Tapped delay multiclass support vector machines for industrial workflow recognition

Abstract

In this paper, a tapped delay multiclass support vector machine scheme is used for supervised job classification, based on video data taken from Nissan factory. The procedure is based on multiclass SVMs enhanced with the time dimension by incorporating additional information of n-th previous frames and allowing for user feedback when necessary. Such methodology will support the visual supervision of industrial environments by providing essential information to the supervisors and supporting their job.