Environmental monitoring applications require seamless registration of optical data into large area mosaics that are geographically
referenced to the world frame. Using frame-by-frame image registration alone, we can obtain seamless mosaics, but it will
not exhibit geographical accuracy due to frame-to-frame error accumulation. On the other hand, the 3D geo-data from GPS, a
laser profiler, an INS system provides a globally correct track of the motion without error propagation. However, the inherent
(absolute) errors in the instrumentation are large for seamless mosaicing. The paper describes an effective two-track method
for combining two different sources of data to achieve a seamless and geo-referenced mosaic, without 3D reconstruction or
complex global registration. Experiments with real airborne video images show that the proposed algorithms are practical in
important environmental applications.
Zhigang Zhu received his B.E., M.E. and Ph.D. degrees, all in computer science from Tsinghua University, Beijing, in 1988, 1991 and 1997,
respectively. He is currently an associate professor in the Department of Computer Science, the City College of the City University
of New York. Previously, he was an associate professor at Tsinghua University, and a senior research fellow at the University
of Massachusetts, Amherst. His research interests include 3D computer vision, HCI, virtual/augmented reality, video representation,
and various applications in education, environment, robotics, surveillance and transportation. He has published over 90 technical
papers in the related fields. He is a member of IEEE and ACM.
Edward M. Riseman received his B.S. degree from Clarkson College of Technology in 1964 and his M.S. and Ph.D. degrees in electrical engineering
from Cornell University in 1966 and 1969, respectively. He joined the Computer Science Department at UMass-Amherst as assistant
professor in 1969, has been a professor since 1978, and served as chairman of the department from 1981 to 1985. Professor
Riseman has conducted research in computer vision, artificial intelligence, learning, and pattern recognition, and has more
than 200 publications. He has co-directed the Computer Vision Laboratory since its inception in 1975. Professor Riseman has
been on the editorial boards of Computer Vision and Image Understanding (CVIU) from 1992 to 1997 and of the International Journal of Computer Vision (IJCV) from 1987 to the present. He is a senior member of IEEE, and a fellow of AAAI.
Allen R. Hanson received his B.S. degree from Clarkson College of Technology in 1964 and his M.S. and Ph.D. degrees in electrical engineering
from Cornell University in 1966 and 1969, respectively. He joined the Computer Science Department at UMass-Amherst as an associate
professor in 1981, and has been a professor there since 1989. Professor Hanson has conducted research in computer vision,
artificial intelligence, learning, and pattern recognition, and has more than 150 publications. He is co-director of the Computer
Vision Laboratory at UMass-Amherst, and has been on the editorial boards of the following journals: Computer Vision, Graphics and Image Processing 1983–1990, Computer Vision, Graphics, and Image Processing—Image Understanding 1991–1994, and Computer Vision and Image Understanding 1995–present.
Howard Schultz received a M.S. degree in physics from UCLA in 1974 and a Ph.D. in physical oceanography from the University of Michigan
in 1982. Currently, he is a senior research fellow with the Computer Science Department at the University of Massachusetts,
Amherst. His research interests include quantitative methods for image understanding and remote sensing. The current focus
of his research activities are on developing automatic techniques for generating complex, 3D models from sequences of images.
This research has found application in a variety of programs including real-time terrain modeling and video aided navigation.
He is a member of the IEEE, the American Geophysical Union, and the American Society of Photogrammetry and Remote Sensing.