UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor

Published: Sep 1, 2015
Abstract
Human action recognition has a wide range of applications including biometrics, surveillance, and human computer interaction. The use of multimodal sensors for human action recognition is steadily increasing. However, there are limited publicly available datasets where depth camera and inertial sensor data are captured at the same time. This paper describes a freely available dataset, named UTD-MHAD, which consists of four temporally...
Paper Details
Title
UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor
Published Date
Sep 1, 2015
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.