Guoying Zhao - Academia.edu (original) (raw)

Papers by Guoying Zhao

Research paper thumbnail of Dynamic Texture Recognition Using Volume Local Binary Patterns

Lecture Notes in Computer Science, 2007

Research paper thumbnail of Boosted multi-resolution spatiotemporal descriptors for facial expression recognition

Pattern Recognition Letters, 2009

Research paper thumbnail of Principal appearance and motion from boosted spatiotemporal descriptors

2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008

Research paper thumbnail of Experiments with Facial Expression Recognition using Spatiotemporal Local Binary Patterns

Multimedia and Expo, 2007 IEEE International Conference on, 2007

Research paper thumbnail of Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000

Research paper thumbnail of Texture Based Description of Movements for Activity Analysis

Computer Vision Theory and Applications, 2008

... The method uses aligned silhouettes and silhouettes are readily available in their database. ... more ... The method uses aligned silhouettes and silhouettes are readily available in their database. ... In the first scenario, we show the proposed LBP-based features cluster even without a powerful modeling method. ... 3.1 Feature Analysis ...

Research paper thumbnail of Human Activity Recognition Using a Dynamic Texture Based Method

British Machine Vision Conference, 2008

We present a novel approach for human activity reco gnition. The method uses dynamic texture desc... more We present a novel approach for human activity reco gnition. The method uses dynamic texture descriptors to describe human movements in a spatiotemporal way. The same features are also use d for human detection, which makes our whole approach computationally simple. Following recent trends in computer vision research , our method works on image data rather than silhouettes. We test

Research paper thumbnail of Amplitude spectrum-based gait recognition

Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings., 2004

Gait is a biometric feature and identification of people from gait captured on video that has bec... more Gait is a biometric feature and identification of people from gait captured on video that has become a challenging problem in computer vision. A recognition method based on amplitude spectrum (Fourier spectrum) of frequency domain is proposed. Fourier spectrum reflects the frequency feature of person's pose in the current frame. After getting the period and key poses through the whole

Research paper thumbnail of Human Motion Recognition and Simulation Based on Retrieval

Journal of Computer Research and Development, 2006

Research paper thumbnail of Common Spatial Patterns for Real-Time Classification of Human Actions

Systems & Control Letters, 2010

We present a discriminative approach to human action recognition. At the heart of our approach is... more We present a discriminative approach to human action recognition. At the heart of our approach is the use of common spatial patterns (CSP), a spatial filter technique that transforms temporal feature data by using differences in variance between two classes. Such a transformation focuses on differences between classes, rather than on modeling each class individually. As a result, to distinguish

Research paper thumbnail of Unsupervised dynamic texture segmentation using local spatiotemporal descriptors

2008 19th International Conference on Pattern Recognition, 2008

Research paper thumbnail of Combining dynamic texture and structural features for speaker identification

Proceedings of the 2nd ACM workshop on Multimedia in forensics, security and intelligence - MiFor '10, 2010

Research paper thumbnail of Learning mappings for face synthesis from near infrared to visual light images

2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009

Research paper thumbnail of Facial expression classification based on local spatiotemporal edge and texture descriptors

Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research - MB '10, 2010

Facial expressions are emotionally, socially and otherwise meaningful reflective signals in the f... more Facial expressions are emotionally, socially and otherwise meaningful reflective signals in the face. Facial expressions play a critical role in human life, providing an important channel of nonverbal communication. Automation of the entire process of expression analysis can potentially facilitate human-computer interaction, making it to resemble mechanisms of human-human communication. In this paper, we present an ongoing research that aims

Research paper thumbnail of Modeling pixel process with scale invariant local patterns for background subtraction in complex scenes

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010

Research paper thumbnail of Dynamic texture synthesis using a spatial temporal descriptor

2009 16th IEEE International Conference on Image Processing (ICIP), 2009

Dynamic textures are image sequences with visual pattern repetition in time and space, such as sm... more Dynamic textures are image sequences with visual pattern repetition in time and space, such as smoke, flames, moving objects and so on. Dynamic texture synthesis is to provide a continuous and infinitely varying stream of images by doing operations on dynamic textures. Considering that the previous video texture method provides high-quality visual results, but its representation does not well explore the temporal correlation among frames, we develop a novel spatial temporal descriptor for frame description accompanied with a similarity measure on the basis of the video texture method. Compared with the previous one, our method considers both the spatial and temporal domains of video sequences in representation; moreover, combines the local and global description on each spatial-temporal plane. From experimental results, the proposed method achieves better performance in both the syntheses of natural scene and human motion. Especially, it has the characteristic to be robust to noise in remodeling videos into infinite time domain.

