Real-Time Continuous Action Detection And Recognition Using Depth Images And Inertial Signals
2017 IEEE 26TH INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE)(2017)
摘要
This paper presents an approach to detect and recognize actions of interest in real-time from a continuous stream of data that are captured simultaneously from a Kinect depth camera and a wearable inertial sensor. Actions of interest are considered to appear continuously and in a random order among actions of non-interest. Skeleton depth images are first used to separate actions of interest from actions of non-interest based on pause and motion segments. Inertial signals from a wearable inertial sensor are then used to improve the recognition outcome. A dataset consisting of simultaneous depth and inertial data for the smart TV actions of interest occurring continuously and in a random order among actions of non-interest is studied and made publicly available. The results obtained indicate the effectiveness of the developed approach in coping with actions that are performed realistically in a continuous manner.
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关键词
Real-time continuous action detection, action recognition from continuous data streams, simultaenous utilization of depth images and inertial signals for action recognition
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