Natural Image Correction by Iterative Linear Projection onto (2009)
Fumihi Sakaue, Takeshi Shakunaga
The present paper reports an image correction method that is based on iterative projection onto eigenspaces. The fundamental method proposed in Shakunaga and Sakaue[ll] and involves iterative...
Appearance Tracker Based on Sparse Eigentemplate (2009)
Takeshi Shakunaga, Yasuharu Matsubara, Kiyoshi Noguchi
A novel scheme is proposed for the efficient object tracking by using partial projections of a sparse set of pixels to eigenspaces. This paper shows a theoretical framework of the sparse...
3-9 Simultaneous Estimation of Head Pose and Shape by Hierarchical Control System (2009)
Junji Satake, Takeshi Shakunaga
The present paper proposes a simultaneous estimation of both human head pose and shape. When head pose is estimated for a generic face model, a considerable estimation error is generated by the shape...
Decomposed Eigenface Method along with Image Correction for Robust Face Recognition (2009)
Kazuma Shigenari, Fumihiko Sakaue, Takeshi Shakunaga
We have proposed a decomposition of the eigenface into two orthogonal eigenspaces and have shown that the decomposition is effective for realizing robust face recognition under various lighting...
Human Tracking Based on Hierarchical Attention Control (2009)
Junji Satake, Takeshi Shakunaga
A hierarchical attention control model is introduced for implementing a human-like attention control in computer vision. The lowest layer of the hierarchy is called a window layer, in which each...
Coordination of Appearance and Motion Data for Virtual View Generation of Traditional Dances (2008)
Yuji Kamon, Ryo Yamane, Yasuhiro Mukaigawa, Takeshi Shakunaga, Yuji Kamon, Ryo Yamane, ...
data for virtual view generation of traditional dances
Classification of Photometric Factors Based on Photometric Linearization (2008)
Yasuhiro Mukaigawa, Yasunori Ishii, Takeshi Shakunaga
Abstract. We propose a new method for classification of photometric factors, such as diffuse reflection, specular reflection, attached shadow, and cast shadow. For analyzing real images, we utilize...
Virtual Exhibition of Traditional Dances by Blending Colors of Multiple Images (2008)
Takeshi Shakunaga, Yasuhiro Mukaigawa, Ryo Yamane, Daisuke Genda, Yuji Kamon
A color blending method for generating a high quality image sequence of human motion is presented. The 3D human shape is reconstructed by volume intersection and expressed as a set of voxels. As each...
Model-based SAR ATR System* (2007)
Katsushi Ikeuchi, M. D. Wheeler, Taku Yamazaki, Takeshi Shakunaga
Recognizing a target in synthetic-aperture radar (SAR) images is an important, yet challenging, application of the model-based vision technique. This paper describes a model-based SAR recogni-tion...
Sakaue, Fumihiko, Kobayashi, Makoto, Migita, Tsuyoshi, Shakunaga, Takeshi, Satake, Junji
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...
Sakaue, Fumihiko, Kobayashi, Makoto, Migita, Tsuyoshi, Shakunaga, Takeshi, Satake, Junji
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...
Coordination of appearance and motion data for virtual view generation of traditional dances (2005)
Kamon, Yuji, Yamane, Ryo, Mukaigawa, Yasuhiro, Shakunaga, Takeshi
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...
Coordination of appearance and motion data for virtual view generation of traditional dances (2005)
Kamon, Yuji, Yamane, Ryo, Mukaigawa, Yasuhiro, Shakunaga, Takeshi
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...
Shakunaga, Takeshi, Sakaue, Fumihiko, Shigenari, Kazuma
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...
Shakunaga, Takeshi, Sakaue, Fumihiko, Shigenari, Kazuma
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...
Mukaigawa, Yasuhiro, Genda, Daisuke, Yamane, Ryo, Shakunaga, Takeshi
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...
Mukaigawa, Yasuhiro, Genda, Daisuke, Yamane, Ryo, Shakunaga, Takeshi
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...
Shakunaga, Takeshi, Sakaue, Fumihiko
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...
Shakunaga, Takeshi, Sakaue, Fumihiko
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...
Decomposed eigenface for face recognition under various lighting conditions (2001)
Shakunaga, Takeshi, Shigenari, Kazuma
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...
Decomposed eigenface for face recognition under various lighting conditions (2001)
Shakunaga, Takeshi, Shigenari, Kazuma
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...
Cooperative distributed tracking for effective face registration (2000)
Takekazu Kato, Yasuhiro Mukaigawa, Takeshi Shakunaga
A three-layer framework is proposed for cooperative distributed face tracking. In this framework, multiple distributed cameras cooperate both for stable face tracking and for effective registrations....
Photometric image-based rendering for virtual lighting image synthesis (1999)
Mukaigawa, Yasuhiro, Mihashi, Sadahiko, Shakunaga, Takeshi
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...
Photometric image-based rendering for virtual lighting image synthesis (1999)
Mukaigawa, Yasuhiro, Mihashi, Sadahiko, Shakunaga, Takeshi
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...
Integration of eigentemplate and structure matching for automatic facial feature detection (1998)
Shakunaga, Takeshi, Ogawa, Keisuke, Oki, Shohei
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...
Integration of eigentemplate and structure matching for automatic facial feature detection (1998)
Shakunaga, Takeshi, Ogawa, Keisuke, Oki, Shohei
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...
Adaptive Model Based ATR System. (1997)
Ikeuchi, Katsushi, Collins, Robert, Shakunaga, Takeshi, Ohba, Khotara, Pomeleau, Dean
This project develops a SAR-ATR system that uses invariant histograms and deformable templates. An invariant histogram is a histogram of geometric invariants given by primitive feature sets....