Research paper thumbnail of Dynamic Facial Expression Recognition Using A Bayesian Temporal Manifold Model

Procedings of the British Machine Vision Conference 2006, 2006

Research paper thumbnail of Facial expression recognition from near-infrared videos

Facial expression recognition is to determine the emotional state of the face regardless of its i... more Facial expression recognition is to determine the emotional state of the face regardless of its identity. Most of the existing datasets for facial expressions are captured in a visible light spectrum. However, the visible light (VIS) can change with time and location, causing significant variations in appearance and texture. In this paper, we present a novel research on a dynamic

Research paper thumbnail of Facial expression recognition from near-infrared video sequences

2008 19th International Conference on Pattern Recognition, 2008

Facial expressions can be thought as specific dynamic textures where local appearance and motion ... more Facial expressions can be thought as specific dynamic textures where local appearance and motion information need to be taken into account. We utilize local spatiotemporal operators to describe facial expressions. All current facial expression recognition databases are captured in visible light spectrum. Visual light usually changes with locations, and can also vary with time, which can cause significant variations in image appearance and texture. In this paper, we present a novel research on a dynamic facial expression recognition from near-infrared (NIR) video sequences. NIR imaging is robust with respect to illumination changes. Experiments on a new NIR database show promising and robust results against illumination variations.

Research paper thumbnail of LBP in Different Applications

Computational Imaging and Vision, 2011

Due to its excellent performance, robustness to illumination variations and computational efficie... more Due to its excellent performance, robustness to illumination variations and computational efficiency the LBP has been used in a wide variety of different image analysis problems and applications around the world. Among the most important areas of application are face analysis, biometrics, biomedical image analysis, industrial inspection and video analysis. This chapter presents a brief introduction to some representative papers from different application areas.

Research paper thumbnail of Dynamic Texture Recognition Using Volume Local Binary Patterns

Lecture Notes in Computer Science, 2007

Research paper thumbnail of Boosted multi-resolution spatiotemporal descriptors for facial expression recognition

Pattern Recognition Letters, 2009

Research paper thumbnail of Principal appearance and motion from boosted spatiotemporal descriptors

2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008

Research paper thumbnail of Experiments with Facial Expression Recognition using Spatiotemporal Local Binary Patterns

Multimedia and Expo, 2007 IEEE International Conference on, 2007

Research paper thumbnail of Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000

Research paper thumbnail of Texture Based Description of Movements for Activity Analysis

Computer Vision Theory and Applications, 2008

... The method uses aligned silhouettes and silhouettes are readily available in their database. ... more ... The method uses aligned silhouettes and silhouettes are readily available in their database. ... In the first scenario, we show the proposed LBP-based features cluster even without a powerful modeling method. ... 3.1 Feature Analysis ...

Research paper thumbnail of Human Activity Recognition Using a Dynamic Texture Based Method

British Machine Vision Conference, 2008

We present a novel approach for human activity reco gnition. The method uses dynamic texture desc... more We present a novel approach for human activity reco gnition. The method uses dynamic texture descriptors to describe human movements in a spatiotemporal way. The same features are also use d for human detection, which makes our whole approach computationally simple. Following recent trends in computer vision research , our method works on image data rather than silhouettes. We test

Research paper thumbnail of Amplitude spectrum-based gait recognition

Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings., 2004

Gait is a biometric feature and identification of people from gait captured on video that has bec... more Gait is a biometric feature and identification of people from gait captured on video that has become a challenging problem in computer vision. A recognition method based on amplitude spectrum (Fourier spectrum) of frequency domain is proposed. Fourier spectrum reflects the frequency feature of person's pose in the current frame. After getting the period and key poses through the whole

Research paper thumbnail of Human Motion Recognition and Simulation Based on Retrieval

Journal of Computer Research and Development, 2006

Research paper thumbnail of Common Spatial Patterns for Real-Time Classification of Human Actions

