金出 武雄 (Takeo Kanade)
所属
履歴
1976年 同 助教授
1980年 カーネギーメロン大学 計算機科学科・ロボット研究所高等研究員
1985年 同教授
1992〜2001年 カーネギーメロン大学ロボティクス研究所 所長
1993年 カーネギーメロン大学 U.A. and Helen Whitaker 記念教授
1998年 カーネギーメロン大学 U.A. and Helen Whitaker 記念全学教授
2001年 産業技術総合研究所 デジタルヒューマン研究ラボ ラボ長（非常勤）
2003年 産業技術総合研究所 デジタルヒューマン研究センター センター長（非常勤）
2006年 カーネギーメロン大学 生活の質工学研究センター設立 センター長
受賞
- National Academy of Engineering 外国特別会員
- American Academy of Arts and Science Fellow
- IEEE、ACM、American Association of Artificial Intelligence、情報通信学会、ロボット学会の各学会フェロー
- C & C 賞
- Joseph Engelberger 賞
- FIT 業績賞
- JARA 賞
- 人工知能学会業績賞
- Otto Franc 賞
- Marr 賞
- フランクリン協会、バウアー賞
- IEEE 国際計算機視覚会議 Azriel Rosenfeld Lifetime Achievement Award
- 大川情報通信基金、大川賞
- IEEE ロボットとアートメーション・ソサイティ パイオニア賞
研究テーマ
・Computer Vision
Within the Image Understanding (IU) project, my students and I are conducting basic
research in interpretation and sensing for computer
vision. My major thrust is the "science of computer vision." Traditionally,
many computer vision algorithms were derived heuristically either
by introspection or biological analogy. In contrast, my approach to vision is to
transform the physical, geometrical, optical and statistical
processes, which underlie vision, into mathematical and computational models. This
approach results in algorithms that are far more
powerful and revealing than traditional ad hoc methods based solely on heuristic
knowledge. With this approach we have developed a new
class of algorithms for color, stereo, motion, and texture.
The two most successful examples of this approach are the factorization method and
the multi-baseline stereo method. The factorization
method is for the robust recovering of shape and motion from an image sequence.
Based on this theory we have been developing a system
for "modeling by video taping"; a user takes a video tape of a scene or
an object by either moving a camera or moving the object, and then
from the video a three-dimensional model of the scene or the object is created.
The multi-baseline stereo method, the second example,
is a new stereo theory that uses multi-image fusion for creating a dense depth map
of a natural scene. Based on this theory, a video-rate
stereo machine has been developed, which can produce a 200x200 depth image at 30
frames/sec, aligned with an intensity image;
in other words, a real 3D camera!!
Currently, we are working on a rapidly trainable object recognition method, a system
for modeling-by-video-taping,
and a multi-camera 3D object copying/reconstruction method.
・Visual media technology for human-computer interaction
A combination of computer vision and computer graphics technology presents an opportunity
for a new exciting visual media. We have
been developing a new visual medium, named "virtualized reality." In the
existing visual medium, the view of the scene is determined at the
transcription time, independent of the viewer. In contrast, the virtualized reality
delays the selection of the viewing angle till view time,
using techniques from computer vision and computer graphics. The visual event is
captured using many cameras that cover the action from
all sides. The 3D structure of the event, aligned with the pixels of the image,
is computed for a few selected directions using the
multi-baseline stereo technique. Triangulation and texture mapping enable the placement
of a soft-camera to reconstruct the event from
any new viewpoint. The viewer, wearing a stereo-viewing system, can freely move
about in the world and observe it from a viewpoint
chosen dynamically at view time. We have built a 3D Virtualized Studio using a hemispherical
dome, 5 meters in diameter, currently
with 51 cameras attached at its nodes.
