Norimichi Ukita

Nara Institute of Science and Technology, Ikuma, Nara, Japan

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Publications (43)11.21 Total impact

  • Norimichi Ukita, Takeo Kanade
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    ABSTRACT: We propose a multiview method for reconstructing a folded cloth surface on which regularly-textured color patches are printed. These patches provide not only easy pixel-correspondence between multiviews but also the following two new functions. (1) Error recovery: errors in 3D surface reconstruction (e.g. errors in occlusion boundaries and shaded regions) can be recovered based on the spatio-temporal consistency of the patches. (2) Single-view hole filling: patches that are visible only from a single view can be extrapolated from the reconstructed ones based on the regularity of the patches. Using these functions for improving 3D reconstruction also produces the patch configuration on the reconstructed surface, showing how the cloth is deformed from its reference shape. Experimental results demonstrate the above improvements and the accurate patch configurations produced by our method.
    Computer Vision and Image Understanding 08/2012; 116(8):869–881. · 1.23 Impact Factor
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    ABSTRACT: We propose a method for calibrating the topology of distributed pan-tilt cameras (i.e. the structure of routes among and within FOVs) and its probabilistic model. To observe as many objects as possible for as long as possible, pan-tilt control is an important issue in automatic calibration as well as in tracking. In a calibration period, each camera should be controlled towards an object that goes through an unreliable route whose topology is not calibrated yet. This camera control allows us to efficiently establish the topology model. After the topology model is established, the camera should be directed towards the route with the biggest possibility of object observation. We propose a camera control framework based on the mixture of the reliability of the estimated routes and the probability of object observation. This framework is applicable both to camera calibration and object tracking by adjusting weight variables. Experiments demonstrate the efficiency of our camera control scheme for establishing the camera topology model and tracking objects as long as possible.
    IEICE Transactions. 01/2012; 95-D:626-635.
  • Norimichi Ukita, Takeo Kanade
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    ABSTRACT: We propose a unified model for human motion prior with multiple actions. Our model is generated from sample pose sequences of the multiple actions, each of which is recorded from real human motion. The sample sequences are connected to each other by synthesizing a variety of possible transitions among the different actions. For kinematically-realistic transitions, our model integrates nonlinear probabilistic latent modeling of the samples and interpolation-based synthesis of the transition paths. While naive interpolation makes unexpected poses, our model rejects them (1) by searching for smooth and short transition paths by employing the good properties of the observation and latent spaces and (2) by avoiding using samples that unexpectedly synthesize the nonsmooth interpolation. The effectiveness of the model is demonstrated with real data and its application to human pose tracking.
    Computer Vision and Image Understanding. 01/2012; 116:500-509.
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    M. Hirai, N. Ukita, M. Kidode
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    ABSTRACT: We present a real-time method for estimating the pose of a human body using its 3D volume obtained from synchronized videos. The method achieves pose estimation by pose regression from its 3D volume. While the 3D volume allows us to estimate the pose robustly against self occlusions, 3D volume analysis requires a large amount of computational cost. We propose fast and stable volume tracking with efficient volume representation in a low dimensional dynamical model. Experimental results demonstrated that pose estimation of a body with a significantly deformable clothing could run at around 60 fps.
    Pattern Recognition (ICPR), 2010 20th International Conference on; 09/2010
  • Norimichi Ukita, Akira Makino, Masatsugu Kidode
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    ABSTRACT: In this research, we focus on how to track a target region that lies next to similar regions (e.g. a forearm and an upper arm) in zoom-in images. Many previous tracking methods express the target region (i.e. a part in a human body) with a single model such as an ellipse, a rectangle, and a deformable closed region. With the single model, however, it is difficult to track the target region in zoom-in images without confusing it and its neighboring similar regions (e.g. ``a forearm and an upper arm'' and ``a small region in a torso and its neighboring regions'') because they might have the same texture patterns and do not have the detectable border between them. In our method, a group of feature points in a target region is extracted and tracked as the model of the target. Small differences between the neighboring regions can be verified by focusing only on the feature points. In addition, (1) the stability of tracking is improved using particle filtering and (2) tracking robust to occlusions is realized by removing unreliable points using random sampling. Experimental results demonstrate the effectiveness of our method even when occlusions occur.
