English / Japanese
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Tomokazu Sato Associate professor e-mail: |
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March,
1977 |
Born
in Tanabe, Wakayama prefecture, Japan |
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1995
- 1999 |
Bachelor course student |
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1999
- 2001 |
Master course student |
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2001
- 2003 |
Doctor
course student |
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2003
- 2011 |
Assistant
professor of Nara Institute of Science and Technology, Japan |
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2010.3-2011.3 |
Guest
researcher of CMP in Czech Technical University in Prague |
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2011
- Present |
Associate
professor of Nara Institute of Science and Technology, Japan |
Researches interests:
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Structure from motion for omni-directional video |
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Abstract: Multi-camera type of omni-directional camera has advantages of high-resolution
and almost uniform resolution for any direction of view. In this research, an
extrinsic camera parameter recovery method for a moving omni-directional
multi-camera system (OMS) is proposed. First, we discuss a perspective
n-point (PnP) problem for an OMS, and then describe a practical method for
estimating extrinsic camera parameters from multiple image sequences obtained
by an OMS. The proposed method is based on using the shape-from-motion and
the PnP techniques. |
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Depth estimation for omni-directional video |
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Abstract: This paper proposes a
method for estimating depth from long-baseline image sequences captured by a precalibrated moving omni-directional
multi-camera system (OMS). Our idea for estimating an omni-directional
depth map is very simple; only counting interest points in images is
integrated with the framework of conventional multibaseline
stereo. Even by a simple algorithm, depth can be determined without computing
similarity measures such as SSD and NCC that have been used for traditional
stereo matching. The proposed method realizes robust depth estimation against
image distortions and occlusions with lower computational cost than
traditional multi-baseline stereo method. These advantages of our method are
fit for characteristics of omni-directional
cameras. |
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3D modeling from video images |
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Abstract: In this paper, we propose
a dense 3-D reconstruction method that first estimates extrinsic camera
parameters of a hand-held video camera, and then reconstructs a dense 3-D
model of a scene. In the first process, extrinsic camera parameters are
estimated by tracking a small number of predefined markers of known 3-D
positions and natural features automatically. Then, several hundreds dense depth maps obtained by multi-baseline
stereo are combined together in a voxel space. We can acquire a dense 3-D
model of the outdoor scene accurately by using several hundreds
input images captured by a handheld video camera. |
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Interactive 3D modeling with AR support |
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Abstract: In most of conventional
methods, some skills for adequately controlling the camera movement are
needed for users to obtain a good 3-D model. In this study, we propose an
interactive 3-D modeling interface in which special skills are not required.
This interface consists of “indication of camera movement” and “preview of reconstruction result.” In
experiments for subjective evaluation, we verify the usefulness of the
proposed 3D modeling interfaces. |
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Extrinisc camera parameter estimation using vision and GPS |
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Abstract: This paper describes a
method for estimating extrinsic camera parameters using both feature points
on an image sequence and sparse position data acquired by GPS. Our method is
based on a structure-from-motion technique but is enhanced by using GPS data
so as to minimize accumulative estimation errors. Moreover, the position data
are also used to remove mis-tracked features. The
proposed method allows us to estimate extrinsic parameters without
accumulative errors even from an extremely long image sequence. |
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Realtime image mosaicing |
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Abstract:This paper presents a real-time video mosaicing system that is one of practical applications of
mobile vision. To realize video mosaicing on an
actual mobile device, in our method, image features are automatically tracked
on the input images and 6-DOF camera motion parameters are estimated with a
fast and robust structure-from-motion algorithm. A preview of generating a
mosaic image is also rendered in real time to support the user. Our system is
basically for the flat targets, but the system also has the capability of 3-D
video mosaicing in which an unwrapped mosaic image
can be generated from a video image sequence of a curved document. |
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Feature-landmark based Geometric Registration |
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Abstract: In this research,
extrinsic camera parameters of video images are estimated from
correspondences between pre-constructed feature-landmarks and image features.
In order to achieve real-time camera parameter estimation, the number of matching candidates are reduced by using
priorities of landmarks that are determined from previously captured video
sequences. |
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Image inpainting using energy function |
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Abstract: Image inpainting is a technique for removing undesired visual
objects in images and filling the missing regions with plausible textures. In
this paper, in order to improve the image quality of completed texture, the
objective function is extended by allowing brightness changes of sample
textures and introducing spatial locality as an additional constraint. The
effectiveness of these extensions is successfully demonstrated by applying
the proposed method to one hundred images and comparing the results with
those obtained by the conventional methods. |
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Inpainting for 3-D model |
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Abstract: 3D mesh models generated
with range scanner or video images often have holes due to many occlusions by
other objects and the object itself. This paper proposes a novel method to fill
the missing parts in the incomplete models. The missing parts are filled by
minimizing the energy function, which is defined based on similarity of local
shape between the missing region and the rest of the object. The proposed
method can generate complex and consistent shapes in the missing region. |
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Omnidirectional telepresence syetem |
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Abstract: This paper describes a
novel telepresence system which enables users to
walk through a photorealistic virtualized environment by actual walking. To
realize such a system, a wide-angle high-resolution movie is projected on an
immersive multi-screen display to present users the virtualized environments
and a treadmill is controlled according to detected user’s locomotion. In
this study, we use an omnidirectional multi-camera system to acquire images
of a real outdoor scene. The proposed system provides users with rich sense
of walking in a remote site. |
My
doctor's thesis:
"Reconstruction of 3-D
Models of Outdoor Scenes Based on Estimating Extrinsic Camera Parameters from
Multiple Image Sequences", NAIST-IS-MT9951049, March 2003.
Complete list of published papers:
Click
this link to see all publications (Japanese papers are included).
Contact
information:
Tel:
+81-743-72-5291
FAX: +81-743-72-5299
Email: tomoka-s@is.naist.jp
Office: Building IS-B-314
Mailing address: 8916-5, Takayama, Ikoma, Nara, Japan