” puppets fabricated by the Russian puppet animator Ladislaw Starevicz with insect exoskeletons, the use of clay puppets and the innovations introduced by LAIKA entertainment in the last decade such as Stereoscopic photography and the 3D computer printed replacement pieces, and then the increasing influence of digital technologies in the process of puppet fabrication are some of the main considered events. Technology transfers, new materials’ features, innovations in the way of animating puppets, are the main aspects through which this historical analysis approaches the previously mentioned events. This short analysis is supposed to remind and demonstrate that stop-motion animation is an interdisciplinary occasion of both artistic expression and technological experimentation, and that its evolution and aesthetic is related to cultural, geographical and technological issues. Lastly, if the technology of materials and processes is a constantly evolving field, what future can be expected for this cinematographic technique? The article ends with this open question and without providing an answer it implicitly states the role of stop-motion as a driving force for innovations that come from other fields and are incentivized by the needs of this specific sector

    The Usage and Evaluation of Anthropomorphic Form in Robot Design

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    There are numerous examples illustrating the application of human shape in everyday products. Usage of anthropomorphic form has long been a basic design strategy, particularly in the design of intelligent service robots. As such, it is desirable to use anthropomorphic form not only in aesthetic design but also in interaction design. Proceeding from how anthropomorphism in various domains has taken effect on human perception, we assumed that anthropomorphic form used in appearance and interaction design of robots enriches the explanation of its function and creates familiarity with robots. From many cases we have found, misused anthropomorphic form lead to user disappointment or negative impressions on the robot. In order to effectively use anthropomorphic form, it is necessary to measure the similarity of an artifact to the human form (humanness), and then evaluate whether the usage of anthropomorphic form fits the artifact. The goal of this study is to propose a general evaluation framework of anthropomorphic form for robot design. We suggest three major steps for framing the evaluation: 'measuring anthropomorphic form in appearance', 'measuring anthropomorphic form in Human-Robot Interaction', and 'evaluation of accordance of two former measurements'. This evaluation process will endow a robot an amount of humanness in their appearance equivalent to an amount of humanness in interaction ability, and then ultimately facilitate user satisfaction. Keywords: Anthropomorphic Form; Anthropomorphism; Human-Robot Interaction; Humanness; Robot Design</p

    Slim accretion disks: theory and observational consequences

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    Slim accretion disks idea emerged over 30 years ago as an answer to several unsolved problems. Since that time there was a tremendous increase in the amount of observational data where this model applies. However, many critical issues on the theoretical side remain unsolved, as they are inherently difficult. This is the issue of the disk stability under the radiation pressure, the role of the magnetic field in the energy transfer inside the disk and the formation (or not) of a warm corona, and outflows. Thus the progress has to be done both through further developments of the model and through the careful comparison to the observational data.Comment: Universe, in pres

    Complex Systems: A Survey

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    A complex system is a system composed of many interacting parts, often called agents, which displays collective behavior that does not follow trivially from the behaviors of the individual parts. Examples include condensed matter systems, ecosystems, stock markets and economies, biological evolution, and indeed the whole of human society. Substantial progress has been made in the quantitative understanding of complex systems, particularly since the 1980s, using a combination of basic theory, much of it derived from physics, and computer simulation. The subject is a broad one, drawing on techniques and ideas from a wide range of areas. Here I give a survey of the main themes and methods of complex systems science and an annotated bibliography of resources, ranging from classic papers to recent books and reviews.Comment: 10 page

    Measurement of ΜˉΌ\bar{\nu}_{\mu} and ΜΌ\nu_{\mu} charged current inclusive cross sections and their ratio with the T2K off-axis near detector

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    We report a measurement of cross section σ(ΜΌ+nucleus→Ό−+X)\sigma(\nu_{\mu}+{\rm nucleus}\rightarrow\mu^{-}+X) and the first measurements of the cross section σ(ΜˉΌ+nucleus→Ό++X)\sigma(\bar{\nu}_{\mu}+{\rm nucleus}\rightarrow\mu^{+}+X) and their ratio R(σ(Μˉ)σ(Îœ))R(\frac{\sigma(\bar \nu)}{\sigma(\nu)}) at (anti-)neutrino energies below 1.5 GeV. We determine the single momentum bin cross section measurements, averaged over the T2K Μˉ/Îœ\bar{\nu}/\nu-flux, for the detector target material (mainly Carbon, Oxygen, Hydrogen and Copper) with phase space restricted laboratory frame kinematics of ΞΌ\theta_{\mu}500 MeV/c. The results are σ(Μˉ)=(0.900±0.029(stat.)±0.088(syst.))×10−39\sigma(\bar{\nu})=\left( 0.900\pm0.029{\rm (stat.)}\pm0.088{\rm (syst.)}\right)\times10^{-39} and $\sigma(\nu)=\left( 2.41\ \pm0.022{\rm{(stat.)}}\pm0.231{\rm (syst.)}\ \right)\times10^{-39}inunitsofcm in units of cm^{2}/nucleonand/nucleon and R\left(\frac{\sigma(\bar{\nu})}{\sigma(\nu)}\right)= 0.373\pm0.012{\rm (stat.)}\pm0.015{\rm (syst.)}$.Comment: 18 pages, 8 figure
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