The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets
Open accessAbstract
Person re-identification (re-id) is a critical problem in video analytics applications such as security and surveillance. The public release of several datasets and code for vision algorithms has facilitated rapid progress in this area over the last few years. However, directly comparing re-id algorithms reported in the literature has become difficult since a wide variety of features, experimental protocols, and evaluation metrics are employed. In order to address this need, we present an extensive review and performance evaluation of single- and multi-shot re-id algorithms. The experimental protocol incorporates the most recent advances in both feature extraction and metric learning. To ensure a fair comparison, all of the approaches were implemented using a unified code library that includes 11 feature extraction algorithms and 22 metric learning and ranking techniques. All approaches were evaluated using a new large-scale dataset that closely mimics a real-world problem setting, in addition to 16 other publicly available datasets: VIPeR, GRID, CAVIAR, DukeMTMC4ReID, 3DPeS, PRID, V47, WARD, SAIVT-SoftBio, CUHK01, CHUK02, CUHK03, RAiD, iLIDSVID, HDA+, and Market1501. The evaluation codebase and results will be made publicly available for community use.
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“We anticipate that the benchmark will be updated (along the lines of the Middlebury benchmarks [31], [32]) as new techniques are implemented into our evaluation framework.”
MethodSUN RGB-D: A RGB-D scene understanding benchmark suite
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Cited by
(2014) · Advances in Computer Vision and Pattern Recognition · doi:10.1007/978-1-4471-6296-4 · Cited by 365
Metadata
- Authors
- Karanam, S., Gou, M., Wu, Z., Rates-Borras, A., Camps, O., & Radke, R. J.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2019-03-01
- Volume
- 41
- Issue
- 3
- Pages
- 523-536
- ISSN
- 0162-8828 (ISSN-L)
- 2160-9292
- 1939-3539
- OpenAlex
- W2560555192
- Cited by
- 247
- References
- 11
- FWCI
- 18.32
- Type
- journal article
- Language
- en
- Open access
- green
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- Karanam, S., Gou, M., Wu, Z., Rates-Borras, A., Camps, O., & Radke, R. J. (2019). A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2018.2807450
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