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Crowdsourced Verification for Operating Calving Surveillance Systems at an Early Stage | IEEE Conference Publication | IEEE Xplore

Crowdsourced Verification for Operating Calving Surveillance Systems at an Early Stage


Abstract:

This study attempts to use crowdsourcing to facilitate the operation of pattern-recognition-based video surveillance systems at an early stage. Target events (i.e. events...Show More

Abstract:

This study attempts to use crowdsourcing to facilitate the operation of pattern-recognition-based video surveillance systems at an early stage. Target events (i.e. events to be detected during surveillance) are not frequently observed in recorded video, so achieving reliable surveillance on the basis of machine learning requires a sufficient amount of target data. Acquiring sufficient data is time-consuming. However, operating unreliable surveillance systems can induce many false alarms. Crowdsourcing is introduced to address this problem by verifying the unreliable results in data-driven surveillance. Experimental simulation conducted using monitoring video of Japanese black beef cattle demonstrates that crowdsourced verification successfully reduced false alarms in calving detection systems.
Date of Conference: 10-15 January 2021
Date Added to IEEE Xplore: 05 May 2021
ISBN Information:
Print on Demand(PoD) ISSN: 1051-4651
Conference Location: Milan, Italy

References

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