Faculty Profiles - OGAWARA Koichi

Published Papers - OGAWARA Koichi

Division display >> ／ All the affair displays1 - 58 of about 58

Improvements over Coordinate Regression Approach for Large-Scale Face Alignment

Haoqi Gao, Koichi Ogawara （Part： Last author,　Corresponding author )

IIEEJ Transactions on Image Electronics and Visual Computing 10 ( 1 ) 127 - 135 2022.06 [Refereed]

Face Reconstruction Algorithm based on Lightweight Convolutional Neural Networks and Channel-wise Attention

Haoqi Gao, Koichi Ogawara （Part： Last author,　Corresponding author )

IIEEJ Transactions on Image Electronics and Visual Computing 10 ( 1 ) 90 - 97 2022.06 [Refereed]

Segmentation and Shape Estimation of Multiple Deformed Cloths Using a CNN-Based Landmark Detector and Clustering," 2022 International Conference on Robotics and Automation (ICRA), 2022, pp. 7043-7049, doi: 10.1109/ICRA46639.2022.9811551

D. Sonegawa, K. Ogawara （Part： Last author,　Corresponding author )

2022 International Conference on Robotics and Automation 7043 - 7049 2022.05 [Refereed]

Face Alignment Using a GAN-based Photorealistic Synthetic Dataset

Haoqi Gao, Koichi Ogawara （Part： Last author )

2022 7th International Conference on Control and Robotics Engineering (ICCRE) ( IEEE ) 2022.04 [Refereed]

DOI

Face alignment by learning from small real datasets and large synthetic datasets

aoqi Gao, Koichi Ogawara （Part： Last author )

2022 Asia Conference on Cloud Computing, Computer Vision and Image Processing 2022.03 [Refereed]

Bidirectional Mapping Augmentation Algorithm for Synthetic Images Based on Generative Adversarial Network

Haoqi Gao, Koichi Ogawara （Part： Last author )

IIEEJ Transactions on Image Electronics and Visual Computing 8 ( 2 ) 110 - 120 2020.12 [Refereed]

Estimation of object class and orientation from multiple viewpoints and relative camera orientation constraints

Koichi Ogawara, Keita Iseki （Part： Lead author,　Corresponding author )

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ( IEEE ) 10588 - 10594 2020.10 [Refereed]

DOI

Generative adversarial network for bidirectional mappings between synthetic and real facial image

HAOQi GAO, Koichi Ogawara （Part： Last author )

Twelfth International Conference on Digital Image Processing (ICDIP 2020) ( SPIE ) 136 - 145 2020.06 [Refereed]

DOI

CGAN-based Synthetic Medical Image Augmentation between Retinal Fundus Images and Vessel Segmented Images

Gao HaoQi, Koichi Ogawara （Part： Last author )

2020 5th International Conference on Control and Robotics Engineering (ICCRE) ( IEEE ) 218 - 223 2020.04 [Refereed]

DOI

Seminar Report: the 105th Robotics Seminar

Ogawara Koichi

Journal of the Robotics Society of Japan ( The Robotics Society of Japan ) 35 ( 7 ) 536 - 537 2017

DOI

Development of Power Assist Suit for Supporting and Transporting Heavy Object with Single Motor

Tomoya Takeno, Ayano Murakami, Han Peng, Koichi Ogawara, Arata Suzuki, Kunitomo Kikuchi

2015 54TH ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS OF JAPAN (SICE) ( IEEE ) 1240 - 1243 2015 [Refereed]

Identification of people walking along curved trajectories

Yumi Iwashita, Koichi Ogawara, Ryo Kurazume

PATTERN RECOGNITION LETTERS ( ELSEVIER SCIENCE BV ) 48 60 - 69 2014.10 [Refereed]

Conventional methods of gait analysis for person identification use features extracted from a sequence of camera images taken during one or more gait cycles. The walking direction is implicitly assumed not to change. However, with the exception of very particular cases, such as walking on a circle centered on the camera, or along a line passing through the camera, there is always some degree of orientation change, most pronounced when the person is closer to the camera. This change in the angle between the velocity vector and the position vector in respect to the camera causes a decrease in performance for conventional methods. To address this issue we propose in this paper a new method, which provides improved identification in this context of orientation change. The proposed method uses a 4D gait database consisting of multiple 3D shape models of walking people and adaptive virtual image synthesis with high accuracy. Each frame, for the duration of a gait cycle, is used to estimate the walking direction of the subject, and a virtual image corresponding to the estimated direction is synthesized from the 4D gait database. The identification uses affine moment invariants as gait features. The efficiency of the proposed method is demonstrated through experiments using a database that includes 42 subjects. (C) 2014 Elsevier B. V. All rights reserved.

