Towards practical implementations of person re-identification from full video frames

Sumari, Felix O.; Machaca, Luigy; Huaman, Jose; Clua, Esteban; Guérin, Joris

doi:10.1016/j.patrec.2020.08.023

Cited by 6 publications

(1 citation statement)

References 11 publications

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“…Our work have a published in Pattern Recognition Letters [31], we thank everyone who was part of this research.…”

Section: Acknowledgmentmentioning

confidence: 99%

A Novel Human-Machine Hybrid Framework for Person Re-Identification from Full Frame Videos

Huayta,

Clúa,

Guérin

2021

Anais Estendidos Da XXXIV Conference on Graphics, Patterns and Images (SIBRAPI Estendido 2021)

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With the major adoption of automation for cities security, person re-identification (Re-ID) has been extensively studied. In this dissertation, we argue that the current way of studying person re-identification, i.e. by trying to re-identify a person within already detected and pre-cropped images of people, is not sufficient to implement practical security applications, where the inputs to the system are the full frames of the video streams. To support this claim, we introduce the Full Frame Person Re-ID setting (FF-PRID) and define specific metrics to evaluate FF-PRID implementations. To improve robustness, we also formalize the hybrid human-machine collaboration framework, which is inherent to any Re-ID security applications. To demonstrate the importance of considering the FF-PRID setting, we build an experiment showing that combining a good people detection network with a good Re-ID model does not necessarily produce good results for the final application. This underlines a failure of the current formulation in assessing the quality of a Re-ID model and justifies the use of different metrics. We hope that this work will motivate the research community to consider the full problem in order to develop algorithms that are better suited to real-world scenarios.

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“…Our work have a published in Pattern Recognition Letters [31], we thank everyone who was part of this research.…”

Section: Acknowledgmentmentioning

confidence: 99%

A Novel Human-Machine Hybrid Framework for Person Re-Identification from Full Frame Videos

Huayta,

Clúa,

Guérin

2021

Anais Estendidos Da XXXIV Conference on Graphics, Patterns and Images (SIBRAPI Estendido 2021)

Self Cite

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Improving Person Re-identification by Rich Feature Discovery with Self-guided Network

Zhou

Zhang

2021

Advances in Intelligent Automation and Soft Computing

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A semi-automated system for person re-identification adaptation to cross-outfit and cross-posture scenarios

et al. 2022

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Towards practical implementations of person re-identification from full video frames

Cited by 6 publications

References 11 publications

A Novel Human-Machine Hybrid Framework for Person Re-Identification from Full Frame Videos

A Novel Human-Machine Hybrid Framework for Person Re-Identification from Full Frame Videos

Improving Person Re-identification by Rich Feature Discovery with Self-guided Network

A semi-automated system for person re-identification adaptation to cross-outfit and cross-posture scenarios

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