Systems & Control Letters, 2010

We present a discriminative approach to human action recognition. At the heart of our approach is... more We present a discriminative approach to human action recognition. At the heart of our approach is the use of common spatial patterns (CSP), a spatial filter technique that transforms temporal feature data by using differences in variance between two classes. Such a transformation focuses on differences between classes, rather than on modeling each class individually. As a result, to distinguish

Research paper thumbnail of Unsupervised dynamic texture segmentation using local spatiotemporal descriptors

2008 19th International Conference on Pattern Recognition, 2008

Research paper thumbnail of Combining dynamic texture and structural features for speaker identification

Proceedings of the 2nd ACM workshop on Multimedia in forensics, security and intelligence - MiFor '10, 2010

Research paper thumbnail of Learning mappings for face synthesis from near infrared to visual light images

2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009

Research paper thumbnail of Facial expression classification based on local spatiotemporal edge and texture descriptors

Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research - MB '10, 2010

Facial expressions are emotionally, socially and otherwise meaningful reflective signals in the f... more Facial expressions are emotionally, socially and otherwise meaningful reflective signals in the face. Facial expressions play a critical role in human life, providing an important channel of nonverbal communication. Automation of the entire process of expression analysis can potentially facilitate human-computer interaction, making it to resemble mechanisms of human-human communication. In this paper, we present an ongoing research that aims

Research paper thumbnail of Modeling pixel process with scale invariant local patterns for background subtraction in complex scenes

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010

Research paper thumbnail of Dynamic texture synthesis using a spatial temporal descriptor

2009 16th IEEE International Conference on Image Processing (ICIP), 2009

Dynamic textures are image sequences with visual pattern repetition in time and space, such as sm... more Dynamic textures are image sequences with visual pattern repetition in time and space, such as smoke, flames, moving objects and so on. Dynamic texture synthesis is to provide a continuous and infinitely varying stream of images by doing operations on dynamic textures. Considering that the previous video texture method provides high-quality visual results, but its representation does not well explore the temporal correlation among frames, we develop a novel spatial temporal descriptor for frame description accompanied with a similarity measure on the basis of the video texture method. Compared with the previous one, our method considers both the spatial and temporal domains of video sequences in representation; moreover, combines the local and global description on each spatial-temporal plane. From experimental results, the proposed method achieves better performance in both the syntheses of natural scene and human motion. Especially, it has the characteristic to be robust to noise in remodeling videos into infinite time domain.

Research paper thumbnail of Dynamic Facial Expression Recognition Using A Bayesian Temporal Manifold Model

Procedings of the British Machine Vision Conference 2006, 2006

Research paper thumbnail of Facial expression recognition from near-infrared videos

Facial expression recognition is to determine the emotional state of the face regardless of its i... more Facial expression recognition is to determine the emotional state of the face regardless of its identity. Most of the existing datasets for facial expressions are captured in a visible light spectrum. However, the visible light (VIS) can change with time and location, causing significant variations in appearance and texture. In this paper, we present a novel research on a dynamic

Research paper thumbnail of Facial expression recognition from near-infrared video sequences

2008 19th International Conference on Pattern Recognition, 2008

Facial expressions can be thought as specific dynamic textures where local appearance and motion ... more Facial expressions can be thought as specific dynamic textures where local appearance and motion information need to be taken into account. We utilize local spatiotemporal operators to describe facial expressions. All current facial expression recognition databases are captured in visible light spectrum. Visual light usually changes with locations, and can also vary with time, which can cause significant variations in image appearance and texture. In this paper, we present a novel research on a dynamic facial expression recognition from near-infrared (NIR) video sequences. NIR imaging is robust with respect to illumination changes. Experiments on a new NIR database show promising and robust results against illumination variations.

Research paper thumbnail of LBP in Different Applications

Computational Imaging and Vision, 2011

Due to its excellent performance, robustness to illumination variations and computational efficie... more Due to its excellent performance, robustness to illumination variations and computational efficiency the LBP has been used in a wide variety of different image analysis problems and applications around the world. Among the most important areas of application are face analysis, biometrics, biomedical image analysis, industrial inspection and video analysis. This chapter presents a brief introduction to some representative papers from different application areas.