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Hierarchical relaxed partitioning system for activity recognition
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Azhar, Faisal and Li, Chang-Tsun (2017) Hierarchical relaxed partitioning system for activity recognition. IEEE Transactions on Cybernetics, 47 (3). pp. 784-795. doi:10.1109/TCYB.2016.2526970
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Official URL: http://doi.org/10.1109/TCYB.2016.2526970
Abstract
A hierarchical relaxed partitioning system (HRPS) is proposed for recognizing similar activities which has a feature space with multiple overlaps. Two feature descriptors are built from the human motion analysis of a 2D stick figure to represent cyclic and non-cyclic activities. The HRPS first discerns the pure and impure activities, i.e., with no overlaps and multiple overlaps in the feature space respectively, then tackles the multiple overlaps problem of the impure activities via an innovative majority voting scheme. The results show that the proposed method robustly recognises various activities of two different resolution data sets, i.e., low and high (with different views). The advantage of HRPS lies in the real-time speed, ease of implementation and extension, and non-intensive training.
| Item Type: | Journal Article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||||||
| Divisions: | Faculty of Science > Computer Science | ||||||||
| Library of Congress Subject Headings (LCSH): | Decision trees, Human activity recognition | ||||||||
| Journal or Publication Title: | IEEE Transactions on Cybernetics | ||||||||
| Publisher: | IEEE Computer Society | ||||||||
| ISSN: | 2168-2267 | ||||||||
| Official Date: | March 2017 | ||||||||
| Dates: |
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| Volume: | 47 | ||||||||
| Number: | 3 | ||||||||
| Number of Pages: | 12 | ||||||||
| Page Range: | pp. 784-795 | ||||||||
| DOI: | 10.1109/TCYB.2016.2526970 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access |
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