# Casper DPM: Cascaded Perceptual Dynamic Projection Mapping onto Hands

arXiv: https://arxiv.org/abs/2409.04397 · HTML: https://mlsanity.com/paper/2409.04397/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Sep 2024.

## Built on by (most cited first, 7 of 7)

- [GS-ProCams: Gaussian Splatting-based Projector-Camera Systems](https://mlsanity.com/paper/2412.11762/) (2024)
- [LAPIG: Language Guided Projector Image Generation with Surface Adaptation and Stylization](https://mlsanity.com/paper/2503.12173/) (2025)
- [Shadowless Projection Mapping for Tabletop Workspaces with Synthetic Aperture Projector](https://mlsanity.com/paper/2603.11551/) (2026)
- [ProCap: Projection-Aware Captioning for Spatial Augmented Reality](https://mlsanity.com/paper/2604.00912/) (2026)
- [Setup-Independent Full Projector Compensation](https://mlsanity.com/paper/2604.01736/) (2026)
- [Physically-guided Image Generation for Multi-Projection Mapping](https://mlsanity.com/paper/2606.22477/) (2026)
- [FF-ProCams: Feed-Forward Gaussian Splatting for Projector-Camera System](https://mlsanity.com/paper/2607.17803/) (2026)

## Abstract (arXiv)

We present a technique for dynamically projecting 3D content onto human hands with short perceived motion-to-photon latency. Computing the pose and shape of human hands accurately and quickly is a challenging task due to their articulated and deformable nature. We combine a slower 3D coarse estimation of the hand pose with high speed 2D correction steps which improve the alignment of the projection to the hands, increase the projected surface area, and reduce perceived latency. Since our approach leverages a full 3D reconstruction of the hands, any arbitrary texture or reasonably performant effect can be applied, which was not possible before. We conducted two user studies to assess the benefits of using our method. The results show subjects are less sensitive to latency artifacts and perform faster and with more ease a given associated task over the naive approach of directly projecting rendered frames from the 3D pose estimation. We demonstrate several novel use cases and applications.