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    Automatic Analysis and Tracking of Motile Cells in Video Microscopy

    , M.Sc. Thesis Sharif University of Technology Shayegh, Zahra (Author) ; Vosughi Vahdat, Bijan (Supervisor) ; Rabiei, Hamid Reza (Supervisor) ; Salman Yazdi, Reza (Co-Advisor)
    Abstract
    Analysis of semen and quality assessments of sperm cells is of great importance in scrutiny of male fertility. Several methods have been introduced for analyzing and identification of the sperm motility and morphology in a semen sample. Identifying and tracking of rapid and variant movements of multiple sperms, in a short duration of time, is somewhat difficult and complex for human, even for an expert. Then applying semi-automated or automated (un-supervised) methods, based on image analysis and computing, spread fast and computer aided semen analyzer systems, became wildly used in clinical and research laboratories.
    In this paper we propose an efficient multiple tracking methods to... 

    Human Action Recognition Using Expandable Graphical Models

    , M.Sc. Thesis Sharif University of Technology Moradi, Reza (Author) ; Kasaei, Shohreh (Supervisor)
    Abstract
    In recent years, ability of computers to recognize human actions, because of numerousapplications, has attracted scientists. Surveillancesystems in house, work and public places, human computer interaction, study of human movement problems, remote supervision of ill or old people and sport training are only some of the applications. In this thesis 10 actions are considered. These actions are Walking, Running, Galloping side, Bending, Jump jacking, Jumping, Jumping in place, Skipping, Waving one hand and Waving two hands. All actions exist in Weisemann dataset so this dataset is used as training and testing dataset. Here important objectives are recognising human action so that it is... 

    3D Human Body Pose Estimation Using Multi-view Videos

    , M.Sc. Thesis Sharif University of Technology Ramezanpour Namaghi, Sadegh (Author) ; Kasaei, Shohreh (Supervisor)
    Abstract
    Estimating 3D pose of the human body in videos has many potential applications in motion analysis, surveillance and human computer interfaces. In the last decade using more than one camera causes more accurate pose estimation. Most of the previous works use calibrated and fixed cameras but in action this is not a realistic assumption and using some arbitrary moving cameras is more likely. We introduce a novel method for this purpose. Our approach does not require specifying locations and directions of the cameras. The method uses a database of 3D poses for different human activities. This database includes body silhouettes from multiple viewpoints. To estimate the 3D body pose, silhouettes...