# GestureLens: Visual Analysis of Gestures in Presentation Videos

arXiv: https://arxiv.org/abs/2204.08894 · HTML: https://mlsanity.com/paper/2204.08894/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 53 references that are in the map.
- First posted on arXiv 19 Apr 2022.

## Builds on (most cited first, 9 of 9)

- [OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://mlsanity.com/paper/1812.08008/) (2018)
- [Learning Individual Styles of Conversational Gesture](https://mlsanity.com/paper/1906.04160/) (2019)
- [Robots Learn Social Skills: End-to-End Learning of Co-Speech Gesture Generation for Humanoid Robots](https://mlsanity.com/paper/1810.12541/) (2018)
- [M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis](https://mlsanity.com/paper/2107.08264/) (2021)
- [EmoCo: Visual Analysis of Emotion Coherence in Presentation Videos](https://mlsanity.com/paper/1907.12918/) (2019)
- [VoiceCoach: Interactive Evidence-based Training for Voice Modulation Skills in Public Speaking](https://mlsanity.com/paper/2001.07876/) (2020)
- [Persua: A Visual Interactive System to Enhance the Persuasiveness of Arguments in Online Discussion](https://mlsanity.com/paper/2204.07741/) (2022)
- [DeHumor: Visual Analytics for Decomposing Humor](https://mlsanity.com/paper/2107.08356/) (2021)
- [Automatic Identification of Non-Meaningful Body-Movements and What It Reveals About Humans](https://mlsanity.com/paper/1707.04790/) (2017)

## Built on by (most cited first, 4 of 4)

- [PromptMagician: Interactive Prompt Engineering for Text-to-Image Creation](https://mlsanity.com/paper/2307.09036/) (2023)
- [VideoPro: A Visual Analytics Approach for Interactive Video Programming](https://mlsanity.com/paper/2308.00401/) (2023)
- [A Survey on Deep Multi-modal Learning for Body Language Recognition and Generation](https://mlsanity.com/paper/2308.08849/) (2023)
- [Probing Experts' Perspectives on AI-Assisted Public Speaking Training](https://mlsanity.com/paper/2507.07930/) (2025)

## Abstract (arXiv)

Appropriate gestures can enhance message delivery and audience engagement in both daily communication and public presentations. In this paper, we contribute a visual analytic approach that assists professional public speaking coaches in improving their practice of gesture training through analyzing presentation videos. Manually checking and exploring gesture usage in the presentation videos is often tedious and time-consuming. There lacks an efficient method to help users conduct gesture exploration, which is challenging due to the intrinsically temporal evolution of gestures and their complex correlation to speech content. In this paper, we propose GestureLens, a visual analytics system to facilitate gesture-based and content-based exploration of gesture usage in presentation videos. Specifically, the exploration view enables users to obtain a quick overview of the spatial and temporal distributions of gestures. The dynamic hand movements are firstly aggregated through a heatmap in the gesture space for uncovering spatial patterns, and then decomposed into two mutually perpendicular timelines for revealing temporal patterns. The relation view allows users to explicitly explore the correlation between speech content and gestures by enabling linked analysis and intuitive glyph designs. The video view and dynamic view show the context and overall dynamic movement of the selected gestures, respectively. Two usage scenarios and expert interviews with professional presentation coaches demonstrate the effectiveness and usefulness of GestureLens in facilitating gesture exploration and analysis of presentation videos.