The Experts below are selected from a list of 4710 Experts worldwide ranked by ideXlab platform
Yoichi Sato - One of the best experts on this subject based on the ideXlab platform.
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ICCV - Shape Reconstruction Based on Similarity in Radiance Changes under Varying Illumination
2007 IEEE 11th International Conference on Computer Vision, 2007Co-Authors: Imari Sato, Takahiro Okabe, Qiong Yu, Yoichi SatoAbstract:This paper presents a technique for determining an object's shape based on the similarity of radiance changes observed at points on its surface under Varying Illumination. To examine the similarity, we use an observation vector that represents a sequence of pixel intensities of a point on the surface under different lighting conditions. Assuming convex objects under distant Illumination and orthographic projection, we show that the similarity between two observation vectors is closely related to the similarity between the surface normals of the corresponding points. This enables us to estimate the object's surface normals solely from the similarity of radiance changes under unknown distant lighting by using dimensionality reduction. Unlike most previous shape reconstruction methods, our technique neither assumes particular reflection models nor requires reference materials. This makes our method applicable to a wide variety of objects made of different materials.
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Shape Reconstruction Based on Similarity in Radiance Changes under Varying Illumination
2007 IEEE 11th International Conference on Computer Vision, 2007Co-Authors: Imari Sato, Takahiro Okabe, Qiong Yu, Yoichi SatoAbstract:This paper presents a technique for determining an object's shape based on the similarity of radiance changes observed at points on its surface under Varying Illumination. To examine the similarity, we use an observation vector that represents a sequence of pixel intensities of a point on the surface under different lighting conditions. Assuming convex objects under distant Illumination and orthographic projection, we show that the similarity between two observation vectors is closely related to the similarity between the surface normals of the corresponding points. This enables us to estimate the object's surface normals solely from the similarity of radiance changes under unknown distant lighting by using dimensionality reduction. Unlike most previous shape reconstruction methods, our technique neither assumes particular reflection models nor requires reference materials. This makes our method applicable to a wide variety of objects made of different materials.
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ACCV (1) - Face recognition under Varying Illumination based on MAP estimation incorporating correlation between surface points
Computer Vision – ACCV 2006, 2006Co-Authors: Mihoko Shimano, Takahiro Okabe, Kenji Nagao, Imari Sato, Yoichi SatoAbstract:In this paper, we propose a new method for face recognition under Varying Illumination conditions using a single input image. Our method is based on a statistical shape-from-shading method which combines the strengths of the Lambertian model and statistical information obtained from a large number of images of different people under Varying Illumination. The main advantage of our method over the previous methods is that our method explicitly incorporates a correlation between surface points on a face in the MAP estimation of surface normals and albedos, so that a new image of the same face under novel Illumination can be synthesized correctly even when the face is partially shadowed. Furthermore, our method introduces pixel grouping and reliability measure in the MAP estimation in order to reduce computational cost while maintaining accuracy. We demonstrate the effectiveness of our proposed method via experiments with real images.
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face recognition under Varying Illumination based on map estimation incorporating correlation between surface points
Lecture Notes in Computer Science, 2006Co-Authors: Mihoko Shimano, Takahiro Okabe, Kenji Nagao, Imari Sato, Yoichi SatoAbstract:In this paper, we propose a new method for face recognition under Varying Illumination conditions using a single input image. Our method is based on a statistical shape-from-shading method which combines the strengths of the Lambertian model and statistical information obtained from a large number of images of different people under Varying Illumination. The main advantage of our method over the previous methods is that our method explicitly incorporates a correlation between surface points on a face in the MAP estimation of surface normals and albedos, so that a new image of the same face under novel Illumination can be synthesized correctly even when the face is partially shadowed. Furthermore, our method introduces pixel grouping and reliability measure in the MAP estimation in order to reduce computational cost while maintaining accuracy. We demonstrate the effectiveness of our proposed method via experiments with real images.
