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>\nAI 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":"
Researchers have engineered an AI-driven intelligent video analyser capable of performing action detection technology on humans.<\/p>\n","protected":false},"author":22,"featured_media":52001,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[830],"tags":[570,885],"acf":[],"yoast_head":"\n
AI breakthrough in action detection technology<\/title>\n \n \n \n \n \n \n \n \n \n \n \n \n\t \n\t \n\t \n \n \n \n \n \n\t \n\t \n\t \n