Actions speak louder than words: Searching human action video based on body movement
Journal
MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
ISBN
9781450310895
Date Issued
2012-12-26
Author(s)
Abstract
Human action video search is a frequent demand in multimedia applications, and conventional video search schemes based on keywords usually fail to correctly find relevant videos due to noisy video tags. Observing the widespread use of Kinect-like depth cameras, we propose to search human action videos by directly performing the target action with body movements. Human actions are captured by Kinect and the recorded depth information is utilized to measure the similarity between the query action and each human action video in the database. We use representative depth descriptors without learning optimization to achieve real-time and promising performance as compatible as those of the leading methods based on color images and videos. Meanwhile, a large Depth-included Human Action video dataset, namely DHA, is collected to prove the effectiveness of the proposed video search system. © 2012 Authors.
Subjects
depth information | human action recognition | human action video retrieval
SDGs
Type
conference paper