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Using extended light sources for modeling object appearance under Varying Illumination
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005Co-Authors: I. Sato, Takahiro Okabe, Yoichi Sato, K. IkeuchiAbstract:In this study, we demonstrate the effectiveness of using extended light sources for modeling the appearance of an object for Varying Illumination. Extended light sources have a radiance distribution that is similar to that of the Gaussian function and have the potential of functioning as a low-pass filter when the appearance of an object is sampled under them. This enables us to obtain a set of basis images of an object for variable Illumination from input images of the object taken under those light sources without suffering aliasing caused by insufficient sampling of its appearance. Furthermore, extended light sources are useful in terms of reducing high contrast in image intensities due to specular and diffuse reflection components. This helps us observe both specular and diffuse reflection components of an object in the same image taken with a single shutter speed. We have tested our proposed approach based on extended light sources with objects of complex appearance that are generally difficult to model using image-based modeling techniques.
Takahiro Okabe - One of the best experts on this subject based on the ideXlab platform.
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ICCV - Shape Reconstruction Based on Similarity in Radiance Changes under Varying Illumination
2007 IEEE 11th International Conference on Computer Vision, 2007Co-Authors: Imari Sato, Takahiro Okabe, Qiong Yu, Yoichi SatoAbstract:This paper presents a technique for determining an object's shape based on the similarity of radiance changes observed at points on its surface under Varying Illumination. To examine the similarity, we use an observation vector that represents a sequence of pixel intensities of a point on the surface under different lighting conditions. Assuming convex objects under distant Illumination and orthographic projection, we show that the similarity between two observation vectors is closely related to the similarity between the surface normals of the corresponding points. This enables us to estimate the object's surface normals solely from the similarity of radiance changes under unknown distant lighting by using dimensionality reduction. Unlike most previous shape reconstruction methods, our technique neither assumes particular reflection models nor requires reference materials. This makes our method applicable to a wide variety of objects made of different materials.
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Shape Reconstruction Based on Similarity in Radiance Changes under Varying Illumination
2007 IEEE 11th International Conference on Computer Vision, 2007Co-Authors: Imari Sato, Takahiro Okabe, Qiong Yu, Yoichi SatoAbstract:This paper presents a technique for determining an object's shape based on the similarity of radiance changes observed at points on its surface under Varying Illumination. To examine the similarity, we use an observation vector that represents a sequence of pixel intensities of a point on the surface under different lighting conditions. Assuming convex objects under distant Illumination and orthographic projection, we show that the similarity between two observation vectors is closely related to the similarity between the surface normals of the corresponding points. This enables us to estimate the object's surface normals solely from the similarity of radiance changes under unknown distant lighting by using dimensionality reduction. Unlike most previous shape reconstruction methods, our technique neither assumes particular reflection models nor requires reference materials. This makes our method applicable to a wide variety of objects made of different materials.
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ACCV (1) - Face recognition under Varying Illumination based on MAP estimation incorporating correlation between surface points
Computer Vision – ACCV 2006, 2006Co-Authors: Mihoko Shimano, Takahiro Okabe, Kenji Nagao, Imari Sato, Yoichi SatoAbstract:In this paper, we propose a new method for face recognition under Varying Illumination conditions using a single input image. Our method is based on a statistical shape-from-shading method which combines the strengths of the Lambertian model and statistical information obtained from a large number of images of different people under Varying Illumination. The main advantage of our method over the previous methods is that our method explicitly incorporates a correlation between surface points on a face in the MAP estimation of surface normals and albedos, so that a new image of the same face under novel Illumination can be synthesized correctly even when the face is partially shadowed. Furthermore, our method introduces pixel grouping and reliability measure in the MAP estimation in order to reduce computational cost while maintaining accuracy. We demonstrate the effectiveness of our proposed method via experiments with real images.
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face recognition under Varying Illumination based on map estimation incorporating correlation between surface points
Lecture Notes in Computer Science, 2006Co-Authors: Mihoko Shimano, Takahiro Okabe, Kenji Nagao, Imari Sato, Yoichi SatoAbstract:In this paper, we propose a new method for face recognition under Varying Illumination conditions using a single input image. Our method is based on a statistical shape-from-shading method which combines the strengths of the Lambertian model and statistical information obtained from a large number of images of different people under Varying Illumination. The main advantage of our method over the previous methods is that our method explicitly incorporates a correlation between surface points on a face in the MAP estimation of surface normals and albedos, so that a new image of the same face under novel Illumination can be synthesized correctly even when the face is partially shadowed. Furthermore, our method introduces pixel grouping and reliability measure in the MAP estimation in order to reduce computational cost while maintaining accuracy. We demonstrate the effectiveness of our proposed method via experiments with real images.
