Literatura académica sobre el tema "Object properties estimation"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Consulte las listas temáticas de artículos, libros, tesis, actas de conferencias y otras fuentes académicas sobre el tema "Object properties estimation".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Artículos de revistas sobre el tema "Object properties estimation"
El-Dawy, Ahmed, Amr El-Zawawi y Mohamed El-Habrouk. "MonoGhost: Lightweight Monocular GhostNet 3D Object Properties Estimation for Autonomous Driving". Robotics 12, n.º 6 (17 de noviembre de 2023): 155. http://dx.doi.org/10.3390/robotics12060155.
Texto completoYang, Hua, Takeshi Takaki y Idaku Ishii. "Simultaneous Dynamics-Based Visual Inspection Using Modal Parameter Estimation". Journal of Robotics and Mechatronics 23, n.º 1 (20 de febrero de 2011): 180–95. http://dx.doi.org/10.20965/jrm.2011.p0180.
Texto completoMavrovouniotis, Michael L., Suzanne Prickett y Leonidas Constantinou. "Object-oriented estimation of properties from molecular structure". Computers & Chemical Engineering 16 (mayo de 1992): S353—S360. http://dx.doi.org/10.1016/s0098-1354(09)80042-2.
Texto completoTang, Jie y Jian Li. "End-to-End Monocular Range Estimation for Forward Collision Warning". Sensors 20, n.º 20 (21 de octubre de 2020): 5941. http://dx.doi.org/10.3390/s20205941.
Texto completoImran, Abid, Sang-Hwa Kim, Young-Bin Park, Il Hong Suh y Byung-Ju Yi. "Singulation of Objects in Cluttered Environment Using Dynamic Estimation of Physical Properties". Applied Sciences 9, n.º 17 (28 de agosto de 2019): 3536. http://dx.doi.org/10.3390/app9173536.
Texto completoHeczko, Dominik, Petr Oščádal, Tomáš Kot, Adam Boleslavský, Václav Krys, Jan Bém, Ivan Virgala y Zdenko Bobovský. "Finding the Optimal Pose of 2D LLT Sensors to Improve Object Pose Estimation". Sensors 22, n.º 4 (16 de febrero de 2022): 1536. http://dx.doi.org/10.3390/s22041536.
Texto completoCoenen, M., F. Rottensteiner y C. Heipke. "DETECTION AND 3D MODELLING OF VEHICLES FROM TERRESTRIAL STEREO IMAGE PAIRS". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (31 de mayo de 2017): 505–12. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-505-2017.
Texto completoPapadaki, Alexandra y Maria Pateraki. "6D Object Localization in Car-Assembly Industrial Environment". Journal of Imaging 9, n.º 3 (20 de marzo de 2023): 72. http://dx.doi.org/10.3390/jimaging9030072.
Texto completoZarepour, Mohammad Saleh. "AVICENNA ON GRASPING MATHEMATICAL CONCEPTS". Arabic Sciences and Philosophy 31, n.º 1 (marzo de 2021): 95–126. http://dx.doi.org/10.1017/s0957423920000090.
Texto completoFreitas, Vander Luis de Souza, Barbara Maximino da Fonseca Reis y Antonio Maria Garcia Tommaselli. "AUTOMATIC SHADOW DETECTION IN AERIAL AND TERRESTRIAL IMAGES". Boletim de Ciências Geodésicas 23, n.º 4 (diciembre de 2017): 578–90. http://dx.doi.org/10.1590/s1982-21702017000400038.
Texto completoTesis sobre el tema "Object properties estimation"
Fathollahi, Ghezelghieh Mona. "Estimation of Human Poses Categories and Physical Object Properties from Motion Trajectories". Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/6835.
Texto completoPandharkar, Rohit (Rohit Prakash). "Hidden object doppler : estimating motion, size and material properties of moving non-line-of-sight objects in cluttered environments". Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/67783.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (p. 111-117).
