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Hotspots Detection for Machine Operation in Egocentric Vision

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publication2017 15th IAPR International Conference on Machine Vision Applications (MVA)
Publisher or commissioning bodyInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages4
StateAccepted/In press - 13 Mar 2017
Event15th IAPR Conference on Machine Vision Applications -

Conference

Conference15th IAPR Conference on Machine Vision Applications
Period8/05/17 → …

Abstract

This paper introduces a novel idea of unsupervised hotspots detection from first person vision (FPV) records. The purpose is to gather typical patterns of machine operations based on touching or manipulating those hotspots and summarize the patterns as guides for operations such as online operating manuals. We chose sewing machine operation as an example and demonstrated that, a good performance of hotspots detection can be achieved by utilizing multiple features, especially touch and hand motion. More importantly, detected hotspots in both temporal and spatial locations matches well the positions of key components such as buttons, levers, and other important portions essential for operating the machine.

Event

15th IAPR Conference on Machine Vision Applications : (MVA2017)

Duration8 May 2017 → …

Event: Conference

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Documents

Documents

  • Full-text PDF (accepted author manuscript)

    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) will be available online via IEEE. Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 595 KB, PDF-document

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