{"id":52000,"date":"2024-10-17T12:18:50","date_gmt":"2024-10-17T11:18:50","guid":{"rendered":"https:\/\/www.innovationnewsnetwork.com\/?p=52000"},"modified":"2024-10-17T12:18:50","modified_gmt":"2024-10-17T11:18:50","slug":"ai-breakthrough-in-action-detection-technology","status":"publish","type":"post","link":"https:\/\/www.innovationnewsnetwork.com\/ai-breakthrough-in-action-detection-technology\/52000\/","title":{"rendered":"AI breakthrough in action detection technology"},"content":{"rendered":"

Researchers at the University of Virginia\u2019s School of Engineering and Applied Science have engineered an AI-driven intelligent video analyser capable of performing action detection technology on humans.<\/h2>\n

The action detection system, called the Semantic and Motion-Aware Spatiotemporal Transformer Network<\/a> (SMAST), promises a wide range of societal benefits.<\/p>\n

These include enhancing surveillance systems and improving public safety, advanced motion tracking in healthcare, and refining how autonomous vehicles navigate through complex environments.<\/p>\n

\u201cThis AI technology<\/a> opens doors for real-time action detection in some of the most demanding environments,\u201d said professor and chair of the Department of Electrical and Computer Engineering, Scott T Acton, who led the project.<\/p>\n

AI technology for complex video analysis<\/h3>\n

The system relies on two key components to detect and understand complex human behaviours.<\/p>\n

The first is a multi-feature action detection model, which helps the AI focus on the most important parts of a scene \u2014 like a person or object \u2014 while ignoring unnecessary details. This makes the system more accurate at identifying what\u2019s happening, such as recognising someone throwing a ball instead of just moving their arm.<\/p>\n

The second key feature is a motion-aware 2D positional encoding algorithm, which helps the AI track how things move over time.<\/p>\n

By integrating these features, SMAST can accurately recognise complex actions in real-time, making it more effective in high-stakes scenarios like surveillance, healthcare diagnostics, or autonomous driving.<\/p>\n

SMAST redefines how machines detect and interpret human actions. Current systems struggle with chaotic, unedited, contiguous video footage, often missing the context of events.<\/p>\n

SMAST\u2019s innovative design allows it to capture the dynamic relationships between people and objects with remarkable accuracy, powered by AI components that allow it to learn and adapt from data.<\/p>\n

New standards in action detection technology<\/h3>\n

This huge leap in action detection technology means the AI system can identify actions like a runner crossing a street, a doctor performing a precise procedure or even a security threat in a crowded space.<\/p>\n

SMAST has already outperformed top-tier solutions across key academic benchmarks, including AVA, UCF101-24 and EPIC-Kitchens, setting new standards for accuracy and efficiency.<\/p>\n

\u201cThe societal impact could be huge,\u201d said Matthew Korban, a postdoctoral research associate in Acton\u2019s lab working on the project.<\/p>\n

\u201cWe\u2019re excited to see how this AI technology might transform industries, making video-based systems more intelligent and capable of real-time understanding.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

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