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Using extended light sources for modeling object appearance under Varying Illumination
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005Co-Authors: I. Sato, Takahiro Okabe, Yoichi Sato, K. IkeuchiAbstract:In this study, we demonstrate the effectiveness of using extended light sources for modeling the appearance of an object for Varying Illumination. Extended light sources have a radiance distribution that is similar to that of the Gaussian function and have the potential of functioning as a low-pass filter when the appearance of an object is sampled under them. This enables us to obtain a set of basis images of an object for variable Illumination from input images of the object taken under those light sources without suffering aliasing caused by insufficient sampling of its appearance. Furthermore, extended light sources are useful in terms of reducing high contrast in image intensities due to specular and diffuse reflection components. This helps us observe both specular and diffuse reflection components of an object in the same image taken with a single shutter speed. We have tested our proposed approach based on extended light sources with objects of complex appearance that are generally difficult to model using image-based modeling techniques.
Imari Sato - One of the best experts on this subject based on the ideXlab platform.
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ICCV - Shape Reconstruction Based on Similarity in Radiance Changes under Varying Illumination
2007 IEEE 11th International Conference on Computer Vision, 2007Co-Authors: Imari Sato, Takahiro Okabe, Qiong Yu, Yoichi SatoAbstract:This paper presents a technique for determining an object's shape based on the similarity of radiance changes observed at points on its surface under Varying Illumination. To examine the similarity, we use an observation vector that represents a sequence of pixel intensities of a point on the surface under different lighting conditions. Assuming convex objects under distant Illumination and orthographic projection, we show that the similarity between two observation vectors is closely related to the similarity between the surface normals of the corresponding points. This enables us to estimate the object's surface normals solely from the similarity of radiance changes under unknown distant lighting by using dimensionality reduction. Unlike most previous shape reconstruction methods, our technique neither assumes particular reflection models nor requires reference materials. This makes our method applicable to a wide variety of objects made of different materials.
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Shape Reconstruction Based on Similarity in Radiance Changes under Varying Illumination
2007 IEEE 11th International Conference on Computer Vision, 2007Co-Authors: Imari Sato, Takahiro Okabe, Qiong Yu, Yoichi SatoAbstract:This paper presents a technique for determining an object's shape based on the similarity of radiance changes observed at points on its surface under Varying Illumination. To examine the similarity, we use an observation vector that represents a sequence of pixel intensities of a point on the surface under different lighting conditions. Assuming convex objects under distant Illumination and orthographic projection, we show that the similarity between two observation vectors is closely related to the similarity between the surface normals of the corresponding points. This enables us to estimate the object's surface normals solely from the similarity of radiance changes under unknown distant lighting by using dimensionality reduction. Unlike most previous shape reconstruction methods, our technique neither assumes particular reflection models nor requires reference materials. This makes our method applicable to a wide variety of objects made of different materials.
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ACCV (1) - Face recognition under Varying Illumination based on MAP estimation incorporating correlation between surface points
Computer Vision – ACCV 2006, 2006Co-Authors: Mihoko Shimano, Takahiro Okabe, Kenji Nagao, Imari Sato, Yoichi SatoAbstract:In this paper, we propose a new method for face recognition under Varying Illumination conditions using a single input image. Our method is based on a statistical shape-from-shading method which combines the strengths of the Lambertian model and statistical information obtained from a large number of images of different people under Varying Illumination. The main advantage of our method over the previous methods is that our method explicitly incorporates a correlation between surface points on a face in the MAP estimation of surface normals and albedos, so that a new image of the same face under novel Illumination can be synthesized correctly even when the face is partially shadowed. Furthermore, our method introduces pixel grouping and reliability measure in the MAP estimation in order to reduce computational cost while maintaining accuracy. We demonstrate the effectiveness of our proposed method via experiments with real images.
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face recognition under Varying Illumination based on map estimation incorporating correlation between surface points
Lecture Notes in Computer Science, 2006Co-Authors: Mihoko Shimano, Takahiro Okabe, Kenji Nagao, Imari Sato, Yoichi SatoAbstract:In this paper, we propose a new method for face recognition under Varying Illumination conditions using a single input image. Our method is based on a statistical shape-from-shading method which combines the strengths of the Lambertian model and statistical information obtained from a large number of images of different people under Varying Illumination. The main advantage of our method over the previous methods is that our method explicitly incorporates a correlation between surface points on a face in the MAP estimation of surface normals and albedos, so that a new image of the same face under novel Illumination can be synthesized correctly even when the face is partially shadowed. Furthermore, our method introduces pixel grouping and reliability measure in the MAP estimation in order to reduce computational cost while maintaining accuracy. We demonstrate the effectiveness of our proposed method via experiments with real images.
