Author : Alexandre Gillet, Michel Sanner, Daniel Stoffler, and Arthur Olson
Computer Graphics and Applications, IEEE
Publication Date : March-April 2005 Volume : 25 , Issue:2 On page(s): 13 - 17
Speaker: Shau-Shiang Hung(洪紹祥)
advisor :Shu-Chen Cheng(鄭淑真)
Date : 2010/4/8
Outline
 Introduction
 Design of physical models
 Augmented reality interface
 Implementation
 Examples
 Evaluation
 Conclusions
Introduction 1/2
 With the prevalence of structural and genomic data,
molecular biology has become a human-guided,
computer-assisted endeavor
 Exploring scientific date
 Test scientists hypotheses
 As databases grow, as structure and process ,and as
software methods become more diverse
 Access and manipulation of digital information is
increasingly a critical issue
Introduction 2/2
 Develop an augmented reality (AR) system
 Visual 3D representations

Molecular structure、properties
 With tangible interaction environment

User can
 intuitively manipulate molecular models and interactions
 Easily change the representation shown
 Access information about molecular properties
Design of physical models 1/2
 Use Python Molecular Viewer (PMV)
 Create virtual objects
 Design tangible models
 Simplifying the integration of the models with the virtual
environment.
 PMV is software framework




Molecular surfaces
Extruded volumes
Backbone ribbons
Atomic ball-and-stick
 Show
 molecular shape in interaction
 Atomic details
Design of physical models 2/2
 PMV includes
 Generic 3D visualization component

A high level interface to the OpenGL library and its geometry
viewing application
 Add


all molecular modeling and visualization functionality
Output formats (.stl and .vrml) for the solid printers serve as
input
Augmented reality interface 1/2
 Use computer-based spatial tracking and rendering
method to enhance the physical models’ semantic
content and show dynamic properties.
 Combines real-world user and physical model
presence with computation models and data
 Approach is based on the widely used ARToolKit
 Calculate the real camera position and orientation
relative to physical marker in real time, allowing overlay
of virtual objects relative to the physical markers.
Marker
Augmented reality interface 2/2
 Add PyARTK
 Integrate ARToolKit with PMV to manage markers

Advantage:
 Streamline the design and display of models within the same
environment.
 Assigns the geometries, animations, and masks to specific AR
markers or sets of markers
 The interface comes with controls for :
 Computer graphic objects
 Camera operations
 Clipping
 Lighting controls
Implementation 1/2
 Integrating the physical models with the virtual
augmentation requires superpositioning the two
worlds into the same perceptual space
 There are a number of possible ways
 using a head-mounted display

the user sees video of the real-world scene and the
superimposed computer graphic information.
 Projecting the computer information onto the physical
model.
 But expense and imperfect performance
Camera
Implementation 2/2
 A simpler two-view Solution
 This configuration has proven to be an effective,
inexpensive, and portable solution.
Physical model
Computer –augmented scene
Examples 1/2
 HIV protease
Examples 2/2
 Superoxide dismutase (SOD)
Evaluation 1/1
 The first pilot test involved high school students from
the Biotech Academy program in Seattle
 The second pilot study with students from a collegelevel biochemistry class at the University of
Washington
 Produced a number of models for colleagues in our
institute for applications ranging from drug design to
assembly of large biomolecular complexes
 Received uniformly positive comments for enhanced
comprehension and communication of structural
characteristics.
Conclusions 1/1
 In our experience, we found that tangible molecular
models can provide several advantages over computer
visualizations alone. They produce a multisensory
engagement that includes visual, tactile, and
proprioceptive perceptual pathways for learning and
memory.
 Using PMV along with our system has proven to be a
fast and efficient approach to develop and test new
ideas.