DOI

顔の部位識別に基づくマーカレスモーションキャプチャに関する研究

赤木康宏, 古川亮, 佐川立昌, 小川原光一, 川崎洋

精密工学会論文誌 79 ( 11 ) 1152 - 1158 2013.11 [Refereed]

A Voting-Based Sequential Pattern Recognition Method

Koichi Ogawara, Masahiro Fukutomi, Seiichi Uchida, Yaokai Feng （Part： Lead author )

PLOS ONE ( PUBLIC LIBRARY SCIENCE ) 8 ( 10 ) 2013.10 [Refereed]

We propose a novel method for recognizing sequential patterns such as motion trajectory of biological objects (i.e., cells, organelle, protein molecules, etc.), human behavior motion, and meteorological data. In the proposed method, a local classifier is prepared for every point (or timing or frame) and then the whole pattern is recognized by majority voting of the recognition results of the local classifiers. The voting strategy has a strong benefit that even if an input pattern has a very large deviation from a prototype locally at several points, they do not severely influence the recognition result; they are treated just as several incorrect votes and thus will be neglected successfully through the majority voting. For regularizing the recognition result, we introduce partial-dependency to local classifiers. An important point is that this dependency is introduced to not only local classifiers at neighboring point pairs but also to those at distant point pairs. Although, the dependency makes the problem non-Markovian (i.e., higher-order Markovian), it can still be solved efficiently by using a graph cut algorithm with polynomial-order computations. The experimental results revealed that the proposed method can achieve better recognition accuracy while utilizing the above characteristics of the proposed method.

DOI

Marker-less Facial Motion Capture based on the Parts Recognition.

Yasuhiro Akagi, Ryo Furukawa, Ryusuke Sagawa, Koichi Ogawara, Hiroshi Kawasaki

Journal of WSCG 21 ( 2 ) 137 - 144 2013 [Refereed]

Expanding gait identification methods from straight to curved trajectories

Yumi Iwashita, Ryo Kurazume, Koichi Ogawara

2013 IEEE WORKSHOP ON APPLICATIONS OF COMPUTER VISION (WACV) ( IEEE ) 193 - 199 2013 [Refereed]

Conventional methods of gait analysis for person identification use features extracted from a sequence of camera images taken during one or more gait cycles. An implicit assumption is made that the walking direction does not change. However, cameras deployed in real-world environments (and often placed at corners) capture images of humans who walk on paths that, for a variety of reasons, such as turning corners or avoiding obstacles, are not straight but curved. This change of the direction of the velocity vector causes a decrease in performance for conventional methods. In this paper we address this aspect, and propose a method that offers improved identification results for people walking on curved trajectories. The large diversity of curved trajectories makes the collection of complete real world data infeasible. The proposed method utilizes a 4D gait database consisting of multiple 3D shape models of walking subjects and adaptive virtual image synthesis. Each frame, for the duration of a gait cycle, is used to estimate a walking direction for the subject, and consequently a virtual image corresponding to this estimated direction is synthesized from the 4D gait database. The identification uses affine moment invariants as gait features. Experiments using the 4D gait database of 21 subjects show that the proposed method has a higher recognition performance than conventional methods.

A facial motion tracking and transfer method based on a key point detection

Yasuhiro Akagi, Ryo Furukawa, Ryusuke Sagawa, Koichi Ogawara, Hiroshi Kawasaki

WSCG 2013, COMMUNICATION PAPERS PROCEEDINGS ( UNION AGENCY SCIENCE PRESS ) 137 - 144 2013 [Refereed]

Facial animation is one of the most important contents in 3D CG animations. By the development of scanning and tracking methods of a facial motion, a face model which consists of more than 100,000 points can be used for the animations. To edit the facial animations, key point based approaches such as "face rigging" are still useful ways. Even if a facial tracking method gives us all point-to-point correspondences, a detection method of a suitable set of key points is needed for content creators. Then, we propose a method to detect the key points which efficiently represent motions of a face. We optimize the key points for a Radial Basis Function (RBF) based 3D deformation technique. The RBF based deformation is a common technique to represent a movement of 3D objects in CG animations. Since the key point based approaches usually deform objects by interpolating movements of the key points, these approaches cause errors between the deformed shapes and the original ones. To minimize the errors, we propose a method which automatically inserts additional key points by detecting the area where the error is larger than the surrounding area. Finally, by utilizing the suitable set of key points, the proposed method creates a motion of a face which are transferred form another motion of a face.

Non-Markovian Dynamic Time Warping

Seiichi Uchida, Masahiro Fukutomi, Koichi Ogawara, Yaokai Feng

2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012) ( IEEE ) 2294 - 2297 2012 [Refereed]

This paper proposes a new dynamic time warping (DTW) method, called non-Markovian DTW In the conventional DTW, the warping function is optimized generally by dynamic programming (DP) subject to some Markovian constraints which restrict the relationship between neighboring time points. In contrast, the non-Markovian DTW can introduce non-Markovian constraints for dealing with the relationship between points with a large time interval. This new and promising ability of DTW is realized by using graph cut as the optimizer of the warping function instead of DP. Specifically, the conventional DTW problem is first converted as an equivalent minimum cut problem on a graph and then edges representing the non-Markovian constraints are added to the graph. An experiment on online character recognition showed the advantage of using non-Markovian constraints during DTW.

