mlsanityData to 14 Oct 2026

On-device Real-time Hand Gesture Recognition

arXiv 2111.00038 ↗First posted 29 Oct 2021cs.CVcited by 6

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Abstract (arXiv)

We present an on-device real-time hand gesture recognition (HGR) system, which detects a set of predefined static gestures from a single RGB camera. The system consists of two parts: a hand skeleton tracker and a gesture classifier. We use MediaPipe Hands as the basis of the hand skeleton tracker, improve the keypoint accuracy, and add the estimation of 3D keypoints in a world metric space. We create two different gesture classifiers, one based on heuristics and the other using neural networks (NN).

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 5 of its 13 references that are in the map. First posted on arXiv 29 Oct 2021.

Builds on

5 of 13 references.

References · 5

  1. 2017Focal Loss for Dense Object Detectioncited by 752
  2. 2019MediaPipe: A Framework for Building Perception Pipelinescited by 583
  3. 2020MediaPipe Hands: On-device Real-time Hand Trackingcited by 161
  4. 2020BlazePose: On-device Real-time Body Pose trackingcited by 113
  5. 2020Weakly Supervised 3D Human Pose and Shape Reconstruction with Normalizing Flowscited by 94

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 3; 2024: 1; 2025: 0; 2026: 1.

6 papers.