The thesis presents a framework for Non-Line-of-Sight Computer Vision techniques using wave fronts. Using short-pulse illumination and a high speed time-of-flight camera, we propose algorithms that use multi path light transport analysis to explore the environments beyond line of sight. What is moving around the corner interests everyone including a driver taking a turn, a surgeon performing laparoscopy and a soldier entering enemy base. State of the art techniques that do range imaging are limited by (i) inability to handle multiple diffused bounces [LIDAR] (ii) Wavelength dependent resolution limits [RADAR] and (iii) inability to map real life objects [Diffused Optical Tomography]. This work presents a framework for (a) Imaging the changing Space-time-impulse-responses of moving objects to pulsed illumination (b) Tracking motion along with absolute positions of these hidden objects and (c) recognizing their default properties like material and size and reflectance. We capture gated space-time impulse responses of the scene and their time differentials allow us to gauge absolute positions of moving objects with knowledge of only relative times of arrival (as absolute times are hard to synchronize at femto second intervals). Since we record responses at very short time intervals we collect multiple readings from different points of illumination and thus capturing multi-perspective responses allowing us to estimate reflectance properties. Using this, we categorize and give parametric models of the materials around corner. We hope this work inspires further exploration of NLOS computer vision techniques.
by Rohit Pandharkar.
S.M.
Chareyre, Maxime. "Apprentissage non-supervisé pour la découverte de propriétés d'objets par découplage entre interaction et interprétation". Electronic Thesis or Diss., Université Clermont Auvergne (2021-...), 2023. http://www.theses.fr/2023UCFA0122.
Texto completoRobots are increasingly used to achieve tasks in controlled environments. However, their use in open environments is still fraught with difficulties. Robotic agents are likely to encounter objects whose behaviour and function they are unaware of. In some cases, it must interact with these elements to carry out its mission by collecting or moving them, but without knowledge of their dynamic properties it is not possible to implement an effective strategy for resolving the mission.In this thesis, we present a method for teaching an autonomous robot a physical interaction strategy with unknown objects, without any a priori knowledge, the aim being to extract information about as many of the object's physical properties as possible from the interactions observed by its sensors. Existing methods for characterising objects through physical interactions do not fully satisfy these criteria. Indeed, the interactions established only provide an implicit representation of the object's dynamics, requiring supervision to identify their properties. Furthermore, the proposed solution is based on unrealistic scenarios without an agent. Our approach differs from the state of the art by proposing a generic method for learning interaction that is independent of the object and its properties, and can therefore be decoupled from the prediction phase. In particular, this leads to a completely unsupervised global pipeline.In the first phase, we propose to learn an interaction strategy with the object via an unsupervised reinforcement learning method, using an intrinsic motivation signal based on the idea of maximising variations in a state vector of the object. The aim is to obtain a set of interactions containing information that is highly correlated with the object's physical properties. This method has been tested on a simulated robot interacting by pushing and has enabled properties such as the object's mass, shape and friction to be accurately identified.In a second phase, we make the assumption that the true physical properties define a latent space that explains the object's behaviours and that this space can be identified from observations collected through the agent's interactions. We set up a self-supervised prediction task in which we adapt a state-of-the-art architecture to create this latent space. Our simulations confirm that combining the behavioural model with this architecture leads to the emergence of a representation of the object's properties whose principal components are shown to be strongly correlated with the object's physical properties.Once the properties of the objects have been extracted, the agent can use them to improve its efficiency in tasks involving these objects. We conclude this study by highlighting the performance gains achieved by the agent through training via reinforcement learning on a simplified object repositioning task where the properties are perfectly known.All the work carried out in simulation confirms the effectiveness of an innovative method aimed at autonomously discovering the physical properties of an object through the physical interactions of a robot. The prospects for extending this work involve transferring it to a real robot in a cluttered environment
Taati, BABAK. "Generation and Optimization of Local Shape Descriptors for Point Matching in 3-D Surfaces". Thesis, 2009. http://hdl.handle.net/1974/5107.
Texto completoThesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2009-09-01 11:07:32.084
Capítulos de libros sobre el tema "Object properties estimation"
Bader, Markus. "Chapter 2. How free is the position of German object pronouns?" En Studies in Language Companion Series, 22–47. Amsterdam: John Benjamins Publishing Company, 2023. http://dx.doi.org/10.1075/slcs.234.02bad.
Texto completoYao, Wei y Jianwei Wu. "Airborne LiDAR for Detection and Characterization of Urban Objects and Traffic Dynamics". En Urban Informatics, 367–400. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8983-6_22.
Texto completoIvanov, Sergey S. "“Counter—Scaling” Method for Estimation of Fractal Properties of Self—Affine Objects". En Fractals and Dynamic Systems in Geoscience, 391–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-662-07304-9_30.
Texto completoFugl, Andreas Rune, Andreas Jordt, Henrik Gordon Petersen, Morten Willatzen y Reinhard Koch. "Simultaneous Estimation of Material Properties and Pose for Deformable Objects from Depth and Color Images". En Lecture Notes in Computer Science, 165–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32717-9_17.