    IEICE Transactions. 01/2010; 93-D:1682-1689.
  • Norimichi Ukita, Michiro Hirai, Masatsugu Kidode
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    ABSTRACT: We propose a method for estimating the pose of a human body using its approximate 3D volume (visual hull) obtained in real time from synchronized videos. Our method can cope with loose-fitting clothing, which hides the human body and produces non-rigid motions and critical reconstruction errors, as well as tight-fitting clothing. To follow the shape variations robustly against erratic motions and the ambiguity between a reconstructed body shape and its pose, the probabilistic dynamical model of human volumes is learned from training temporal volumes refined by error correction. The dynamical model of a body pose (joint angles) is also learned with its corresponding volume. By comparing the volume model with an input visual hull and regressing its pose from the pose model, pose estimation can be realized. In our method, this is improved by double volume comparison: 1) comparison in a low-dimensional latent space with probabilistic volume models and 2) comparison in an observation volume space using geometric constrains between a real volume and a visual hull. Comparative experiments demonstrate the effectiveness of our method faster than existing methods.
    Computer Vision, 2009 IEEE 12th International Conference on; 11/2009
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    N. Ukita, K. Terashita, M. Kidode
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    ABSTRACT: We propose a method for calibrating the topology of distributed pan tilt cameras (i.e., the structure of routes among FOVs) and its probabilistic model, which is useful for multi-object tracking in a wide area. To observe objects as long and many as possible, pan tilt control is an important issue in automatic calibration as well as in tracking. If only one object is observed by a camera and its neighboring cameras, the camera should point towards this object both in the calibration and tracking periods. However, if there are multiple objects, in the calibration period, the camera should be controlled towards an object that goes through an unreliable route in which a sufficient number of object detection results have not been observed. This control allows us to efficiently establish the reliable topology model. After the reliable topology model is established, on the other hand, the camera should be directed towards the route with the biggest possibility of object observation. We therefore propose a camera control framework based on the mixture of the reliability of the estimated routes and the probability of object observation. This framework is applicable both to camera calibration and object tracking by adjusting weight variables. Experiments demonstrate the efficiency of our camera control scheme for establishing the camera topology model and tracking objects as long as possible.
    Distributed Smart Cameras, 2009. ICDSC 2009. Third ACM/IEEE International Conference on; 10/2009
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    ABSTRACT: This paper proposes a free-viewpoint imaging method that can be used in a complicated scene such as an office room by using sparsely located cameras. In our method, a free-viewpoint image is generated from multiple image patches obtained by dividing observed images. The quality of the generated image strongly depends on how to divide the observed images. In an incorrect patch in the generated image, the images projected from different cameras differ significantly. With this property, the incorrect patches can be detected. These patches are then re-divided. We demonstrated the effectiveness of our method by generating free-viewpoint images from the real images observed by the cameras in an office room.
    Pattern Recognition, 2008. ICPR 2008. 19th International Conference on; 01/2009
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    N. Enami, N. Ukita, M. Kidode
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    ABSTRACT: In this paper, we propose a matching method for images captured at different times and under different capturing conditions. Our method is designed for change detection in street scapes using normal automobiles that has an off-the-shelf car mounted camera and a GPS. Therefore, we should analyze low-resolution and low frame-rate images captured asynchronously. To cope with this difficulty, previous and current panoramic images are created from sequential images which are rectified based on the view direction of a camera, and then compared. In addition, in order to allow the matching method to be applicable to images captured under varying conditions, (1) for different lanes, enlarged/reduced panoramic images are compared with each other, and (2) robustness to noises and changes in illumination is improved by the edge features. To confirm the effectiveness of the proposed method, we conducted experiments matching real images captured under various capturing conditions.
