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Object and action detection methods using MOSSE filters




Arn, Robert T., author
Kirby, Michael, advisor
Peterson, Chris, advisor
Draper, Bruce, committee member

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In this thesis we explore the application of the Minimum Output Sum of Squared Error (MOSSE) filter to object detection in images as well as action detection in video. We exploit the properties of the Fourier transform for computing correlations in two and three dimensions. We perform a comprehensive examination of the shape parameters of the desired target response and determine values to optimize the filter performance for specific objects and actions. In addition, we propose the Gaussian Iterative Response (GIR) algorithm and the Multi-Sigma Geometric Mean method to improve the MOSSE filter response on test signals. Also, new detection criteria are investigated and shown to boost the detection accuracy on two well-known data sets.


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