Sung Hsiang Chang - One of the best experts on this subject based on the ideXlab platform.
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gabor filter based hand pose angle estimation for hand gesture recognition under Varying Illumination
Expert Systems With Applications, 2011Co-Authors: Deng-yuan Huang, Wu Chih Hu, Sung Hsiang ChangAbstract:Research highlights? We proposed a method for hand gesture recognition based on Gabor filters and support vector machines under Varying Illumination. ? The proposed method is robust against Varying Illumination and insensitive to hand-pose variations. ? The proposed method allows users to wear either a long- or short-sleeve shirt. ? The recognition rates are improved from 72.8% to 93.7% by using the proposed hand-pose correction module. In this paper, we present a novel approach for hand gesture recognition based on Gabor filters and support vector machine (SVM) classifiers for environments with Varying Illumination. The proposed method (1) is robust against Varying Illumination, which is achieved using an adaptive skin-color model switching method; (2) is insensitive to hand-pose variations, which is achieved using a Gabor filter-based gesture angle estimation and correction method; (3) allows users to wear either a long- or short-sleeve shirt, which is achieved using a method that segments the hand from the forearm. To evaluate the robustness of the proposed method, we created a database of hand gestures in realistic conditions. A recognition rate of 96.1% was achieved using the proposed method. A dynamic gesture recognition system is also presented for real-life conditions. In the proposed system, the recognition results improved from 72.8% to 93.7% when the hand-pose correction module was used, indicating that using the responses of Gabor filters to estimate the hand-pose angle is effective.
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Gabor filter-based hand-pose angle estimation for hand gesture recognition under Varying Illumination
Expert Systems with Applications, 2011Co-Authors: Deng-yuan Huang, Wu Chih Hu, Sung Hsiang ChangAbstract:In this paper, we present a novel approach for hand gesture recognition based on Gabor filters and support vector machine (SVM) classifiers for environments with Varying Illumination. The proposed method (1) is robust against Varying Illumination, which is achieved using an adaptive skin-color model switching method; (2) is insensitive to hand-pose variations, which is achieved using a Gabor filter-based gesture angle estimation and correction method; (3) allows users to wear either a long- or short-sleeve shirt, which is achieved using a method that segments the hand from the forearm. To evaluate the robustness of the proposed method, we created a database of hand gestures in realistic conditions. A recognition rate of 96.1% was achieved using the proposed method. A dynamic gesture recognition system is also presented for real-life conditions. In the proposed system, the recognition results improved from 72.8% to 93.7% when the hand-pose correction module was used, indicating that using the responses of Gabor filters to estimate the hand-pose angle is effective. © 2010 Elsevier Ltd. All rights reserved.
Deng-yuan Huang - One of the best experts on this subject based on the ideXlab platform.
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ICGEC - Eye Detection Based on Skin Color Analysis with Different Poses under Varying Illumination Environment
2011 Fifth International Conference on Genetic and Evolutionary Computing, 2011Co-Authors: Deng-yuan Huang, Wu Chih Hu, Mu-song ChenAbstract:In this paper, we propose a method of eye detection based on skin color analysis under Varying Illumination. The proposed method consists of several phases, including color conversion, skin color segmentation and face mask calculation, facial feature extraction and eye candidate determination, and detection of human eyes. To eliminate the effect of lighting change on the performance of eye detection, color conversion is first performed. Face mask calculation based on skin color segmentation is then carried out to reduce the possible searching region of human eyes. Eye candidates detected using facial features are used to define the possible human eyes. Human eyes are thus detected by the geometric features of gravity and spatial centers for these eye candidates. Results show that the proposed method works well for faces with different poses and multiple faces under Varying Illumination. The eye detection time of 21.8 ms is achieved for an image of size 213x320 pixels, indicating computational efficiency of the proposed system.
