JSAI2020

Presentation information

Interactive Session

[4Rin1] Interactive 2

Fri. Jun 12, 2020 9:00 AM - 10:40 AM Room R01 (jsai2020online-2-33)

[4Rin1-57] Video-Based Behavioral Analysis System "Actlyzer"

〇Yuka Sugimura1, Daisuke Uchida1, Genta Suzuki1, Toshio Endoh1 (1.FUJITSU LABORATORIES LTD.)

Keywords:Social system, Behavioral analysis, Suspicious behavior detection

We have innovated an AI technology for video-based behavioral analysis. Dubbed "Actlyzer", the tech can recognize a variety of subtle and complex human activities without relying on large amounts of training data.
Deep learning technologies conventionally demand large amounts of video data for training systems to recognize individual behaviors, and video data must be collected from scratch in order to add each new behavior. This time-consuming process means that it can often take several months to introduce functional AI into the field.
Taking advantage of the fact that human behaviors generally consist of a combination of basic movements and actions, (e.g. walking, nodding, extending the hand) we have created a technology that makes it possible to recognize more complex human behaviors by training the AI to recognize about 100 basic actions in advance.
Potential use cases for this new technology include automatic detection of individuals engaged in suspicious-seeming activity, recognition of purchase behavior by customers, and training applications through comparing the skills of experienced and novice workers at factories, to name a few.

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