# Gesture-based Human-Machine Interaction: Taxonomy, Problem Definition, and Analysis

arXiv: https://arxiv.org/abs/2201.10186 · HTML: https://mlsanity.com/paper/2201.10186/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Jan 2022.

## Built on by (most cited first, 3 of 3)

- [Head and eye egocentric gesture recognition for human-robot interaction using eyewear cameras](https://mlsanity.com/paper/2201.11500/) (2022)
- [A Task and Motion Planning Framework Using Iteratively Deepened AND/OR Graph Networks](https://mlsanity.com/paper/2503.07700/) (2025)
- [Towards Open-set Gesture Recognition via Feature Activation Enhancement and Orthogonal Prototype Learning](https://mlsanity.com/paper/2312.02535/) (2023)

## Abstract (arXiv)

The possibility for humans to interact with physical or virtual systems using gestures has been vastly explored by researchers and designers in the last twenty years to provide new and intuitive interaction modalities. Unfortunately, the literature about gestural interaction is not homogeneous, and it is characterised by a lack of shared terminology. This leads to fragmented results and makes it difficult for research activities to build on top of state-of-the-art results and approaches. The analysis in this paper aims at creating a common conceptual design framework to enforce development efforts in gesture-based human-machine interaction. The main contributions of the paper can be summarised as follows: (i) we provide a broad definition for the notion of functional gesture in human-machine interaction, (ii) we design a flexible and expandable gesture taxonomy, and (iii) we put forward a detailed problem statement for gesture-based human-machine interaction. Finally, to support our main contribution, the paper presents, and analyses 83 most pertinent articles classified on the basis of our taxonomy and problem statement.