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Robust video foreground segmentation and face recognition

Journal of Shanghai University(English Edition) 2009年第4期13卷 311-315页

作者：管业鹏 School of Communication and Information Engineering Shanghai University Key Laboratory of Advanced Displays and System Application Ministry of Education Shanghai University

Face recognition provides a natural visual interface for human computer interaction （HCI） applications. The process of face recognition, however, is inhibited by variations in the appearance of face images caused by changes in lighting, expression, viewpoint, aging and introduction of occlusion. Although various algorithms have been presented for face recognition, face recognition is still a very challenging topic. A novel approach of real time face recognition for HCI is proposed in the paper. In view of the limits of the popular approaches to foreground segmentation, wavelet multi-scale transform based background subtraction is developed to extract foreground objects. The optimal selection of the threshold is automatically determined, which does not require any complex supervised training or manual experimental calibration. A robust real time face recognition algorithm is presented, which combines the projection matrixes without iteration and kernel Fisher discriminant analysis （KFDA） to overcome some difficulties existing in the real face recognition. Superior performance of the proposed algorithm is demonstrated by comparing with other algorithms through experiments. The proposed algorithm can also be applied to the video image sequences of natural HCI.

关键词： face recognition human computer interaction (HCI) foreground segmentation face detection threshold

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Study on Spot Addressing and segmentation Method for Microarray Image

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Chinese Journal of Biomedical Engineering(English Edition) 2016年第4期25卷 139-148页

作者： LIU Quan-jin ZHU Xing-yue ZHAO Zhi-min College of Science Nanjing University of Aeronautics and Astronautics School of Physics & Electronic Engineering Anqing Normal College

This paper presents a novel method of spot addressing and segmentation about the foreground segmentation of microarray image. In this paper,a spot addressing method based on particle swarm optimization(PSO),algorithm is proposed to have a further search for the center coordinate and radius of the spot whose region is determined by the projection method. Then,a foreground segmentation method is put forward to make the spot foreground segmentation based on the center coordinate and radius of the spot. The spot addressing and segmentation experiments on synthetic and real microarray images show that the proposed method is effective and feasible for the foreground segmentation of microarray image.

关键词： microarray image spot addressing foreground segmentation particle swarm optimization(PSO) algorithm

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维普期刊数据库

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Video foreground Detection via Sparse Representation

Video Foreground Detection via Sparse Representation

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第三十届中国控制会议

作者： LIU Shuangshuang,WANG Bo,ZHENG Zhihui School of Automation,Beijing Institute of Technology,Beijing 100081,P.R.China

In this article we propose a novel background model method based on sparse representation *** this framework the image is divided into N×N non-overlapping blocks,each block of a new input image has a sparse representation in the space spanned by background *** sparse representation is achieved by solving an l-regularized least squares problem which is computed by the preconditioned conjugate gradients(PCG) *** the block with large error vector is taken as the foreground *** experimental results show that proposed algorithm produces more accurate and stable results.

关键词： Spares Representation Background Subtraction foreground segmentation Object Detection

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