32,568 research outputs found
Multi-touch 3D Exploratory Analysis of Ocean Flow Models
Modern ocean flow simulations are generating increasingly complex, multi-layer 3D ocean flow models. However, most researchers are still using traditional 2D visualizations to visualize these models one slice at a time. Properly designed 3D visualization tools can be highly effective for revealing the complex, dynamic flow patterns and structures present in these models. However, the transition from visualizing ocean flow patterns in 2D to 3D presents many challenges, including occlusion and depth ambiguity. Further complications arise from the interaction methods required to navigate, explore, and interact with these 3D datasets. We present a system that employs a combination of stereoscopic rendering, to best reveal and illustrate 3D structures and patterns, and multi-touch interaction, to allow for natural and efficient navigation and manipulation within the 3D environment. Exploratory visual analysis is facilitated through the use of a highly-interactive toolset which leverages a smart particle system. Multi-touch gestures allow users to quickly position dye emitting tools within the 3D model. Finally, we illustrate the potential applications of our system through examples of real world significance
Reuleaux: Robot Base Placement by Reachability Analysis
Before beginning any robot task, users must position the robot's base, a task
that now depends entirely on user intuition. While slight perturbation is
tolerable for robots with moveable bases, correcting the problem is imperative
for fixed-base robots if some essential task sections are out of reach. For
mobile manipulation robots, it is necessary to decide on a specific base
position before beginning manipulation tasks.
This paper presents Reuleaux, an open source library for robot reachability
analyses and base placement. It reduces the amount of extra repositioning and
removes the manual work of identifying potential base locations. Based on the
reachability map, base placement locations of a whole robot or only the arm can
be efficiently determined. This can be applied to both statically mounted
robots, where position of the robot and work piece ensure the maximum amount of
work performed, and to mobile robots, where the maximum amount of workable area
can be reached. Solutions are not limited only to vertically constrained
placement, since complicated robotics tasks require the base to be placed at
unique poses based on task demand.
All Reuleaux library methods were tested on different robots of different
specifications and evaluated for tasks in simulation and real world
environment. Evaluation results indicate that Reuleaux had significantly
improved performance than prior existing methods in terms of time-efficiency
and range of applicability.Comment: Submitted to International Conference of Robotic Computing 201
Morphing a Stereogram into Hologram
This paper develops a simple and fast method to reconstruct reality from
stereoscopic images. We bring together ideas from robust optical flow
techniques, morphing deformations and lightfield 3D rendering in order to
create unsupervised multiview images of a scene. The reconstruction algorithm
provides a good visualization of the virtual 3D imagery behind stereograms upon
display on a headset-free Looking Glass 3D monitor. We discuss the possibility
of applying the method for live 3D streaming optimized via an associated lookup
table.Comment: PDF, 8 pages, 4 Fig
Weakly supervised 3D Reconstruction with Adversarial Constraint
Supervised 3D reconstruction has witnessed a significant progress through the
use of deep neural networks. However, this increase in performance requires
large scale annotations of 2D/3D data. In this paper, we explore inexpensive 2D
supervision as an alternative for expensive 3D CAD annotation. Specifically, we
use foreground masks as weak supervision through a raytrace pooling layer that
enables perspective projection and backpropagation. Additionally, since the 3D
reconstruction from masks is an ill posed problem, we propose to constrain the
3D reconstruction to the manifold of unlabeled realistic 3D shapes that match
mask observations. We demonstrate that learning a log-barrier solution to this
constrained optimization problem resembles the GAN objective, enabling the use
of existing tools for training GANs. We evaluate and analyze the manifold
constrained reconstruction on various datasets for single and multi-view
reconstruction of both synthetic and real images
Pycortex: an interactive surface visualizer for fMRI.
Surface visualizations of fMRI provide a comprehensive view of cortical activity. However, surface visualizations are difficult to generate and most common visualization techniques rely on unnecessary interpolation which limits the fidelity of the resulting maps. Furthermore, it is difficult to understand the relationship between flattened cortical surfaces and the underlying 3D anatomy using tools available currently. To address these problems we have developed pycortex, a Python toolbox for interactive surface mapping and visualization. Pycortex exploits the power of modern graphics cards to sample volumetric data on a per-pixel basis, allowing dense and accurate mapping of the voxel grid across the surface. Anatomical and functional information can be projected onto the cortical surface. The surface can be inflated and flattened interactively, aiding interpretation of the correspondence between the anatomical surface and the flattened cortical sheet. The output of pycortex can be viewed using WebGL, a technology compatible with modern web browsers. This allows complex fMRI surface maps to be distributed broadly online without requiring installation of complex software
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