Gait-based person re-identification under covariate factors
Pattern Analysis and Applications, ISSN: 1433-755X, Vol: 22, Issue: 4, Page: 1629-1642
2019
- 13Citations
- 12Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Gait is recognized as an effective behavioral biometric trait. Gait pattern information can be captured and perceived from a distance thanks to its noninvasive and less intrusive nature. Therefore, gait could be well suited for person re-identification. However, semantic information like clothing and carrying bags has a remarkable influence on its accuracy. Unlike the existing solutions, this paper proposed a new method for gait-based person re-identification relying on dynamic selection of human parts. This method consists in computing a new person descriptor from relevant selected human parts. The selection of the most informative parts was achieved depending on the presence of semantic information. Our experiments were performed on the CASIA-B database revealing promising results and showing the effectiveness of the proposed method.
Bibliographic Details
Springer Science and Business Media LLC
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