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Papers - Saito, Hideo

Division display 121 - 140 of about 356 ／ All the affair displays >>

Specular 3D Object Tracking by View Generative Learning

Yukiko Shinozuka, Francois de Sorbier and Hideo Saito

Proc. 2014 Irish Machine Vision and Image Processing (IMVIP2014) 9 - 14 2014.08

Research paper (international conference proceedings), Joint Work, Accepted

Combination Method: Photometric Stereo with Shadows

A. Dulac, S. Martedi, H. Saito, K. Tezuka and M. Shimizu

Proc. 2014 Irish Machine Vision and Image Processing (IMVIP2014) 137 - 142 2014.08

Research paper (international conference proceedings), Joint Work, Accepted

Human Trajectory Tracking Using a Single Omnidirectional Camera

A. Kawasaki, D. Hung and H. Saito

Proc. 2014 Irish Machine Vision and Image Processing (IMVIP2014) 157 - 162 2014.08

Research paper (international conference proceedings), Joint Work, Accepted

Accurate Camera Pose Estimation for KinectFusion Based on Line Segment Matching by LEHF

Yusuke Nakayama, Toshihiro Honda, Hideo Saito, Masayoshi Shimizu,and Nobuyasu Yamaguchi Accurate Camera Pose Estimation for KinectFusion

Proceedings of the 2014 22nd International Conference on Pattern Recognition (IEEE Computer Society Washington, DC, USA) 2149 - 2154 2014.08

Research paper (international conference proceedings), Joint Work, Accepted, ISSN 978-1-4799-5209-0

Access to Document (DOI)

Camera Pose Estimation for Mixed and Diminished Reality in FTV

Hideo Saito, Toshihiro Honda, Yusuke Nakayama, Francois de Sorbier

3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON), 2014 (IEEE) 2014.07

Research paper (international conference proceedings), Joint Work, Accepted

Access to Document (DOI)

RGB-Dカメラによる環境の3次元計測に基づく実時間隠消現実感

SAITO HIDEO

日本バーチャルリアリティ学会論文誌 (日本バーチャルリアリティ学会) 19 ( 2 ) 105 - 116 2014.06

Research paper (scientific journal), Joint Work, Accepted, ISSN 1344011X

Dynamic learning, retrieval, and tracking to augment hundreds of photographs

Julien Pilet, Hideo Saito

Virtual Reality (Springer London) 18 ( 2 ) 89 - 100 2014.06

Research paper (scientific journal), Joint Work, Accepted, ISSN 1434-9957

In this paper, we present a method that combines the speed and accuracy of tracking with the scalability of image retrieval. At the heart of our approach is a bi-layer clustering process that allows our system to index and retrieve objects based on tracks of features, thereby effectively summarizing the information available on multiple video frames. Dynamic learning of new viewpoints as the camera moves naturally yields the kind of robustness and reliability expected from an augmented reality engine. As a result, our system is able to track in real-time multiple objects, recognized with low delay from a database of more than 300 entries. We released the source code of our system in a package called Polyora.

Access to Document (DOI)

Rapid Feedback of Table Tennis Ball Trajectory with Unsynchronized Cameras

Sho Tamaki, Hideo Saito

Proc. International Association of Computer Science in Sports 2014 Conference 39 - 45 2014.06

Research paper (international conference proceedings), Joint Work, Accepted

Virtual rope slider

Tatsuya Kodera, Naoto Tani, Jun Morita, Naoya Maeda, Kazuna Tsuboi, Motoko Kanegae, Yukiko Shinozuka, Sho Shimamura, Kadoki Kubo, Yusuke Nakayama, Jaejun Lee, Maxime Pruneau, Hideo Saito, Maki Sugimoto

Proceedings of the 2014 Virtual Reality International Conference ( Article No. 36 ) 2014.04

Research paper (international conference proceedings), Joint Work, Accepted

Access to Document (DOI)

Virtual Slicer: Interactive visualizer for tomographic medical images based on position and orientation of handheld device

Sho Shimamura, Motoko Kanegae, Yuji Uema, Masahiko Inami, Tetsu Hayashida, Hideo Saito, and Maki Sugimoto

