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Permanent link (DOI): https://doi.org/10.7939/R3KH4T
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Shadow Removal for Action Recognition in a Smart Condo Environment Open Access
- Other title
Human Action Dataset
- Type of item
- Degree grantor
University of Alberta
- Author or creator
- Supervisor and department
Yang, Herbert (Computing Science)
- Examining committee member and department
Stroulia, Eleni (Computing Science)
Boulanger, Pierre (Computing Science)
Department of Computing Science
- Date accepted
- Graduation date
Master of Science
- Degree level
Depending on the method we choose for human action recognition, some algorithms require the localization of human in action videos as a preprocessing step. This preprocessing is more challenging in real environments with noises or varying illumination, and may include background subtraction, shadow removal and noise removal.
This thesis concerns with shadow removal problem with the goal of extracting human silhouette properly. Detecting shadows can be considered as a labeling problem and can be transformed into an energy minimization problem in a Markov Random Field framework. The advantage of the algorithm is that it considers the neighborhood information as well as chromaticity values of the pixels.
Also a new dataset is provided containing several daily actions of people living in a smart condo. The dataset is used in order to evaluate the proposed method. Moreover, it can be useful in action recognition and motion analysis studies with health care applications.
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