Weighted averaging fusion for multi‐view skeletal data and its application in action recognition
Open Access
- 1 March 2016
- journal article
- research article
- Published by Institution of Engineering and Technology (IET) in IET Computer Vision
- Vol. 10 (2), 134-142
- https://doi.org/10.1049/iet-cvi.2015.0146
Abstract
Existing studies in skeleton-based action recognition mainly utilise skeletal data taken from a single camera. Since the quality of skeletal tracking of a single camera is noisy and unreliable, however, combining data from multiple cameras can improve the tracking quality and hence increase the recognition accuracy. In this study, the authors propose a method called weighted averaging fusion which merges skeletal data of two or more camera views. The method first evaluates the reliability of a set of corresponding joints based on their distances to the centroid, then computes the weighted average of selected joints, that is, each joint is weighted by the overall reliability of the camera reporting the joint. Such obtained, fused skeletal data are used as the input to the action recognition step. Experiments using various frame-level features and testing schemes show that more than 10% improvement can be achieved in the action recognition accuracy using these fused skeletal data as compared with the single-view case.Keywords
Funding Information
- Korea Advanced Institute of Science and Technology
This publication has 35 references indexed in Scilit:
- Human activity recognition from 3D data: A reviewPattern Recognition Letters, 2014
- Human Action Recognition by Representing 3D Skeletons as Points in a Lie GroupPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- A survey of human motion analysis using depth imageryPattern Recognition Letters, 2013
- Model-based recognition of human actions by trajectory matching in phase spacesImage and Vision Computing, 2012
- Human action recognition using multiple viewsPublished by Association for Computing Machinery (ACM) ,2011
- A survey of vision-based methods for action representation, segmentation and recognitionComputer Vision and Image Understanding, 2011
- Does Human Action Recognition Benefit from Pose Estimation?Published by British Machine Vision Association and Society for Pattern Recognition ,2011
- A survey on vision-based human action recognitionImage and Vision Computing, 2010
- Machine Recognition of Human Activities: A SurveyIEEE Transactions on Circuits and Systems for Video Technology, 2008
- Free viewpoint action recognition using motion history volumesComputer Vision and Image Understanding, 2006