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
2025
Experiential space analysis: scoring tranquil, social, and explorative places in habitable buildingsA framework using spatial analysis to score the tranquil, social, and…
2024
XLB: A Differentiable Massively Parallel Lattice Boltzmann Library in PythonThis research introduces the XLB library, a scalable Python-based…
2023
Leveraging Graph Neural Networks for Graph Regression and Effective Enumeration ReductionGraph-based framework represents aspects of optimal thermal management…
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