Proceedings of the 2014 Virtual Reality International Conference ( Article No. 12 ) 2014.04

Research paper (international conference proceedings), Joint Work, Accepted

This paper introduces an interface that helps understand the
correspondence between the patient and medical images.
Surgeons determine the extent of resection by using tomographic
images such as MRI (Magnetic Resonance Imaging) data
.
However, understanding the relationship between the patient and
tomographic images is di
ffi
cult. This study aims to visualize the
correspond
en
ce more intuitive
ly
.
In this paper, we propose an
interactive visualizer for medical images based on the relative
position and orientation of the handheld device and the patient.
We conducted an experiment to verify the performances of the
proposed method and several other methods. In the experiment,
t
he
proposed method showed the minimum error.

Access to Document (DOI)

Sharing 3D object with multiple clients via networks using vision-based 3D object tracking

Yukiko Shinozuka and Hideo Saito

Proceedings of the 2014 Virtual Reality International Conference ( Article No. 34 ) 2014.04

Research paper (international conference proceedings), Joint Work, Accepted

This paper proposes a new system for 3D object sharing with
multiple clients using networks. Our system aims to support group
communication across devices over the same 3D object and puts
the annotations with augmented reality automatically. In order to
keep putting the annotations during the interaction, we apply the
vision-based 3D object tracking algorithm which estimates 3D
position and pose of the object just by capturing the object with a
single RGB camera. By employing the tracking algorithm robust
to viewpoint changes and occlusion, we develop the 3D object
sharing system with a desktop as a server and a laptop and a smart
phone as clients. We conducted the experiments to show the
tracking algorithm is tolerant of interaction and can be applied to
various objects with texture.

Access to Document (DOI)

An AR edutainment system supporting bone anatomy learning

Wucherer, P. ; Oyamada, Y. ; Ma, M. ; Schoch, A. ; Kanegae, M. ; Shimizu, N. ; Kodera, T. ; Cahier, S. ; Weigl, M. ; Sugimoto, M. ; Fallavollita, P. ; SAITO HIDEO ; Navab, N.

IEEE Virtual Reality (VR2014) 113 - 114 2014.03

Research paper (international conference proceedings), Joint Work, Accepted

We present a medical Augmented Reality (AR) edutainment system for bone anatomy learning. This learning environment, called AR bone puzzle, is a metaphor for bone anatomy learning with AR visualization and intuitive interaction. AR bone puzzle uses its user's body as a puzzle frame and computer generated virtual bones as puzzle pieces. Users learn bone anatomy by assembling the virtual bone pieces on their body. Key features of this system are 3D AR visualization and intuitive gesture based user interaction.

Access to Document (DOI)

Stereoscopic augmented reality with pseudo-realistic global illumination effects

Francois de Sorbier; Hideo Saito

Proc. SPIE. 9011, Stereoscopic Displays and Applications XXV 90111W 2014.03

Research paper (international conference proceedings), Accepted

Access to Document (DOI)

Joint upsampling and noise reduction for real-time depth map enhancement

Kazuki Matsumoto, Chiyoung Song, Francois de Sorbier, Hideo Saito

Proc. SPIE 9011, Stereoscopic Displays and Applications XXV 901120 2014.03

Research paper (international conference proceedings), Joint Work, Accepted

An efficient system that upsamples depth map captured by Microsoft Kinect while jointly reducing the effect of noise is presented. The upsampling is carried by detecting and exploiting the piecewise locally planar structures of the downsampled depth map, based on corresponding high-resolution RGB image. The amount of noise is reduced by accumulating the downsampled data simultaneously. By benefiting from massively parallel computing capability of modern commodity GPUs, the system is able to maintain high frame rate. Our system is observed to produce the upsampled depth map that is very close to the original depth map both visually and mathematically.