    Distributed Smart Cameras, 2008. ICDSC 2008. Second ACM/IEEE International Conference on; 10/2008
  • Norimichi Ukita, Ryosuke Tsuji, Masatsugu Kidode
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    ABSTRACT: We propose a real-time method for simultaneously refining the reconstructed volume of a human body with loose-fitting clothing and identifying body-parts in it. Time-series volumes, which are acquired by a slow but sophisticated D reconstruction algorithm, with body-part la- bels are obtained offline. The time-series sample volumes are represented by trajectories in the eigenspaces using PCA. An input visual hull recon- structed online is projected into the eigenspace and compared with the trajectories in order to find similar high-precision samples with body- part labels. The hierarchical search taking into account 3D reconstruc- tion errors can achieve robust and fast matching. Experimental results demonstrate that our method can refine the input visual hull including loose-fitting clothing and identify its body-parts in real time.
    Computer Vision - ECCV 2008, 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part III; 01/2008
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    ABSTRACT: This paper proposes a method for precise overlapping of projected images from multiple steerable projectors. When they are controlled simultaneously, two problems are revealed: (1) even a slight positional error of the projected image, which does not matter in the case of a single projector, causes misalignments of multiple projected images that can be perceived clearly when using multiple projectors; and (2) as the projectors usually do not have architectures for their synchronization it is impossible to display a moving image that is by tiling or overlaying precisely the multiple projected images. To overcome (1), a method is proposed that measures preliminarily the misalignments through every plane in the environment, and hence displays the image without the misalignment. For (2), a consideration and a new proposal for the synchronization of multiple projectors are also discussed.
    2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 18-23 June 2007, Minneapolis, Minnesota, USA; 01/2007
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    Norimichi Ukita
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    ABSTRACT: We propose a method for estimating the topol- ogy of distributed cameras, which can provide useful in- formation for multi-target tracking in a wide area, with- out object identification among the FOVs of the cam- eras. In our method, each camera first detects objects in its observed images independently in order to obtain the positions/times where/when the objects enter/exit its FOV. Each obtained data is tentatively paired with all other data detected before the data is observed. A transit time between each paired data and their x-y coordinates are then computed. Based on classifying the distribu- tion of the transit times and the x-y coordinates, object routes between FOVs can be detected. The classification is achieved by simple and robust vector quantization. The detected routes are then categorized to acquire the probabilistic-topological information of distributed cam- eras. In addition, offline tracking of observed objects can be realized by means of the calibration process. Exper- iments demonstrated that our method could automat- ically estimate the topological relationships of the dis- tributed cameras and the object transits among them.
    Machine Vision and Applications 01/2007; 18:249-260. · 1.10 Impact Factor
  • S. Yous, N. Ukita, M. Kidode
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    ABSTRACT: We are designing a self controlling active camera system for a 3D video of a moving object (mainly human body). We made up our system of cameras with long focal length lenses for high resolution input images. However, such cameras can get only partial views of the object. We present, in this paper, a multiple active (pan-tilt) camera assignment scheme. The goal is to assign each camera to a specific part of the moving object so as to allow the best visibility of the whole object. For each camera, we evaluate the visibility to the different regions of the object, corresponding to different camera orientations and with respect to the field of view of the camera in question. Thereafter, we assign each camera to one orientation in such a way to maximize the visibility to the whole object.
    Computer Vision Systems, 2006 ICVS '06. IEEE International Conference on; 02/2006
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    ABSTRACT: This paper proposes a method for reconstructing a 3D scene structure by using the images reflected in a spherical mirror. In our method, the mirror is moved freely within the field of view of a camera in order to observe a surrounding scene virtually from multiple viewpoints. The observation scheme, therefore, allows us to obtain the wide-angle multi-viewpoint images of a wide area. In addition, the following characteristics of this observation enable multi-view stereo with simple calibration of the geometric configuration between the mirror and the camera; (1) the distance and direction from the camera to the mirror can be estimated directly from the position and size of the mirror in the captured image and (2) the directions of detected points from each position of the moving mirror can be also estimated based on reflection on a spherical surface. Some experimental results show the effectiveness of our 3D reconstruction method
