Augmented inputs for surveillance re-identification

Person Re-Identification (Re-ID) is one of the important applications for Surveillance. However, the performance of Re-ID is dependent on the input quality, which cannot be guaranteed from the surveillance systems. We explored the technique from Gait Re-ID to address viewpoint changes. From our find...

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Bibliographic Details
Published in:International journal of multimedia information retrieval 2024-03, Vol.13 (1), p.2, Article 2
Main Authors: Kasantikul, Rangwan, Kusakunniran, Worapan
Format: Article
Language:English
Subjects:
Automation
Computer Science
Data Mining and Knowledge Discovery
Database Management
Datasets
Deep learning
Image Processing and Computer Vision
Information retrieval
Information Storage and Retrieval
Information Systems Applications (incl.Internet)
Multimedia computer applications
Multimedia Information Systems
Regular Paper
Surveillance
Surveillance systems
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Summary:Person Re-Identification (Re-ID) is one of the important applications for Surveillance. However, the performance of Re-ID is dependent on the input quality, which cannot be guaranteed from the surveillance systems. We explored the technique from Gait Re-ID to address viewpoint changes. From our findings, adding horizontally mirrored image into an auxiliary pipeline can achieve a modest performance uplift in our test (0.8% net increase in mean average precision and 0.9% increase in Rank-1 accuracy) in MARS dataset. This extra pipeline can be substituted by Heterogeneous Input Triplet Loss (hiTri) for minimal performance loss. The overall performance of the proposed method outperforms state-of-the-art techniques on well-known datasets. Further investigations on other auxiliary input types are warranted.
ISSN:2192-6611
2192-662X
DOI:10.1007/s13735-023-00309-1