Publication | ACM International Joint Conference on Pervasive and Ubiquitous Computing 2019
Demo
Semantic Human Activity Annotation Tool Using Skeletonized Surveillance Videos
Abstract
Demo: Semantic Human Activity Annotation Tool Using Skeletonized Surveillance Videos
Bokyung Lee, Michael Lee, Pan Zhang, Alex Tessier, Azam Khan
ACM International Joint Conference on Pervasive and Ubiquitous Computing 2019
Human activity data sets are fundamental for intelligent activity recognition in context-aware computing and intelligent video analysis. Surveillance videos include rich human activity data that are more realistic compared to data collected from a controlled environment. However, there are several challenges in annotating large data sets: 1) inappropriateness for crowd-sourcing because of public privacy, and 2) tediousness to manually select activities of people from busy scenes.
Download publicationAssociated Autodesk Researchers
Related Resources
2024
Reduced-order modeling of unsteady fluid flow using neural network ensemblesA framework to enhance the accuracy of time-series predictions in…
2022
A Discretization-free Metric For Assessing Quality Diversity AlgorithmsA multi-scale generative design model that adapts the Wave Function…
2017
Simulating Use Scenarios in Hospitals using Multi-Agent NarrativesAnticipating building-related complexities ensuing from occupants’…
2022
Neon: A Multi-GPU Programming Model for Grid-based ComputationsWe present Neon, a new programming model for grid-based computation…
Get in touch
Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.
Contact us