Approximate Belief Propagation by Hierarchical Averaging of Outgoing Messages

OGAWARA Koichi （Part： Lead author )

20th International Conference on Pattern Recognition(ICPR) ( The Institute of Electronics, Information and Communication Engineers ) J94-D ( 3 ) 593 - 603 2011.03 [Refereed]

本論文では,ノードの出力メッセージをそのノードの全出力メッセージの平均値で置き換え,更に低解像度グラフから元のグラフへと階層的にメッセージを伝搬することにより,画像に対して適用した場合に通常の確率伝搬法と比較して計算時間を約2分の1から3分の1に,メモリ使用量を40%に削減可能な近似確率伝搬法を提案する.また,提案手法をCPU及びGPU上に実装し,Middleburyステレオデータセットを使用して通常の確率伝搬法と比較実験を行い,わずかな精度の低下と引換えに計算時間とメモリ使用量の両面において性能が大きく改善されたことを示す.

DOI

Detecting Frequent Patterns in Time Series Data using Partly Locality Sensitive Hashing

OGAWARA Koichi, TANABE Yasufumi, KURAZUME Ryo, HASEGAWA Tsutomu （Part： Lead author )

Journal of the Robotics Society of Japan ( The Robotics Society of Japan ) 29 ( 1 ) 67 - 76 2011.01 [Refereed]

Frequent patterns in time series data are useful clues to learn previously unknown events in an unsupervised way. In this paper, we propose a method for detecting frequent patterns in long time series data efficiently. The major contribution of the paper is two-fold: (1) Partly Locality Sensitive Hashing (PLSH) is proposed to find frequent patterns efficiently and (2) the problem of finding consecutive time frames that have a large number of frequent patterns is formulated as a combinatorial optimization problem which is solved via Dynamic Programming (DP) in polynomial time O (N 1+1/α) thanks to PLSH where N is the total amount of data. The proposed method was evaluated by detecting frequent whole body motions in a video sequence as well as by detecting frequent everyday manipulation tasks in motion capture data.

DOI

相互制約付き多数決型アルゴリズムによる時系列パターン認識

福冨正弘, 小川原光一, 馮尭楷, 内田誠一

電子情報通信学会論文誌 J93-D ( 4 ) 548 - 551 2010.04 [Refereed]

Detecting Repeated Patterns using Partly Locality Sensitive Hashing

Koichi Ogawara, Yasufumi Tanabe, Ryo Kurazume, Tsutomu Hasegawa

IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010) ( IEEE ) 2010 [Refereed]

Repeated patterns are useful clues to learn previously unknown events in an unsupervised way. This paper presents a novel method that detects relatively long variable-length unknown repeated patterns in a motion sequence efficiently.
The major contribution of the paper is two-fold: (1) Partly Locality Sensitive Hashing (PLSH) [1] is employed to find repeated patterns efficiently and (2) the problem of finding consecutive time frames that have a large number of repeated patterns is formulated as a combinatorial optimization problem which is solved via Dynamic Programming (DP) in polynomial time O( N1+1/alpha) thanks to PLSH where N is the total amount of data. The proposed method was evaluated by detecting repeated interactions between objects in everyday manipulation tasks and outperformed previous methods in terms of accuracy or computational time.

Approximate belief propagation by hierarchical averaging of outgoing messages

Koichi Ogawara

Proceedings - International Conference on Pattern Recognition 1368 - 1372 2010 [Refereed]

This paper presents an approximate belief propagation algorithm that replaces outgoing messages from a node with the averaged outgoing message and propagates messages from a low resolution graph to the original graph hierarchically. The proposed method reduces the computational time by half or two-thirds and reduces the required amount of memory by 60% compared with the standard belief propagation algorithm when applied to an image. The proposed method was implemented on CPU and GPU, and was evaluated against Middlebury stereo benchmark dataset in comparison with the standard belief propagation algorithm. It is shown that the proposed method outperforms the other in terms of both the computational time and the required amount of memory with minor loss of accuracy. © 2010 IEEE.

DOI

Painting robot with multi-fingered hands and stereo vision.

Shunsuke Kudoh, Koichi Ogawara, Miti Ruchanurucks, Katsushi Ikeuchi

Robotics Auton. Syst. 57 ( 3 ) 279 - 288 2009.03 [Refereed]

DOI

Detecting Repeated Motion Patterns via Dynamic Programming using Motion Density

Koichi Ogawara, Yasufumi Tanabe, Ryo Kurazume, Tsutomu Hasegawa

ICRA: 2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-7 ( IEEE ) 2926 - + 2009 [Refereed]

In this paper, we propose a method that detects repeated motion patterns in a long motion sequence efficiently. Repeated motion patterns are the structured information that can be obtained without knowledge of the context of motions. They can be used as a seed to find causal relationships between motions or to obtain contextual information of human activity, which is useful for intelligent systems that support human activity in everyday environment.
The major contribution of the proposed method is two-fold:
(1) motion density is proposed as a repeatability measure and
(2) the problem of finding consecutive time frames with large motion density is formulated as a combinatorial optimization problem which is solved via Dynamic Programming (DP) in polynomial time O(N log N) where N is the total amount of data. The proposed method was evaluated by detecting repeated interactions between objects in everyday manipulation tasks and outperformed the previous method in terms of both detectability and computational time.

