Face Modeling, Expression Analysis, Caricature
Reconstructed
3D model
uncalibrated
images
automated caricature
Model detail enhancement
Expression analysis from region models
0. Frontalis L
1. Frontalis C
2. Frontalis R
3. Corrugator
4. Orbicularis Occuli L
5. Orbicularis Occuli R
6. Levator Palpebrae L
7. Levator Palpebrae R
8. Levator Nasii
9. Zygomatic Major L
10. Zygomatic Major R
11. Risorius L
12. Risorius R
13. Triangularis L
14. Triangularis R
15. Mentalis
CR
Muscles
0
1
2
3
4
5
6
7
8
0
1, 3
2
4, 6
5, 7
9, 11, 13
10, 12, 14
15
8
Figure 1: (left) List of analyzed muscle groups and their locations and directions of contraction. (right)
Mixed Reality and Visualization



Augmented Reality for Space Flight (NASA)

Develop AR authoring tools for video-based training

Anthony Majoros, Human Factors group, The Boeing Corp
4D Visualization (MURI-ARMY)

Develop fusion of video, images, and 3D models

Avideh Zakhor (Berkeley), Suresh Lodha (UC Santa Cruz),
Bill Ribarsky (Georgia Tech), Pramod Varshney (Syracuse)
Wide Area AR Tracking (ONR)

Novel sensors & fusion for tracking position/orientation
AVE Problem
Imagine dozens (100’s) of video/data streams from people,
UAVs, and robot sensors distributed and moving
through a scene…
 Problem: visualization as separate streams/images
provides no integration of information, no high-level
scene comprehension, and obstructs collaboration
Information Management (IM)



Distributed streaming media systems
 P2P storage, indexing, and retrieval (YIMA+)
 Formal analysis and design of P2P systems using complex
systems theory
Multidimensional databases and data streams
 Progressive & approximate (wavelet-based) query
evaluation
 Spatio-temporal capabilities
 Real-time analysis of sensor data streams
 Music (MIDI) stream analysis
Semantic information representation
 Use of dynamic ontologies to represent information about
objects in immersispace
 Use of information semantics for customized experiences