Texto completoSidorkina, Irina y Aleksey Rуbakov. "Creating Model of E-Course". En Handbook of Research on Estimation and Control Techniques in E-Learning Systems, 286–97. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9489-7.ch019.
Texto completoDospisil, Jana. "Software Metrics, Information and Entropy". En Practicing Software Engineering in the 21st Century, 116–42. IGI Global, 2003. http://dx.doi.org/10.4018/978-1-93177-750-6.ch009.
Texto completoChernyshenko, Serge V. "Design of Avatars With “Differential” Logic". En Avatar-Based Control, Estimation, Communications, and Development of Neuron Multi-Functional Technology Platforms, 121–31. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1581-5.ch006.
Texto completo"Probability and Statistics". En Examining an Operational Approach to Teaching Probability, 301–30. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-3871-5.ch009.
Texto completoConnolly, Andrew J., Jacob T. VanderPlas, Alexander Gray, Andrew J. Connolly, Jacob T. VanderPlas y Alexander Gray. "Classification". En Statistics, Data Mining, and Machine Learning in Astronomy. Princeton University Press, 2014. http://dx.doi.org/10.23943/princeton/9780691151687.003.0009.
Texto completoGouda, Maha, Mostafa Atiaa y Omar Abdel-Kareem. "Investigation and Analysis of Ancient Dyed Textiles". En Preservation and Restoration Techniques for Ancient Egyptian Textiles, 93–118. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-4811-0.ch005.
Texto completoActas de conferencias sobre el tema "Object properties estimation"
Avant, Trevor y Kristi A. Morgansen. "Observability Properties of Object Pose Estimation". En 2019 American Control Conference (ACC). IEEE, 2019. http://dx.doi.org/10.23919/acc.2019.8814791.
Texto completoLiu, T., A. Klotzsche, M. Pondkule, H. Vereecken, J. van der Kruk y Y. Su. "Estimation of subsurface cylindrical object properties from GPR full-waveform inversion". En 2017 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR). IEEE, 2017. http://dx.doi.org/10.1109/iwagpr.2017.7996064.
Texto completoAhola, Jari M. y Tapio Heikkilä. "Object Recognition and Pose Estimation Based on Combined Use of Projection Histograms and Surface Fitting". En ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-67315.
Texto completoKurrant, Douglas J. y Elise C. Fear. "Estimation of regional geometric and spatially averaged dielectric properties of an object". En 2012 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting. IEEE, 2012. http://dx.doi.org/10.1109/aps.2012.6348049.
Texto completoPavlic, Marko, Timo Markert, Sebastian Matich y Darius Burschka. "RobotScale: A Framework for Adaptable Estimation of Static and Dynamic Object Properties with Object-dependent Sensitivity Tuning". En 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). IEEE, 2023. http://dx.doi.org/10.1109/ro-man57019.2023.10309315.
Texto completoPetsch, Susanne y Darius Burschka. "Estimation of spatio-temporal object properties for manipulation tasks from observation of humans". En 2010 IEEE International Conference on Robotics and Automation (ICRA 2010). IEEE, 2010. http://dx.doi.org/10.1109/robot.2010.5509885.
Texto completoTanaka, M., S. Amari y T. Horiuchi. "MODELLING OF PERCEPTUAL GLOSS UNDER MIXED LIGHTING CONDITIONS". En CIE 2023 Conference. International Commission on Illumination, CIE, 2023. http://dx.doi.org/10.25039/x50.2023.po174.
Texto completoCretu, Ana-Maria, Emil M. Petriu, Pierre Payeur y Fouad F. Khalil. "Estimation of deformable object properties from shape and force measurements for virtualized reality applications". En 2010 IEEE International Workshop on Haptic Audio Visual Environments and Games (HAVE 2010). IEEE, 2010. http://dx.doi.org/10.1109/have.2010.5623970.
Texto completoMurooka, Masaki, Shunichi Nozawa, Yohei Kakiuchi, Kei Okada y Masayuki Inaba. "Feasibility evaluation of object manipulation by a humanoid robot based on recursive estimation of the object's physical properties". En 2017 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2017. http://dx.doi.org/10.1109/icra.2017.7989469.
Texto completoSeacat, R. H., Harrison H. Barrett, R. L. Shoemaker, T. J. Roney y W. J. Smith. "Parallel processor for optimization and estimation problems: algorithms". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1988. http://dx.doi.org/10.1364/oam.1988.fo3.
Texto completo