There are many applications of virtualized reality. Virtualized reality starts with
a real world, rather than creating an artificial model of it. So,
training can become safer, more real and more effective. A surgery, recorded in
a virtualized reality studio, could be revisited by medical
students repeatedly, viewing it from positions of their choice. Or, an entirely
new generation of entertainment media can be
developed - "Let's watch NBA in the court": basketball enthusiasts could
watch a game from inside the court, from a referee's point of view,
or even from the "ball's eye" point of view.
A Virtualized Reality application, CBS's Eye Vision, was demonstrated during SuperBowl XXXV.
Also, I am interested in and currently working on vision techniques for recognizing
facial expression, gaze, and hand-finger gestures.
Such techniques will provide natural non-intrusive means for human-computer interface
by replacing current clumsy mechanical devices,
such as datagloves.
・Informedia Project
With the growth and popularity of multimedia computing technologies, video is gaining
importance and broadening its uses in libraries.
Digital video libraries open up great potentials for education, training and entertainment;
but to achieve this potential, the information
embedded within the digital video library must be easy to locate, manage and use.
Searches within a large data set or lengthy video would
take a user through vast amounts of material irrelevant to the search topic. The
typical database, which searches by keywords (e.g. title) - where
images are only referenced and not directly searched for - is not appropriate or
useful for the digital video library, since it does not provide
the user a way to know the contents of the image, short of viewing it. New techniques
are needed to organize these vast video collections so that
users can effectively retrieve and browse their holdings based on their content.
The Informedia Digital Video Library, funded by NSF, ARPA,
and NASA, is developing intelligent, automatic mechanisms to populate the video
library and allow for a full-content knowledge-based search,
retrieval and presentation of video. The distinguishing feature of Informedia's
approach is the integrated application of speech, language and
image understanding technologies.
・Computational Sensor
While significant advancements have been made over the last 30 years of computer
vision research, the consistent paradigm has been that a "camera"
sees the world and a computer "algorithm" recognizes the object. I have
been undertaking a project with Dr. Vladimir Brajovic that breaks away from
this traditional paradigm by integrating sensing and processing into a single VLSI
chip a computational sensor. The first successful example was
an ultra fast range sensor which can produce approximately 1000 frames of range
images per second an improvement of two orders of magnitude
over the state of the art. A few new sensors are being developed including a sorting
sensor chip, a 2D salient feature detector
(2D winner-take-all circuits), and others.
・Medical Robotics and Computer Assisted Surgery
The emerging field of Medical Robotics and Computer Assisted Surgery strives to
develop smart tools to perform medical procedures better
than either a physician or machine could alone. Robotic and computer-based systems
are now being applied in specialties that range from
neurosurgery and laparoscopy to opthalmology and family practice. Robots are able
to perform precise and repeatable tasks that would
be impossible for any human. The physician provides these systems with the decision
making skills and adaptable dexterity that are well beyond
current technology. The potential combination of robots and physicians has created
a new worldwide interest in the area of medical robotics.
We have developed a new computer assisted surgical systems for total hip replacement.
The work is based on biomechanics-based surgical
simulations and less invasive and more accurate vision-based techniques for determining
the position of the patient anatomy during a robot
surgery. The developed system, HipNav, has been already test -used in clinical setting.
・Vision-based Autonomous Helicopter
An unmanned helicopter can take maximum advantage of the high maneuverability of
helicopters in dangerous support tasks, such as search and rescue,
and fire fighting, since it does not place a human pilot in danger. The CMU Vision-Guided
Helicopter Project (with Dr. Omead Amidi) has been
developing the basic technologies for an unmanned autonomous helicopter including
robust control methods, vision algorithms for
real-time object detection and tracking, integration of GPS, motion sensors, vision
output for robust positioning, and high-speed real-time
hardware. After having tested various control algorithms and real-time vision algorithms
using an electric helicopter on an indoor teststand,
we have developed a computer controlled helicopter (4 m long), which carries two
CCD cameras, GPS, gyros and accelerometers together
with a multiprocessor computing system. Autonomous outdoor free flight has been
demonstrated with such capabilities as following
prescribed trajectory, detecting an object, and tracking or picking it from the
air.