mlsanityData to 14 Oct 2026

A Brief Survey on Person Recognition at a Distance

arXiv 2212.08969 ↗First posted 17 Dec 2022cs.CVcited by 4

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Abstract (arXiv)

Person recognition at a distance entails recognizing the identity of an individual appearing in images or videos collected by long-range imaging systems such as drones or surveillance cameras. Despite recent advances in deep convolutional neural networks (DCNNs), this remains challenging. Images or videos collected by long-range cameras often suffer from atmospheric turbulence, blur, low-resolution, unconstrained poses, and poor illumination. In this paper, we provide a brief survey of recent advances in person recognition at a distance. In particular, we review recent work in multi-spectral face verification, person re-identification, and gait-based analysis techniques. Furthermore, we discuss the merits and drawbacks of existing approaches and identify important, yet under explored challenges for deploying remote person recognition systems in-the-wild.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 54 of its 104 references that are in the map. First posted on arXiv 17 Dec 2022.

Builds on

54 of 104 references.

References · 54

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38 more
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50 most cited of 54 All 54 (JSON)

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Cited by year

Citing papers per year: 2023: 2; 2024: 2.

4 papers.

  1. 2024Neural Eulerian Scene Flow Fieldscited by 15
  2. 2023ShARc: Shape and Appearance Recognition for Person Identification In-the-wildcited by 13
  3. 2024From Data to Insights: A Covariate Analysis of the IARPA BRIAR Dataset for Multimodal Biometric Recognition Algorithms at Altitude and Rangecited by 6
  4. 2023Human Body Model based ID using Shape and Pose Parameterscited by 0