Real Time Multi-Object Detection for Helmet Safety

• URL: http://arxiv.org/abs/2205.09878v1
• Date: Thu, 19 May 2022 21:56:03 GMT
• Title: Real Time Multi-Object Detection for Helmet Safety
• Authors: Mrinal Mathur, Archana Benkkallpalli Chandrashekhar, Venkata Krishna Chaithanya Nuthalapati
• Abstract summary: We are trying to implement a computer vision based ML algorithms capable of assigning detected helmet impacts to correct players via tracking information. This will also allow them to review previous plays and explore the trends in exposure over time.
• Score: 0.9434133337939499
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The National Football League and Amazon Web Services teamed up to develop the best sports injury surveillance and mitigation program via the Kaggle competition. Through which the NFL wants to assign specific players to each helmet, which would help accurately identify each player's "exposures" throughout a football play. We are trying to implement a computer vision based ML algorithms capable of assigning detected helmet impacts to correct players via tracking information. Our paper will explain the approach to automatically track player helmets and their collisions. This will also allow them to review previous plays and explore the trends in exposure over time.

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