Integrating Region Growing and Classification for Segmentation and Matting

Miti Ruchanurucks, Koichi Ogawara, Katsushi Ikeuchi

2008 15TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-5 ( IEEE ) 593 - 596 2008 [Refereed]

This paper presents a supervised foreground segmentation method that uses local and global feature similarity with edge constraint. This framework integrates and extends the notion of region growing and classification to deal with local and global fitness. It parameterizes constraint of growing using Chebyshev's inequality. The constraint is used to stop segmentation before matting. Matting relies on both local and global information. The proposed method outperforms many of the current methods in the sense of correctness and minimal user interaction, and it does so in a reasonable computation time.

Learning Meaningful Interactions from Repetitious Motion Patterns

Koichi Ogawara, Yasufumi Tanabe, Ryo Kurazume, Tsutomu Hasegawa

2008 IEEE/RSJ INTERNATIONAL CONFERENCE ON ROBOTS AND INTELLIGENT SYSTEMS, VOLS 1-3, CONFERENCE PROCEEDINGS ( IEEE ) 3350 - + 2008 [Refereed]

In this paper, we propose a method for estimating meaningful actions from long-term observation of everyday manipulation tasks without prior knowledge as part of an action understanding framework for life support robotic systems. The target task is defined as a sequence of interactions between objects. An interaction that appears many times is assumed to be meaningful and repetitious relative motion patterns are detected from trajectories of multiple objects. The main contribution is that the problem is formulated as a combinatorial optimization problem with two parameters, target object labels and correspondences on similar motion patterns, and is solved using local and global Dynamic Programming (DP) in polynomial time O(N log N), where N is a total amount of data. The proposed method is evaluated against manipulation tasks using everyday objects such as a cup and a tea-pot.

DOI

Representation of Drawing Behavior by a Robot

KUDOH Shunsuke, OGAWARA Koichi, RUCHANURUCKS Miti, TAKAMATSU Jun, IKEUCHI Katsushi

Journal of the Robotics Society of Japan ( The Robotics Society of Japan ) 26 ( 6 ) 612 - 619 2008 [Refereed]

This paper describes a painting robot with multi-fingered hands and stereo vision. The goal of this study is for the robot to reproduce the whole procedure involved in human painting. A painting action is divided into three phases: obtaining a 3D model, composing a picture model, and painting by a robot. In this system, various feedback techniques including computer vision and force sensors are used. As experiments, an apple and a human silhouette are painted on a canvas using this system.

DOI

Integrating Region Growing and Classification for Segmentation and Matting

Miti Ruchanurucks, Koichi Ogawara, Katsushi Ikeuchi

2008 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, PROCEEDINGS ( IEEE ) 597 - + 2008 [Refereed]

This paper presents a supervised foreground segmentation method that uses local and global feature similarity with edge constraint. This framework integrates and extends the notion of region growing and classification to deal with local anti global fitness. It parameterizes constraint of growing using Chebyshev's inequality. The constraint is used to stop segmentation before matting. Matting relies on both local and global information. The proposed method outperform many of the current methods in the sense of correctness and minimal user interaction, and it does so in a reasonable computation time.

Condtruction method of drift-free omni images by integration of multiple video cameras

MIKAMI Takeshi, ONO Shintaro, OGAWARA Koichi, KAWASAKI Hiroshi, IKEUCHI Katsushi

Monthly journal of the Institute of Industrial Science, University of Tokyo ( The University of Tokyo ) 59 ( 3 ) 80 - 84 2007.05

DOI

Marker-less human motion estimation using articulated deformable model

Koichi Ogawara, Xiaolu Li, Katsushi Ikeuchi

PROCEEDINGS OF THE 2007 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-10 ( IEEE ) 46 - 51 2007 [Refereed]

This paper presents a novel whole body motion estimation method by fitting a deformable articulated model of the human body into the 31) reconstructed volume obtained from multiple video streams. The advantage of the proposed method is two fold: (1) combination of a robust estimator and ICP algorithm with Kd-tree search in pose and normal space make it possible to track complex and dynamic motion robustly against noise and interference between limb and torso, (2) the hierarchical estimation and backtrack re-estimation algorithm enable accurate estimation.
The power to track challenging whole body motion in real environment is also presented.

