Table · dataset · 2024
DHP19: Dynamic Vision Sensor 3D Human Pose Dataset
Listed in ETH Zürich Research Collection
Human pose estimation has dramatically improved thanks to the continuous developments in deep learning.
Description
However, marker-free human pose estimation based on standard frame-based cameras is still slow and power hungry for real-time feedback interaction because of the huge number of operations necessary for large Convolutional Neural Network (CNN) inference. Event-based cameras such as the Dynamic Vision Sensor (DVS) quickly output sparse moving-edge information.
Their sparse and rapid output is ideal for driving low-latency CNNs, thus potentially allowing real-time interaction for human pose estimators. Although the application of CNNs to standard frame-based cameras for human pose estimation is well established, their application to event-based cameras is still under study. This paper proposes a novel benchmark dataset of human body movements, the Dynamic Vision Sensor Human Pose dataset (DHP19).
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It consists of recordings from 4 synchronized 346x260 pixel DVS cameras, for a set of 33 movements with 17 subjects. DHP19 also includes a 3D pose estimation model that achieves an average 3D pose estimation error of about 8 cm, despite the sparse and reduced input data from the DVS.
Links
Where it is published
- ETH Zürich Research Collection record hdl.handle.net/20.500.11850/694758 ↗
landing page · from research collection ethz ch
- DOI doi.org/10.3929/ethz-b-000694758 ↗
DOI / persistent id · from research collection ethz ch
Catalogue records · 1
- OAI-PMH record research-collection.ethz.ch/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Awww.… ↗
metadata API · from research collection ethz ch
Topics
- From keywords
- Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Materials Science · Mathematics & Statistics · Medicine & Health · Physics · Psychology & Behavioral Science · Social Science
- Inferred from text
- Computer vision and multimedia computation 72%
Provenance · 1 source records, 19 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ETH Zürich Research Collection | oai:www.research-collection.ethz.ch:20.500.11850/694758 | 9 d ago | JSON v1 |
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|---|---|---|---|
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