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This paper presents an approach to analyze and model tasks of machines being operated. The executions of the tasks were captured through egocentric vision. Each task was decomposed into a sequence of physical hand-machine interactions, which are described with touch-based hotspots and interaction patterns. Modeling the tasks was achieved by integrating the experiences of multiple experts and using a hidden Markov model (HMM). Here, we present the results of more than 70 recorded egocentric experiences of the operation of a sewing machine. Our methods show good potential for the detection of hand-machine interactions and modeling of machine operation tasks.
- Egocentric vision
- Machine operation experiences
- Task modeling
FingerprintDive into the research topics of 'Hotspot modeling of hand-machine interaction experiences from a head-mounted RGB-D camera'. Together they form a unique fingerprint.
- 1 Finished
4/04/16 → 2/02/22