Robot painter: From object to trajectory

Miti Ruchanurucks, Shunsuke Kudoh, Koichi Ogawara, Takaaki Shiratori, Katsushi Ikeuchi

2007 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-9 ( IEEE ) 345 - + 2007 [Refereed]

This paper presents visual perception discovered in high-level manipulator planning for a robot to reproduce the procedure involved in human painting. First, we propose a technique of 3D object segmentation that can work well even when the precision of the cameras is inadequate. Second, we apply a simple yet powerful fast color perception model that shows similarity to human perception. The method outperforms many existing interactive color perception algorithms. Third, we generate global orientation map perception using a radial basis function. Finally, we use the derived foreground, color segments, and orientation map to produce a visual feedback drawing. Our main contributions are 3D object segmentation and color perception schemes.

Humanoid robot painter: Visual perception and high-level manning

Miti Ruchanurucks, Shunsuke Kudoh, Koichi Ogawara, Takaaki Shiratori, Katsushi Ikeuchi

PROCEEDINGS OF THE 2007 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-10 ( IEEE ) 3028 - + 2007 [Refereed]

This paper presents visual perception discovered in high-level manipulator planning for a robot to reproduce the procedure involved in human painting. First, we apply a technique of 2D object segmentation that considers region similarity as an objective function and edge as a constraint with artificial intelligent used as a criterion function. The system can segment images more effectively than most of existing methods, even if the foreground is very similar to the background. Second, we propose a novel color perception model that shows similarity to human perception. The method outperforms many existing color reduction algorithms. Third, we propose a novel global orientation map perception using a radial basis function. Finally, we use the derived model along with the brush's position- and force-sensing to produce a visual feedback drawing. Experiments show that our system can generate good paintings including portraits.

Recognizing Assembly Tasks Through Human Demonstration.

Jun Takamatsu, Koichi Ogawara, Hiroshi Kimura, Katsushi Ikeuchi

International Journal of Robotics Research 26 ( 7 ) 641 - 659 2007 [Refereed]

DOI

Representation for knot-tying tasks.

Jun Takamatsu, Takuma Morita, Koichi Ogawara, Hiroshi Kimura, Katsushi Ikeuchi

IEEE Transactions on Robotics 22 ( 1 ) 65 - 78 2006 [Refereed]

DOI

Painting robot with multi-fingered hands and stereo vision

Shunsuke Kudoh, Koichi Ogawara, Miti Ruchanurucks, Katsushi Ikeuchi

IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 127 - 132 2006 [Refereed]

In this paper, we describe a painting robot with multi-fingered hands and stereo vision. The goal of this study is for the robot to reproduce the whole procedure involved in human painting. A painting action is divided into three phases: obtaining a 3D model, composing a picture model, and painting by a robot. In this system, various feedback techniques including computer vision and force sensors are used. As experiments, an apple and a human silhouette are painted on a canvas using this system. © 2006 IEEE.

DOI

Laser Range Sensor Suspended beneath Balloon : FLRS (Flying Laser Range Sensor)

HASEGAWA Kazuhide, HIROTA Yuichiro, OGAWARA Koichi, KURAZUME Ryo, IKEUCHI Katsushi

The transactions of the Institute of Electronics, Information and Communication Engineers. D-II ( The Institute of Electronics, Information and Communication Engineers ) J88-D-II ( 8 ) 1499 - 1507 2005.08 [Refereed]

レーザレンジセンサなどを用いた計測作業において, 遺跡や建物などの対象物が大規模になればなるほど, 地上からは観測できないオクルージョン領域が発生する. 一般的には足場を組んでセンサを持ち上げてその上部からの計測を行っているが, 計測位置の移動には多くの時間とコストがかかる. また, 足場を組むことが不可能な場合は計測作業自体が止まることにもなる. この問題を解決するために, 筆者らは気球を用いて空中から計測を行うことにより, 足場を組むことなく手軽に計測位置の移動を可能にするレーザレンジセンサFLRSの開発を行った. このセンサでは, 気球の揺れによる影響を少なくするために高速な計測を実現しているが, 計測結果には若干のひずみが発生している. そこで, センサに内蔵しているビデオカメラからの連続画像を用いて, センサ本体の動きを検出して補正する手法を提案する. そして, 実際に遺跡計測に用いた例を挙げ, センサシステムの有効性を示す.

Representation of Knot Tying Tasks for Robot Execution

TAKAMATSU Jun, MORITA Takuma, OGAWARA Koichi, KIMURA Hiroshi, IKEUCHI Katsushi

Journal of the Robotics Society of Japan ( The Robotics Society of Japan ) 23 ( 5 ) 572 - 582 2005.07 [Refereed]

TheLearning from Observation (LFO) paradigm has been widely applied in various types of robot systems. It helps reduce the work of the programmer. However, so far, the available systems have application limited to rigid objects. Deformable objects are not considered, because: (1) it is difficult to describe their states and (2) too many operations are possible on them. In this paper, we choose knot-tying tasks as case study for operating on deformable objects, since theknot theoryis available and since types of operations are limited. In actuality, we introduce an appropriate representation for describing knot's states and define four types of operations enough to realize any knot-tying tasks.

