Paper Info
Title
Multi-view hand tracking using epipolar geometry-based consistent labeling for an industrial application
Abstract
This paper addresses a visual tracking and analysis method for automatic monitoring of an industrial manual assembly process, where each worker sequentially picks up components from different boxes during an assembling process. Automatic surveillance of assembling process would enable to reduce assembling errors by giving early warning. We propose a hand tracking and trajectory analysis method from videos captured by several uncalibrated cameras with overlapping views. The proposed method consists of three modules through single-view hand tracking, consistent labeling across views, and optimal decision from multi-view temporal dynamics. The main novelties of the paper include: (a) target model learning with multiple instances through K-means clustering applied to accommodate different levels of light reflection; (b) optimal criterion for consistent labeling of tracked hands across views, based on the symmetric epipolar distance; (c) backward correction of mis-detection by combining epipolar lines with previously tracked results; (d) a multi-view voting scheme for analyzing hand trajectory using binary hand location maps. Experiments have been conducted on videos by multiple uncalibrated cameras, where a person performs assembly operations. Test results and performance evaluation have shown the effectiveness of this method, in terms of multi-view consistent estimation of hand trajectories and accurate interpretation of component assembly actions.
Year
DOI
Venue
2013
10.1109/ICDSC.2013.6778217
2013 Seventh International Conference on Distributed Smart Cameras (ICDSC)
Keywords
DocType
Citations 
multi-view hand tracking,hand trajectory analysis,epipolar geometry,multiple view tracking,consistent labeling
Conference
1
PageRank 
References 
Authors
0.37
6
4
Name
Order
Citations
PageRank
Yixiao Yun1365.09
Irene Yu-Hua Gu261335.06
Julien Provost3538.79
Knut Åkesson430233.72