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gabor filter based hand pose angle estimation for hand gesture recognition under Varying Illumination
Expert Systems With Applications, 2011Co-Authors: Deng-yuan Huang, Wu Chih Hu, Sung Hsiang ChangAbstract:Research highlights? We proposed a method for hand gesture recognition based on Gabor filters and support vector machines under Varying Illumination. ? The proposed method is robust against Varying Illumination and insensitive to hand-pose variations. ? The proposed method allows users to wear either a long- or short-sleeve shirt. ? The recognition rates are improved from 72.8% to 93.7% by using the proposed hand-pose correction module. In this paper, we present a novel approach for hand gesture recognition based on Gabor filters and support vector machine (SVM) classifiers for environments with Varying Illumination. The proposed method (1) is robust against Varying Illumination, which is achieved using an adaptive skin-color model switching method; (2) is insensitive to hand-pose variations, which is achieved using a Gabor filter-based gesture angle estimation and correction method; (3) allows users to wear either a long- or short-sleeve shirt, which is achieved using a method that segments the hand from the forearm. To evaluate the robustness of the proposed method, we created a database of hand gestures in realistic conditions. A recognition rate of 96.1% was achieved using the proposed method. A dynamic gesture recognition system is also presented for real-life conditions. In the proposed system, the recognition results improved from 72.8% to 93.7% when the hand-pose correction module was used, indicating that using the responses of Gabor filters to estimate the hand-pose angle is effective.
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Gabor filter-based hand-pose angle estimation for hand gesture recognition under Varying Illumination
Expert Systems with Applications, 2011Co-Authors: Deng-yuan Huang, Wu Chih Hu, Sung Hsiang ChangAbstract:In this paper, we present a novel approach for hand gesture recognition based on Gabor filters and support vector machine (SVM) classifiers for environments with Varying Illumination. The proposed method (1) is robust against Varying Illumination, which is achieved using an adaptive skin-color model switching method; (2) is insensitive to hand-pose variations, which is achieved using a Gabor filter-based gesture angle estimation and correction method; (3) allows users to wear either a long- or short-sleeve shirt, which is achieved using a method that segments the hand from the forearm. To evaluate the robustness of the proposed method, we created a database of hand gestures in realistic conditions. A recognition rate of 96.1% was achieved using the proposed method. A dynamic gesture recognition system is also presented for real-life conditions. In the proposed system, the recognition results improved from 72.8% to 93.7% when the hand-pose correction module was used, indicating that using the responses of Gabor filters to estimate the hand-pose angle is effective. © 2010 Elsevier Ltd. All rights reserved.
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Eye Detection Based on Skin Color Analysis with Different Poses under Varying Illumination Environment
2011 Fifth International Conference on Genetic and Evolutionary Computing, 2011Co-Authors: Deng-yuan Huang, Wu Chih Hu, Mu-song ChenAbstract:In this paper, we propose a method of eye detection based on skin color analysis under Varying Illumination. The proposed method consists of several phases, including color conversion, skin color segmentation and face mask calculation, facial feature extraction and eye candidate determination, and detection of human eyes. To eliminate the effect of lighting change on the performance of eye detection, color conversion is first performed. Face mask calculation based on skin color segmentation is then carried out to reduce the possible searching region of human eyes. Eye candidates detected using facial features are used to define the possible human eyes. Human eyes are thus detected by the geometric features of gravity and spatial centers for these eye candidates. Results show that the proposed method works well for faces with different poses and multiple faces under Varying Illumination. The eye detection time of 21.8 ms is achieved for an image of size 213×320 pixels, indicating computational efficiency of the proposed system.
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feature based face detection against skin color like backgrounds with Varying Illumination
J. Inf. Hiding Multim. Signal Process., 2011Co-Authors: Wu Chih Hu, Deng-yuan Huang, Chingyu Yang, Chunhsiang HuangAbstract:A three-stage scheme for real-time reliable face detection is presented. The proposed three-stage scheme is a feature-based method that is mainly based on skin color and facial features. Skin regions are obtained using a YCbCr skin-color model in the first stage. In the second stage, a face template measure is used to obtain face candidates and then a suitable face box is used to effectively remove non-face regions from the face can- didates. Finally, facial features are measured to detect faces from face candidates in the third stage. Experimental results show that the proposed method has good performance in the face detection of faces in various poses, faces in skin color-like backgrounds, faces under Varying Illumination, and faces of various races.
