Angel Group Co., Ltd.

Sensen Networks Group Pty Ltd

Subhash Challa

Nhat Vo

Louis Quinn

Duc Dinh Minh Vo

Zhi Li

Nhat Dinh Minh Vo

Some embodiments relate to a system for automated gaming recognition, the system comprising: at least one image sensor configured to capture image frames of a field of view including; a table game; at least one depth sensor configured to capture depth of field images of the field of view; and a computing device configured to receive the image frames and the depth of field images, and configured to process the received image frames and depth of field images in order to produce an automated recognition of at least one gaining state appearing in the field of view. Embodiments also relate to methods and computer-readable media for automated gaming recognition. Further embodiments relate to methods and systems for monitoring game play and/or gaming events on a gaming table.

System and method for automated table game activity recognition

Embodiments relate to systems, methods and computer readable media for gaming monitoring. In particular, embodiments process images to determine presence of a gaming object on a gaming table in the images. Embodiments estimate postures of one or more players in the images and based on the estimated postures determine a target player associated with the gaming object among the one or more players.

Gaming activity monitoring systems and methods

Embodiments relate to systems, methods and computer readable media for gaming monitoring. In particular, embodiments process images to determine presence of a gaining object on a gaming table in the images. Embodiments estimate postures of one or more players in the images and based on the estimated postures determine a target player associated with the gaming object among the one or more players.

Embodiments relate to systems and methods for gaming monitoring. In particular, embodiments relate to systems and methods for gaming monitoring based on machine learning processes configured to analyse captured images to identify or detect game objects and game events to monitor games.

System and method for machine learning-driven object detection

Some embodiments relate to a system for automated gaming recognition, the system comprising: at least one image sensor configured to capture image frames of a field of view including a table game; at least one depth sensor configured to capture depth of field images of the field of view; and a computing device configured to receive the image frames and the depth of field images, and configured to process the received image frames and depth of field images in order to produce an automated recognition of at least one gaming state appearing in the field of view. Embodiments also relate to methods and computer-readable media for automated gaming recognition. Further embodiments relate to methods and systems for monitoring game play and/or gaming events on a gaming table.

Embodiments relate to systems and methods for gaining monitoring. In particular, embodiments relate to systems and methods for gaining monitoring based on machine learning processes configured to analyse captured images to identify or detect game objects and game events to monitor games.

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Abbotsford, Australia

Subhash Challa