6,142 research outputs found
Unwind: Interactive Fish Straightening
The ScanAllFish project is a large-scale effort to scan all the world's
33,100 known species of fishes. It has already generated thousands of
volumetric CT scans of fish species which are available on open access
platforms such as the Open Science Framework. To achieve a scanning rate
required for a project of this magnitude, many specimens are grouped together
into a single tube and scanned all at once. The resulting data contain many
fish which are often bent and twisted to fit into the scanner. Our system,
Unwind, is a novel interactive visualization and processing tool which
extracts, unbends, and untwists volumetric images of fish with minimal user
interaction. Our approach enables scientists to interactively unwarp these
volumes to remove the undesired torque and bending using a piecewise-linear
skeleton extracted by averaging isosurfaces of a harmonic function connecting
the head and tail of each fish. The result is a volumetric dataset of a
individual, straight fish in a canonical pose defined by the marine biologist
expert user. We have developed Unwind in collaboration with a team of marine
biologists: Our system has been deployed in their labs, and is presently being
used for dataset construction, biomechanical analysis, and the generation of
figures for scientific publication
Continuum modelling and simulation of granular flows through their many phases
We propose and numerically implement a constitutive framework for granular
media that allows the material to traverse through its many common phases
during the flow process. When dense, the material is treated as a pressure
sensitive elasto-viscoplastic solid obeying a yield criterion and a plastic
flow rule given by the inertial rheology of granular materials. When
the free volume exceeds a critical level, the material is deemed to separate
and is treated as disconnected, stress-free media. A Material Point Method
(MPM) procedure is written for the simulation of this model and many
demonstrations are provided in different geometries. By using the MPM
framework, extremely large strains and nonlinear deformations, which are common
in granular flows, are representable. The method is verified numerically and
its physical predictions are validated against known results
Conformational Dynamics of Supramolecular Protein Assemblies in the EMDB
The Electron Microscopy Data Bank (EMDB) is a rapidly growing repository for
the dissemination of structural data from single-particle reconstructions of
supramolecular protein assemblies including motors, chaperones, cytoskeletal
assemblies, and viral capsids. While the static structure of these assemblies
provides essential insight into their biological function, their conformational
dynamics and mechanics provide additional important information regarding the
mechanism of their biological function. Here, we present an unsupervised
computational framework to analyze and store for public access the
conformational dynamics of supramolecular protein assemblies deposited in the
EMDB. Conformational dynamics are analyzed using normal mode analysis in the
finite element framework, which is used to compute equilibrium thermal
fluctuations, cross-correlations in molecular motions, and strain energy
distributions for 452 of the 681 entries stored in the EMDB at present. Results
for the viral capsid of hepatitis B, ribosome-bound termination factor RF2, and
GroEL are presented in detail and validated with all-atom based models. The
conformational dynamics of protein assemblies in the EMDB may be useful in the
interpretation of their biological function, as well as in the classification
and refinement of EM-based structures.Comment: Associated online data bank available at:
http://lcbb.mit.edu/~em-nmdb
DeepSketch2Face: A Deep Learning Based Sketching System for 3D Face and Caricature Modeling
Face modeling has been paid much attention in the field of visual computing.
There exist many scenarios, including cartoon characters, avatars for social
media, 3D face caricatures as well as face-related art and design, where
low-cost interactive face modeling is a popular approach especially among
amateur users. In this paper, we propose a deep learning based sketching system
for 3D face and caricature modeling. This system has a labor-efficient
sketching interface, that allows the user to draw freehand imprecise yet
expressive 2D lines representing the contours of facial features. A novel CNN
based deep regression network is designed for inferring 3D face models from 2D
sketches. Our network fuses both CNN and shape based features of the input
sketch, and has two independent branches of fully connected layers generating
independent subsets of coefficients for a bilinear face representation. Our
system also supports gesture based interactions for users to further manipulate
initial face models. Both user studies and numerical results indicate that our
sketching system can help users create face models quickly and effectively. A
significantly expanded face database with diverse identities, expressions and
levels of exaggeration is constructed to promote further research and
evaluation of face modeling techniques.Comment: 12 pages, 16 figures, to appear in SIGGRAPH 201
Morphological shape generation through user-controlled group metamorphosis
Morphological shape design is interpreted in this paper as a search for new shapes from a particular application domain represented by a set of selected shape instances. This paper proposes a new foundation for morphological shape design and generation. In contrast to existing generative procedures, an approach based on a user-controlled metamorphosis between functionally based shape models is presented. A formulation of the pairwise metamorphosis is proposed with a variety of functions described for the stages of deformation, morphing and offsetting. This formulation is then extended to the metamorphosis between groups of shapes with user-defined, dynamically correlated and weighted feature elements. A practical system was implemented in the form of plugin to Maya and tested by an industrial designer on a group of representative shapes from a particular domain. Ā© 2013 Elsevier Ltd
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