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Computer Vision and Image Processing Symposium

Although recent research of visual computing technology has witnessed great development on computer vision and image processing, the information explosion of daily released image/video data requires more intelligent computing scheme to handle such massive data. At the same time, the visual tasks from low-level to high-level vision confront many challenges, such as powerful and robust description for visual features; modeling diverse and complex visual patterns; and the designment of fast and efficient algorithm for real applications. The Symposium of Computer Vision and Image Processing is aiming at providing a platform to bring the new developments and original work, as well as possible emerging techniques with a potential to further improve the performance, or to lead to new algorithms and applications for all vision tasks. This symposium targets a mixed audience of researchers from several communities, such as computer vision, pattern recognition, image/video processing, information extraction/retrieval, data mining and machine learning, etc. Both theoretical contributions and application validations are welcome. Topics of interest include, but are not limited to:

Pattern Recognition and Machine Learning: Statistical, syntactic and structural pattern recognition; Artificial neural networks; Dimensionality reduction and manifold learning; Classification and clustering; Graphical Models for Pattern Recognition; Representation and analysis in pixel/voxel images; Support vector machines and kernel methods; 
Symbolic learning; Active and ensemble learning; Pattern recognition for big data; Transfer learning; Semi-supervised learning and spectral methods; Model selection; Reinforcement learning and temporal models;
Computer Vision and Robot Vision: Early/low-level vision; Biologically motivated vision; Illumination and reflectance modeling; Image based modeling; Physics based vision; Shape modeling and encoding; 3D shape recovery; Motion, tracking and video analysis; Kinect; 2D/3D object detection and recognition; Activity and event analysis;Scene understanding; Occlusion and shadow detection; Stereo and multiple view geometry; Reconstruction and camera motion estimation; Vision for graphics; Deep learning and convolutional neural networks; Vision for robotics;
Image and Video Processing: Image and video analysis and understanding; Sensor array & multichannel signal processing; Segmentation, features and descriptors; Texture and color analysis; Enhancement, denoising, restoration and filtering; Visual-based image/video quality assessment; Video motion detection and estimation; Coding, compression and super-resolution; Facial expression recognition; Affective computing; Human body motion and gesture based interaction; Multimedia analysis, indexing and retrieval; Depth & range sensor data processing and analysis;
Document Analysis, Biometrics and Pattern Recognition Applications: Character and Text Recognition; Handwriting Recognition; Graphics Recognition; Document Understanding; Gesture and Behavior Analysis; Mixed and Augmented Reality; Face, fingerprint and iris recognition; Biometric systems and applications; Multi-biometrics; Forensic biometrics and applications; Bioinformatics; Surveillance and Security; Search, Retrieval and Visualization; Industrial image analysis; Human computer interaction; Applications of pattern recognition to big data;
Biomedical Image Analysis and Applications: Medical image and signal analysis; Biological image and signal analysis; Modeling, simulation and visualization; Computer-aided detection and diagnosis; Image guidance and robot guidance of interventions; Medical and biological imaging; Segmentation of biomedical images; Molecular and cellular image analysis; Volumetric image analysis; Imaging and hardware for health care; Brain-computer interfaces; Data mining for biological databases; Algorithms for molecular biology; Deep learning for biomedical image analysis.
TPC chair
Dr. Zhongyuan Lai, JiangHan University
Dr. Guangwei Gao, Nanjing University of Posts and Telecommunications
Dr. Xin Jin, Beijing Electronic Science and Technology Institute
Dr. Leyuan Liu, Centrtal China Normal University
Assoc. Prof. Zhanyu Ma, Beijing Univeristy of Posts and Telecommunications
Assoc. Prof. Weihua Ou, Guiyang Normal University
Dr. Yibing Song, City University of Hong Kong
Prof. Wenyu Liu, Huazhong University of Science and Technology
Dr. Wei Wang, Institute of Automation of Chinese Academy of Sciences
Dr. Dan Wang, Beijing Institute of spacecraft system engineering
Assoc. Prof. Xin Wei, Nanjing University of Posts and Telecommunications
Dr. Zhijun Yao, The 723 Institute of China Shipbuilding Industry Corporation
Assoc. Prof. Yang Yu, Nanjing University
Prof. Yudong Zhang, Nanjing Normal University
Dr. Yu Zhou, Beijing Univeristy of Posts and Telecommunications
Dr. Yawen Fan, Nanjing University of Posts and Telecommunications
Assoc. Prof. Jiayi Ma, Wuhan University
Dr. Nannan Wang, Xi'dian University
Dr. Hu Zhu, Nanjing University of Posts and Telecommunications
Dr. Huiming Lu, Kyushu Institute of Technology
Dr. Jun Zhu, University of California, Los Angeles
 
 
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