mlsanityData to 14 Oct 2026

Frame-Synchronous Hand Gesture Detection by Projected Winding Order

arXiv 2609.13269 ↗First posted 7 Sep 2026cs.CV cs.GR cs.HCcited by 0

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Abstract (arXiv)

Gesture recognition on video is normally posed as classification: label each frame, then act on the label. That is adequate for control, where a command may be obeyed several frames late without a user noticing, and inadequate for synchronisation, where an output must be aligned to the frame on which the gesture physically occurred. We take the synchronisation problem for one common movement, the rotation of an open hand about its long axis, and show that it admits an exact solution needing no classifier, no training data and no calibration. Let s be the normalised two-dimensional cross product of the two palm edges at the wrist and the outer knuckles, under the projection the camera already performs. We prove that s factorises as k(theta)cos(theta) with |k| > 0 everywhere, so s vanishes exactly when the palm is edge-on and its sign tracks the face presented to the camera. Detection is therefore a zero crossing of one scalar, which yields an instant rather than an interval, and we prove the criterion invariant to image mirroring, hand scale and handedness, all from its algebraic form rather than from the landmark estimator. A two-handed interaction uses four fingertips as a window onto a restyled version of the same scene. We give a coverage predicate that stays correct when the hands cross, where the usual triangulation does not, and derive each free parameter of the three stylisation operators from a noise statistic rather than by inspection. Against a corpus with exact ground truth the criterion detects 95% of flips with no false positive in 240 near-miss sequences, and places each within 6.7 ms on average of the instant it occurred, a sixth of the interval at which the hand is observed, against 23.0 ms for reporting the bracketing sample. Reporting an event more finely than one samples follows from treating a gesture as the zero of a continuous quantity rather than a label.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 33 references that are in the map. First posted on arXiv 7 Sep 2026.

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References · 11

  1. 2022Generative Adversarial Networkscited by 5,627
  2. 2018OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,162
  3. 2019MediaPipe: A Framework for Building Perception Pipelinescited by 583
  4. 2017Hand Keypoint Detection in Single Images using Multiview Bootstrappingcited by 231
  5. 2020MediaPipe Hands: On-device Real-time Hand Trackingcited by 161
  6. 2020BlazePose: On-device Real-time Body Pose trackingcited by 113
  7. 2019BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUscited by 74
  8. 2019Real-time Hand Gesture Detection and Classification Using Convolutional Neural Networkscited by 30
  9. 2021White-Box Cartoonization Using An Extended GAN Frameworkcited by 4
  10. 2026A Modular Zero-Shot Pipeline for Accident Detection, Localization, and Classification in Traffic Surveillance Videocited by 2
  11. 2021Adversarial Open Domain Adaption Framework (AODA): Sketch-to-Photo Synthesiscited by 1

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