- Restrictions on Access:
- Open Access.
- The challenges faced when constructing a system to track biological cells coincides with the challenges when tracking pedestrians: they have complex topological shapes; wide range of behaviors; they move abruptly; they interact with other objects; their shape deforms; they leave the field of view (FOV) and enter the FOV; they split and merge. The similarities suggest that a system for tracking cells potentially works well for pedestrians.This work presents an automated tracking system that extends a framework, designed for tracking hundreds of biological cells in phase contrast microscopy, to tracking multiple human sized objects with LIDAR range data. It integrates various classic image-processing techniques with an adaptive interacting multiple model (IMM) estimator, a topologically constrained active contour, and spatiotemporal trajectory optimization. The framework processes the data with multiple independent collaborating modules. This module design facilitates a straight forward substitution of algorithms within a module without affecting the rest of the system.
- Dissertation Note:
- M.S. Pennsylvania State University, 2017.
- Technical Details:
- The full text of the dissertation is available as an Adobe Acrobat .pdf file ; Adobe Acrobat Reader required to view the file.
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