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on; 02/2006
  • Systems and Computers in Japan. 01/2006; 37:21-31.
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    Sofiane Yous, Norimichi Ukita, Masatsugu Kidode
    01/2006;
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    N. Ukita
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    ABSTRACT: We have proposed a real-time multi-target tracking system by cooperative behaviors of active vision agents (AVAs), where an AVA is a logical model of a network-connected computer with an active camera. All AVAs change their roles adaptively by negotiating with each other. The previous system, however, was unable to simultaneously track target objects that are greater in number than the AVAs. In this paper, we realize the increase in number of simultaneously trackable objects by improving cooperative tracking protocols so that AVAs exchange a large amount of information with each other without increasing network traffic. This system enables the increase of trackable objects by (1) an AVA that provides information of observed objects for several agencies (i.e., a group of AVAs that track the same target) and (2) a vacant-agency that receives information of its target from AVAs tracking other objects. Experimental results demonstrate that our system can track multiple targets (greater in number than the cameras) simultaneously and robustly in real time.
    Intelligent Agent Technology, IEEE/WIC/ACM International Conference on; 10/2005
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    N. Ukita
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    ABSTRACT: We propose a method for detecting foreground objects in non-stationary scenes. The method can (1) detect arbitrary foreground objects without any prior knowledge of them, (2) identify background pixels under various changes in a background scene, and (3) detect minor difference between the background and target colors. Online detection is realized by the nearest neighbor classifier in the 5D xy-YUV space (the spatio-color space), consisting of the x and y coordinates of an image and Y, U, and V colors, which holds rectified training data of background colors and automatically learned target colors. We conducted experiments to confirm the effectiveness of our method.
    Advanced Video and Signal Based Surveillance, 2005. AVSS 2005. IEEE Conference on; 10/2005
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    I. Mitsugami, N. Ukita, M. Kidode
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    ABSTRACT: We describe a new steerable projector, whose projection center precisely corresponds with its rotation center, which we call a "fixed-center pan-tilt (FC-PT) projector." This mechanism allows it be set up more easily to display graphics precisely on the planes in the environment than for other steerable projectors; wherever we would like to display graphics, all we have to do are locating the FC-PT projector in the environment, and directing it to the corners of the planes whose 2D sizes have been measured. Moreover, as the FC-PT projector can recognize automatically whether each plane is connected to others, it can display visual information that lies across the boundary line of two planes in a similar way to a paper poster folded along the planes.
    Computer Vision and Pattern Recognition, 2005 IEEE Computer Society Conference on; 07/2005
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    [show abstract] [hide abstract]
    ABSTRACT: We describe a new steerable projector, whose projection center precisely corresponds with its rotation center, which we call a "fixed-center pan-tilt (FC-PT) projector." This mechanism allows it be set more easily to display graph- ics precisely on the planes in the environment than for other steerable projectors; wherever we would like to draw graphics, all we have to do are locate the FC-PT projec- tor in the environment, and directing it to the corners of the planes whose 2D sizes have been measured. Moreover, by describing multiple planes in the environment by an inte- grated 2D coordinate system, it can display even a graphic that lies across a boundary line of two planes in a similar way to a paper poster folded along the planes.
    Proceedings of the IAPR Conference on Machine Vision Applications (IAPR MVA 2005), May 16-18, 2005, Tsukuba Science City, Japan; 01/2005

Publication Stats

200 Citations
87 Downloads
2k Views
11.21 Total Impact Points

Institutions

  • 2003–2012
    • Nara Institute of Science and Technology
      • Graduate School of Information Science
      Ikuma, Nara, Japan
  • 2000–2005
    • Kyoto University
      • • Graduate School of Informatics
      • • Department of Intelligence Sciences and Technology
      Kyoto, Kyoto-fu, Japan