102 resultados para 3D action games
Resumo:
This work addresses the challenging problem of unconstrained 3D human pose estimation (HPE) from a novel perspective. Existing approaches struggle to operate in realistic applications, mainly due to their scene-dependent priors, such as background segmentation and multi-camera network, which restrict their use in unconstrained environments. We therfore present a framework which applies action detection and 2D pose estimation techniques to infer 3D poses in an unconstrained video. Action detection offers spatiotemporal priors to 3D human pose estimation by both recognising and localising actions in space-time. Instead of holistic features, e.g. silhouettes, we leverage the flexibility of deformable part model to detect 2D body parts as a feature to estimate 3D poses. A new unconstrained pose dataset has been collected to justify the feasibility of our method, which demonstrated promising results, significantly outperforming the relevant state-of-the-arts. © 2013 IEEE.
Resumo:
This paper presents an analytical model for the determination of the basic breakdown properties of three-dimensional (3D)-RESURF/CoolMOS/super junction type structures. To account for the two-dimensional (2D) effect of the 3D-RESURF action, 2D models of the electric field distribution are developed. Based on these, expressions are derived for the breakdown voltage as a function of doping concentration and physical dimensions. In addition to cases where the drift regions are fully depleted, the model developed is also applicable to situations involving drift regions which are almost depleted. Accuracy of the analytical approach is verified by comparison with numerical results obtained from the MEDICI device simulator.
Resumo:
Physical forces generated by cells drive morphologic changes during development and can feedback to regulate cellular phenotypes. Because these phenomena typically occur within a 3-dimensional (3D) matrix in vivo, we used microelectromechanical systems (MEMS) technology to generate arrays of microtissues consisting of cells encapsulated within 3D micropatterned matrices. Microcantilevers were used to simultaneously constrain the remodeling of a collagen gel and to report forces generated during this process. By concurrently measuring forces and observing matrix remodeling at cellular length scales, we report an initial correlation and later decoupling between cellular contractile forces and changes in tissue morphology. Independently varying the mechanical stiffness of the cantilevers and collagen matrix revealed that cellular forces increased with boundary or matrix rigidity whereas levels of cytoskeletal and extracellular matrix (ECM) proteins correlated with levels of mechanical stress. By mapping these relationships between cellular and matrix mechanics, cellular forces, and protein expression onto a bio-chemo-mechanical model of microtissue contractility, we demonstrate how intratissue gradients of mechanical stress can emerge from collective cellular contractility and finally, how such gradients can be used to engineer protein composition and organization within a 3D tissue. Together, these findings highlight a complex and dynamic relationship between cellular forces, ECM remodeling, and cellular phenotype and describe a system to study and apply this relationship within engineered 3D microtissues.
Resumo:
3D thermo-electro-mechanical device simulations are presented of a novel fully CMOS-compatible MOSFET gas sensor operating in a SOI membrane. A comprehensive stress analysis of a Si-SiO2-based multilayer membrane has been performed to ensure a high degree of mechanical reliability at a high operating temperature (e.g. up to 400°C). Moreover, optimisation of the layout dimensions of the SOI membrane, in particular the aspect ratio between the membrane length and membrane thickness, has been carried out to find the best trade-off between minimal device power consumption and acceptable mechanical stress.
Resumo:
A direct comparison between time resolved PLIF measurements of OH and two dimensional slices from a full three dimensional DNS data set of turbulent premixed flame kernels in lean methane/air mixture was presented. The local flame structure and the degree of flame wrinkling were examined in response to differing turbulence intensities and turbulent Reynolds numbers. Simulations were performed using the SEGA DNS code, which is based on the solution of the compressible Navier Stokes, species, and energy equations for a lean hydrocarbon mixture. For the OH PLIF measurements, a cluster of four Nd:YAG laser was fired sequentially at high repetition rates and used to pump a dye laser. The frequency doubled laser beam was formed into a sheet of 40 mm height using a cylindrical telescope. The combination of PLIF and DNS has been demonstrated as a powerful tool for flame analysis. This research will form the basis for the development of sub-grid-scale (SGS) models for LES of lean-premixed combustion systems such as gas turbines. This is an abstract of a paper presented at the 30th International Symposium on Combustion (Chicago, IL 7/25-30/2004).
Resumo:
A new liquid crystal device structure has been developed using a vertically grown Multi-Wall Carbon NanoTube (MWCNT) as a 3D electrode structure, which allows complicated phase only hologram to be displayed using conventional liquid crystal materials. The nanotubes act as an individual electrode sites that generate an electric field profile, dictating the refractive index profile with the liquid crystal cell. Changing the electric field applied makes it possible to tune the properties to modulate the light in an ideal kinoform. A perfect 3D image can be generated by a computer generated hologram by using the diffraction of the light from the hologram pixels to create an optical wave front that appears to come from 3D object. A multilevel phase modulating device based on nematic LC's is also under progress, which will be used with the LC/CNT devices on an LCOS backplane to project a full 3D image from the kinoform.
Restoration of images and 3D data to higher resolution by deconvolution with sparsity regularization