DOI

ロボット動作の自動生成のための観察による組み立て作業の抽象化

高松淳, 小川原光一, 木村浩, 池内克史

情報処理学会論文誌コンピュータビジョンとイメージメディア 46 ( SIG 9 ) 41 - 55 2005.06 [Refereed]

A sensor fusion approach for recognizing continuous human grasping sequences using hidden Markov models

Keni Bernardin, Koichi Ogawara, Katsushi Ikeuchi, Ruediger Dillmann

IEEE Transactions on Robotics 21 ( 1 ) 47 - 57 2005.02 [Refereed]

The Programming by Demonstration (PbD) technique aims at teaching a robot to accomplish a task by learning from a human demonstration. In a manipulation context, recognizing the demonstrator's hand gestures, specifically when and how objects are grasped, plays a significant role. Here, a system is presented that uses both hand shape and contact-point information obtained from a data glove and tactile sensors to recognize continuous human-grasp sequences. The sensor fusion, grasp classification, and task segmentation are made by a hidden Markov model recognizer. Twelve different grasp types from a general, task-independent taxonomy are recognized. An accuracy of up to 95% could be achieved for a multiple-user system. © 2005 IEEE.

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A photo-realistic driving simulation system for mixed-reality traffic experiment space

Shintaro Ono, Koichi Ogawara, Masataka Kagesawa, Hiroshi Kawasaki, Masaaki Onuki, Junichi Abeki, Tori Yano, Masami Nerio, Ken Honda, Katsushi Ikeuchi

IEEE Intelligent Vehicles Symposium, Proceedings 2005 747 - 752 2005 [Refereed]

In this paper, we propose an efficient and effective image generation system for "Mixed Reality Traffic Experiment Space", an enhanced driving/traffic simulation system which we have been developing for Sustainable ITS project at the University of Tokyo. Conventional driving simulators represent ther view by a set of polygon-based objects, which leads to less photo-reality and huge human costs for dataset construction. We introduce our image/geometry-based hybrid method to realize more photo-realistic view with less human cost at the same time. Images for datesets are captured from real world by multiple video cameras mounted on a data acquisition vehicle. And the view for the system is created by synthesizing the image dataset. Following contents mainly describe details on data acquisition and view rendering. © 2005 IEEE.

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Driving view simulation synthesizing virtual geometry and real images in an experimental mixed-reality traffic space

Shintaro Ono, Koichi Ogawara, Masataka Kagesawa, Hiroshi Kawasaki, Masaaki Onuki, Ken Honda, Katsushi Ikeuchi

Proceedings - Fourth IEEE and ACM International Symposium on Symposium on Mixed and Augmented Reality, ISMAR 2005 2005 214 - 215 2005 [Refereed]

We propose an efficient and effective image generation system for an experimental mixed-reality traffice space. Our enhanced traffic/driving simulation system represents the view through a hybrid that combines virtual geometry with real images to realize high photo-reality with little human cost. Images for datasets are captured from the real world, and the view for the simulation system is created by synthesizing image datasets with a conventional driving simulator. © 2005 IEEE.

DOI

Understanding of Human Assembly Tasks for Robot Execution Generation of Optimal Trajectories Based on Transitions of Contact Relations

TAKAMATSU Jun, OGAWARA Koichi, KIMURA Hiroshi, IKEUCHI Katsushi

JRSJ ( The Robotics Society of Japan ) 22 ( 6 ) 752 - 763 2004.09 [Refereed]

The planning-from-observation paradigm is widely noticed as a novel robot-programming technique. It consists of two parts: (1) recognition of a human demonstration from observation as symbolic representation, i.e., a sequence of movement primitives and (2) execution of the same task. Symbolic representation enables a robot to achieve the same task even in a different environment. We already proposed a method to build a symbolic representation for an assembly task. However, for a robot to execute the task, it is necessary to adjust parameters of each movement primitive to generate appropriate trajectories of objects, especially a path which maintains one of any contact states. Many researchers have proposed methods to calculate such a path using a non-linear optimization method, for example, the potential field method, the probabilistic method, and so on. Although these methods are very powerful as calculation tools on a computer, their solutions are not optimal. We propose a novel method to calculate such an optimal path using a linear solution.

DOI

民俗芸能のデジタルアーカイブとロボットによる動作提示

池内克史, 中澤篤志, 小川原光一, 高松淳, 工藤俊亮, 中岡慎一郎, 白鳥貴亮

日本バーチャルリアリティ学会誌 9 ( 2 ) 14 - 20 2004.06 [Refereed]

Extraction of Essential Interactions Through Multiple Observations of Human Demonstrations

Koichi Ogawara, Jun Takamatsu, Hiroshi Kimura, Katsushi Ikeuchi （Part： Lead author )

IEEE Transactions on Industrial Electronics 50 ( 4 ) 667 - 675 2003.12 [Refereed]

観察に基づく手作業の獲得における視覚の利用

小川原光一, 高松淳, 木村浩, 池内克史（Part： Lead author )

情報処理学会論文誌コンピュータビジョンとイメージメディア 44 ( SIG 17 ) 13 - 23 2003.12 [Refereed]

Knot planning from observation

Takuma Morita, Jun Takamatsu, Koichi Ogawara, Hiroshi Kimura, Katsushi Ikeuchi

Proceedings - IEEE International Conference on Robotics and Automation 3 3887 - 3892 2003

Learning from Observation (LFO) has been widely applied in various types of robot system. It helps reduce the work of the programmer. But the available systems have application limited to rigid objects. Deformable objects are not considered because: 1) it is difficult to describe their state and 2) too many operations are possible on them. In this paper, we choose the knot tying as case study for operating on nonrigid bodies, because a "knot theory" is available and the type of operations is limited. We describe the Knot Planning from Observation (KPO) paradigm, a KPO theory and a KPO system.