Access to Document (DOI)

A calibration method for performance analysis in table tennis

Sho Tamaki, Hideo Saito

Proc. 20th Korea-Japan Joint Workshop on Frontiers of Computer Vision 330 - 334 2014.02

Research paper (international conference proceedings), Joint Work, Accepted

3D Surface Reconstruction of a BGA Connector with Large Specular Highlightsby Photometric Stereo

Maxime Vallee, Hideo Saito, Junichi Sugano, Yoshinobu Takizawa

Proc. 20th Korea-Japan Joint Workshop on Frontiers of Computer Vision 2014.02

Research paper (international conference proceedings), Joint Work, Accepted

View Independent Vehicle Make and Model Recognition with Virtual Frontal View

Yukiko Shinozuka, Takuya Minagawa, Hideo Saito

IEEJ Transactions on Electronics, Information and Systems 134 ( 2 ) 233 - 241 2014.02

Research paper (scientific journal), Accepted

This paper proposes a novel view independent vehicle make and model recognition method (VMMR). Our system identifies the make and model from the variety of viewpoints while the conventional methods for VMMR work only for the fixed frontal or rear images. In addition, it needs only the 2D images not CAD data for database. To solve the alignment issue, our method uses SIFT, that has scale and rotation invariance. For the view independent recognition, it creates less distorted frontal view images by view morphing or homography matrix calculated by the position of the license plate and extracts the keypoints from them. Our method enables to recognize up to 60-degree angle with high accuracy due to the less distorted virtual frontal images.

Access to Document (DOI)

View Independent Recognition of Vehicle Make and Model from View Morphed Frontal Image

Yukiko Shinozuka, Takuya Minagawa, Hideo Saito

2014 Int. Workshop on Advanced Image Technology (IWAIT 2014) 451 - 455 2014.01

Research paper (international conference proceedings), Joint Work, Accepted

This paper proposes a novel view independent
vehicle make and model recognition method(VMMR). Our system
identifies the make and model from the variety of viewpoints while
the conventional methods for VMMR work only for the fixed
frontal or rear images. In addition, it needs only the 2D images
not CAD data for database. To solve the alignment issue, our
method uses SIFT, that has scale and rotation invariance. For the
view independent recognition, it creates the more realistic and less
distorted frontal view images by view morphing and extracts the
keypoints from them. Our method enables to recognize up to 40-
degree angle with high accuracy due to the less distorted morphed
images. Our method can be extended to the other product model
recognition.

Augmented reality system using a smartphone based on getting a 3D environment model in real-time with an RGB-D camera

Toshihiro Honda, Francois de Sorbier, and Hideo Saito

2014 Int. Workshop on Advanced Image Technology (IWAIT 2014) 355 - 359 2014.01

Research paper (international conference proceedings), Joint Work, Accepted

n this paper, we propose a system to achieve
Augmented Reality (AR) on a smartphone. In this system, we
assume a fixed RGB-D camera connected to a server is installed in
the environment, and perform AR based on the 3D environment
shape got by the RGB-D camera in real-time. On the smartphone
side, it sends the image captured by its camera, and receives
the output image processed to perform AR by the server. On
the server side, it sends back the image that virtual objects
are superimposed on. At this time, by constructing the 3D
environment model in real-time using the RGB-D camera, it is
possible to calculate the smartphone pose and the interaction
between the virtual objects and the environment properly. It is
also possible to change the lighting virtually. Our experiment
revealed it is possible to superimpose virtual objects on the
smartphone in approximately 8fps.

Real time relighting with dynamic light environment using an RGB-D camera

Takuya Ikeda, Francois de Sorbier, and Hideo Saito

2014 Int. Workshop on Advanced Image Technology (IWAIT 2014) 420 - 425 2014.01

Research paper (international conference proceedings), Joint Work, Accepted

elighting techniques often require knowledge
about the shape and the reflectance property of a target object
and the light environment. The quality of the relighting is highly
dependent on the normals accuracy of the object since they
are used for the computation of the illumination. We propose
a new relighting approach for arbitrary shaped objects with
dynamic light environment using an RGB-D camera such as
the Microsoft’s Kinect. The generated depth map is useful to
estimate the normals of the object, but it’s inaccurate because of
the noise such as discrete depth values or missing data. We focus
on the depth map modification to segment the accurate object
region, and normal estimation for relighting. Our implementation
achieves a relighting at 10fps with GPU. Therefore, our relighting
system can apply for a moving object and a dynamic light
environment in real time.

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