|Title:||Motion-based head detection for lift control system|
Optical pattern recognition
Pattern recognition systems
Hong Kong Polytechnic University -- Dissertations
Department of Electronic and Information Engineering
|Pages:||ii, 100 leaves : ill. ; 30 cm|
|Abstract:||In this project, a motion-based head detection system is developed to segment and count moving human heads from complex background. The constraint line clustering and the block based motion compensation approach with Higher Order Statistics (HOS) are implemented to produce velocity field clusters. The constraint line clustering approach provides a robust method for scalar motion field generation. The block based motion compensation approach with HOS generates motion field vectors of an image sequence, which aims to produce compact segments of objects for further recognition. Higher order statistics algorithm instead of a typical mean square error minimization algorithm is implemented to eliminate Gaussian noise. The performance of the detector is evaluated on a number of image frames with different illumination conditions and injection of noise. In addition, a color feature-based approach is developed to extract heads from segmented objects. The possible applications in industry are also discussed in this dissertation.|
|Rights:||All rights reserved|
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