Acquisition of a symbolic manipulation task model by attention point analysis

Koichi Ogawara, Jun Takamatsu, Hiroshi Kimura, Katsushi Ikeuchi （Part： Lead author )

Advanced Robotics 17 ( 10 ) 1073 - 1091 2003 [Refereed]

As a way of automatic programming of robot behavior, a method for building a symbolic manipulation task model from a demonstration is proposed. The feature of this model is that it explicitly stores the information about the essential parts of a task, i.e. interaction between a hand and an environmental object, or interaction between a grasped object and a target object. Thus, even in different environments, this method reproduces robot motion as similar as possible to that of humans to complete the task while changing the motion during non-essential parts to adapt to the current environment. To automatically determine the essential parts, a method called attention point analysis is proposed
this method searches for the nature of a task using multiple sensors and estimates the parameters to represent the task. A humanoid robot is used to verify the reproduced robot motion based on the generated task model.

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複数教示動作の時系列上での統合に基づく人間作業のモデル化手法

小川原光一, 高松淳, 木村浩, 池内克史（Part： Lead author )

情報処理学会論文誌コンピュータビジョンとイメージメディア 43 ( SIG 4 ) 117 - 126 2002.06 [Refereed]

Modeling manipulation interactions by hidden Markov models

Koichi Ogawara, Jun Takamatsu, Hiroshi Kimura, Katsushi Ikeuchi

IEEE International Conference on Intelligent Robots and Systems 2 1096 - 1101 2002

This paper describes a new approach on how to teach everyday manipulation tasks to a robot under the "Learning from Observation" framework. In our previous work, to acquire low-level action primitives of a task automatically, we proposed a technique to estimate essential interactions to complete a task by integrating multiple observations of similar demonstrations. But after many demonstrations are performed, there are possibly interactions which are the same in nature. These identical interactions should be grouped so that each action primitive becomes unique. For this purpose, a Hidden Markov Model based clustering algorithm is presented which automatically determines the number of the independent interactions, We also show that obtained interactions can be used as discriminations of human behavior. Finally, a simulation result and an experimental result in which a real humanoid robot learns and recognizes essential actions by observing demonstrations are presented.

Correcting observation errors for assembly task recognition

Jun Takamatsu, Koichi Ogawara, Hiroshi Kimura, Katsushi Ikeuchi

IEEE International Conference on Intelligent Robots and Systems 1 232 - 237 2002

The completion of robot programs requires long development time and much effort. To shorten the programming time and to minimize the effort, we have been developing a system which we refer to as the "assembly-plan-from-observation (APO) system." This system requires assembly task recognition from observing human performance. Observation data by a robot's vision system is usually error contaminated, and, thus, we cannot use those data directly. This paper proposes two methods to clean up those errors by using contact relations and their transitions. The first one corrects the observed configuration from contact relations observed. The second one identifies wrongly determined contact relations from an analysis of configuration space (C-space). We have implemented both methods on our test bed and have verified their effectiveness.

Refining hand-action models through repeated observations of human and robot behavior by combined template matching

Koichi Ogawara, Hiroshi Kimura, Katsushi Ikeuchi

IEEE International Conference on Intelligent Robots and Systems 1 545 - 550 2001

This paper describes our current research on learning task level representations by a robot through observation of human demonstrations. Representations proposed so far typically utilized one or a few sensors and were constructed through one time observation, therefore they could solve ambiguity in the data only under strong assumptions. We focus on human hand actions and have been developing a novel construction method of a human task model which integrates multiple observations to solve ambiguity based on Attention Points (APs). So far, this analysis constructs a symbolic task model efficiently in a coarse-to-fine way through two steps. However, to represent delicate motion appeared in a task, the system must incorporate the information about precise motion of the manipulated objects into an abstract task model. In this paper, we propose a method to identify the manipulated object through repeated observations of both human and robot behavior. To this end, we present a method which combines 2D and 3D template matching techniques to localize an object in 3D space generated from a depth and an intensity image. We apply this technique to recognition of human and robot behavior by obtaining the precise trajectory of the manipulated objects. We also present the experimental results achieved through the use of a human-form robot equipped with a 9-eye stereo vision system.

