Acta Medica Okayama 1999 Photometric image-based rendering for virtual lighting image synthesis 115 124 EN Yasuhiro Mukaigawa Sadahiko Mihashi Takeshi Shakunaga A concept named Photometric Image-Based Rendering (PIBR) is introduced for a seamless augmented reality. The PIBR is defined as image-based rendering which covers appearance changes caused by the lighting condition changes, while Geometric Image-Based Rendering (GIBR) is defined as image-based rendering which covers appearance changes caused by the view point changes. PIBR can be applied to image synthesis to keep photometric consistency between virtual objects and real scenes in arbitrary lighting conditions. We analyze conventional IBR algorithms, and formalize PIBR within the whole IBR framework. A specific algorithm is also presented for realizing PIBR. The photometric linearization makes a controllable framework for PIBR, which consists of four processes: (1) separation of environmental illumination effects, (2) estimation of lighting directions, (3) separation of specular reflections and cast-shadows, and (4) linearization of self-shadows. After the-photometric linearization of input images, we can synthesize any realistic images which include not-only diffuse reflections but also self-shadows, cast-shadows and specular reflections. Experimental results show that realistic images can be successfully synthesized while keeping photometric consistency No potential conflict of interest relevant to this article was reported.

Acta Medica Okayama 1998 Integration of eigentemplate and structure matching for automatic facial feature detection 94 99 EN Takeshi Shakunaga Keisuke Ogawa Shohei Oki An algorithm is proposed for facial feature detection from a facial image. The algorithm consists of the bottom-up and the top-down interpretation processes, which work with the feature matching module and the structure matching module. Experimental results show that the proposed algorithm can detect no less than five features in 99.3% of the frontal views and can work even if the face orientation is unknown No potential conflict of interest relevant to this article was reported.

Acta Medica Okayama 1 2001 Decomposed eigenface for face recognition under various lighting conditions EN Takeshi Shakunaga Kazuma Shigenari Face recognition under various lighting condition's is discussed to cover cases when too few images are available for registration. This paper proposes decomposition of an eigenface into two orthogonal eigenspaces for realizing robust face recognition under such conditions. The decomposed eigenfaces consisting of two eigenspaces are constructed for each person even if only one image is available. A universal eigenspace called the canonical space (CS) plays an important role in creating the eigenspaces by way of decomposition, where CS is constructed a priori by principal component analysis (PCA) over face images of many people under many lighting conditions. In the registration stage, an input face image is decomposed to a projection image in CS and the residual of the projection. Then two eigenspaces are created independently in CS and in the orthogonal complement CS/sup /spl perp//. Some refinements of the two eigenspaces are also discussed. By combining the two eigenspaces, we can easily realize face identification that is robust to illumination change, even when too few images are registered. Through experiments, we show the effectiveness of the decomposed eigenfaces as compared with conventional methods. No potential conflict of interest relevant to this article was reported.

Acta Medica Okayama 3 2006 A Real-life Test of Face Recognition System for Dialogue Interface Robot in Ubiquitous Environments 1155 1160 EN Fumihiko Sakaue Makoto Kobayashi Tsuyoshi Migita Takeshi Shakunaga Junji Satake This paper discusses a face recognition system for a dialogue interface robot that really works in ubiquitous environments and reports an experimental result of real-life test in a ubiquitous environment. While a central module of the face recognition system is composed of the decomposed eigenface method, the system also includes a special face detection module and the face registration module. Since face recognition should work on images captured by a camera equipped on the interface robot, all the methods are tuned for the interface robot. The face detection and recognition modules accomplish robust face detection and recognition when one of the registered users is talking to the robot. Some interesting results are reported with careful analysis of a sufficient real-life experiment. No potential conflict of interest relevant to this article was reported.

