A Deployment Study of Identity-Gated Drone Gesture Control
Vision-based gesture control accepts commands from any hand in the camera field of view, which is unsafe in shared indoor spaces. This paper presents IGate, an identity-gated control stack that includes gesture control and face tracking, in which commands are admitted only when an enrolled operator is verified. The system performs few-shot user enrolment from 20 initial face frames, without prior user-specific training: verification compares an embedding of the current face crop against the enrolled template by cosine similarity, while face tracking uses proportional correction. Gesture control is achieved by classifying extracted hand landmarks using an RBF-SVM trained on a custom datase...
| Authors | Diyari Mohammed Salih, Ilyes Chaabeni, Naima Ait Oufroukh |
|---|---|
| Primary category | cs.RO |
| Published | 22 September 2026 |
| Last updated at source | 22 September 2026 |
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