Acquiring hand-action models by attention point analysis

Koichi Ogawara, Soshi Iba, Tomikazu Tanuki, Hiroshi Kimura, Katsushi Ikeuchi

Proceedings - IEEE International Conference on Robotics and Automation 1 465 - 470 2001 [Refereed]

This paper describes our current research on learning task level representations by a robot through observation of human demonstrations. We focus on human hand actions and represent such hand actions in symbolic task models. We propose a framework of such models by efficiently integrating multiple observations based on attention points
we then evaluate the produced model by using a human-form robot. We propose a two-step observation mechanism. At the first step, the system roughly observes the entire sequence of the human demonstration, builds a rough task model and also extracts attention points (APs). The attention points indicate the time and the position in the observation sequence that requires further detailed analysis. At the second step, the system closely examines the sequence around the APs, and obtains attribute values for the task model, such as what to grasp, which hand to be used, or what is the precise trajectory of the manipulated object. We have implemented this system on a human form r obot and demonstrated its effectiveness.

DOI

Extraction of fine motion through multiple observations of human demonstration by DP matching and combined template matching

Koichi Ogawara, Jun Takamatsu, Hiroshi Kimura, Katsushi Ikeuchi

Proceedings - IEEE International Workshop on Robot and Human Interactive Communication 8 - 13 2001 [Refereed]

This paper describes our current research on how a robot, through observation of human demonstrations, can learn task level representations of human hand-work tasks. Representations proposed so far typically handle a human hand trajectory as it is or segment the entire task into a discrete pre-determined symbol sequence
but to make a generalized model of human hand-work tasks, both types of information must be incorporated into the model appropriately. We propose a technique for segmenting an observed hand-work task into pieces which are composed of fine motion or coarse motion. Fine motion means delicate manipulation and holds the relative trajectory between the grasped object and the target object, while coarse motion is a symbol which connects each fine motion. During coarse motion, a trajectory can be adjusted according to the environment or the structure of a robot when the robot performs the same task performed by a human. To extract essential fine motion automatically, we propose a technique for integrating and aligning multiple observations of different demonstrations, which are virtually the same task, by using data gloves and multi-dimensional Dynamic Programming (DP) matching. Along each fine motion, the relative trajectory (position and orientation) is calculated by tracking the manipulated object using a stereo vision. To localize and track the manipulated object efficiently, we propose a model-based localization technique, which combines 2D and 3D template matching. We have implemented those techniques on our human-form robot and present an experimental result which analyzed and performed a non-contact hand-work task. © 2001 IEEE.

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ネットワーク環境におけるモバイルエージェント機構に基づいて個人の継続的な支援を目指した分散ロボット統合法

小川原光一, 金広文男, 稲葉雅幸, 井上博允（Part： Lead author )

日本ロボット学会誌 18 ( 7 ) 1034 - 1039 2000.07 [Refereed]

Recognition of Human Behaviour using Stereo Vision and Data Gloves

Ogawara Koichi, Iba Soshi, Tanuki Tomikazu, Sato Yoshihiro, Saegusa Akira, Kimura Hiroshi, Ikeuchi Katsushi

Monthly journal of the Institute of Industrial Science, University of Tokyo ( The University of Tokyo ) 52 ( 5 ) 225 - 230 2000.05

This paper presents a novel method of constructing a human behaviour model by attention point (AP) analysis. The AP analysis consists of two steps. At the first step, it broadly observes human behaviour, constructs rough human behaviour model and finds APs which require detailed analysis. Then at the second step, by applying time-consuming analysis on APs in the same human behaviour, it can enhance the human behaviour model. This human behaviour model is highly abstracted and is able to change the degree of abstraction adapting to the environment so as to be applicable in a different environment. We describe this method and its implementation using data gloves and a stereo vision system. We also show an experimental result in which a real robot observed and performed the same human behaviour successfully in a different environment using this model.

DOI

Recognition of human task by attention point analysis

Koichi Ogawara, Soshi Iba, Tomikazu Tanuki, Hiroshi Kimura, Katsushi Ikeuchi

IEEE International Conference on Intelligent Robots and Systems 3 2121 - 2126 2000 [Refereed]

This paper presents a novel method of constructing a human task model by attention point (AP) analysis. The AP analysis consists of two steps. At the first step, it broadly observes human task, constructs rough human task model and finds APs which require detailed analysis. Then at the second step, by applying time-consuming analysis on APs in the same human task, it can enhance the human task model. This human task model is highly abstracted and is able to change the degree of abstraction adapting to the environment so as to be applicable in a different environment. We describe this method and its implementation using data gloves and a stereo vision system. We also show an experimental result in which a real robot observed a human task and performed the same human task successfully in a different environment using this model.

DOI

Symbolic Representation of Trajectories for Skill Generation.

Hirohisa Tominaga, Jun Takamatsu, Koichi Ogawara, Hiroshi Kimura, Katsushi Ikeuchi

Proceedings of the 2000 IEEE International Conference on Robotics and Automation, ICRA 2000, April 24-28, 2000, San Francisco, CA, USA ( IEEE ) 4076 - 4081 2000 [Refereed]

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