Acta Medica Okayama 2003 Color blending based on viewpoint and surface normal for generating images from any viewpoint using multiple cameras 95 100 EN Yasuhiro Mukaigawa Daisuke Genda Ryo Yamane Takeshi Shakunaga A color blending method for generating a high quality image of human motion is presented. The 3D (three-dimensional) human shape is reconstructed by volume intersection and expressed as a set of voxels. As each voxel is observed as different colors from different cameras, voxel color needs to be assigned appropriately from several colors. We present a color blending method, which calculates voxel color from a linear combination of the colors observed by multiple cameras. The weightings in the linear combination are calculated based on both viewpoint and surface normal. As surface normal is taken into account, the images with clear texture can be generated. Moreover, since viewpoint is also taken into account, high quality images free of unnatural warping can be generated. To examine the effectiveness of the algorithm, a traditional dance motion was captured and new images were generated from arbitrary viewpoints. Compared to existing methods, quality at the boundaries was confirmed to improve. No potential conflict of interest relevant to this article was reported.

Acta Medica Okayama 1 2002 Natural image correction by iterative projections to eigenspace constructed in normalized image space 648 651 EN Takeshi Shakunaga Fumihiko Sakaue Image correction is discussed for realizing both effective object recognition and realistic image-based rendering. Three image normalizations are compared in relation with the linear subspaces and eigenspaces, and we conclude that normalization by L1-norm, which normalizes the total sum of intensities, is the best for our purposes. Based on noise analysis in the normalized image space (NIS), an image correction algorithm is constructed, which is accomplished by iterative projections along with corrections of an image to an eigenspace in NIS. Experimental results show that the proposed method works well for natural images which include various kinds of noise shadows, reflections and occlusions. The proposed method provides a feasible solution to object recognition based on the illumination cone. The technique can also be extended to face detection of unknown persons and registration/recognition using eigenfaces. No potential conflict of interest relevant to this article was reported.

IEEE Computer Society Acta Medica Okayama 2004 Robust face recognition by combining projection-based image correction and decomposed eigenface 241 247 EN Takeshi Shakunaga Fumihiko Sakaue Kazuma Shigenari This work presents a robust face recognition method, which can work even when an insufficient number of images are registered for each person. The method is composed of image correction and image decomposition, both of which are specified in the normalized image space (NIS). The image correction [(F. Sakaue and T. Shakunaga, 2004), (T. Shakunaga and F. Sakaue, 2002)] is realized by iterative projections of an image to an eigenspace in NIS. It works well for natural images having various kinds of noise, including shadows, reflections, and occlusions. We have proposed decomposition of an eigenface into two orthogonal eigenspaces [T. Shakunaga and K. Shigenari, 2001], and have shown that the decomposition is effective for realizing robust face recognition under various lighting conditions. This work shows that the decomposed eigenface method can be refined by projection-based image correction. No potential conflict of interest relevant to this article was reported.

IEEE Computer Society Acta Medica Okayama 1550-6185 2005 Coordination of appearance and motion data for virtual view generation of traditional dances 118 125 EN Yuji Kamon Ryo Yamane Yasuhiro Mukaigawa Takeshi Shakunaga A novel method is proposed for virtual view generation of traditional dances. In the proposed framework, a traditional dance is captured separately for appearance registration and motion registration. By coordinating the appearance and motion data, we can easily control virtual camera motion within a dancer-centered coordinate system. For this purpose, a coordination problem should be solved between the appearance and motion data, since they are captured separately and the dancer moves freely in the room. The present paper shows a practical algorithm to solve it. A set of algorithms are also provided for appearance and motion registration, and virtual view generation from archived data. In the appearance registration, a 3D human shape is recovered in each time from a set of input images after suppressing their backgrounds. By combining the recovered 3D shape and a set of images for each time, we can compose archived dance data. In the motion registration, stereoscopic tracking is accomplished for color markers placed on the dancer. A virtual view generation is formalized as a color blending among multiple views, and a novel and efficient algorithm is proposed for the composition of a natural virtual view from a set of images. In the proposed method, weightings of the linear combination are calculated from both an assumed viewpoint and a surface normal. No potential conflict of interest relevant to this article was reported.