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GESTURE RECOGNITION APPARATUSES, METHODS AND SYSTEMS FOR HUMAN-MACHINE INTERACTION

机译:人机交互的手势识别装置,方法和系统

摘要

The Gesture Recognition Apparatuses, Methods And Systems For Human-machine Interaction ("GRA") discloses vision-based gesture recognition. GRA can be implemented in any application involving tracking, detection and/or recognition of gestures or motion in general. Disclosed methods and systems consider a gestural vocabulary of a predefined number of user specified static and/or dynamic hand gestures that are mapped with a database to convey messages. In one implementation, the disclosed systems and methods support gesture recognition by detecting and tracking body parts, such as arms, hands and fingers, and by performing spatio-temporal segmentation and recognition of the set of predefined gestures, based on data acquired by an RGBD sensor. In one implementation, a model of the hand is employed to detect hand and finger candidates. At a higher level, hand posture models are defined and serve as building blocks to recognize gestures based on the temporal evolution of the detected postures.
机译:用于人机交互的手势识别装置,方法和系统(“ GRA”)公开了基于视觉的手势识别。通常,GRA可以在涉及跟踪,检测和/或识别手势或动作的任何应用中实现。所公开的方法和系统考虑了预定义数量的用户指定的静态和/或动态手势的手势词汇,这些手势与数据库映射以传达消息。在一个实施方式中,所公开的系统和方法通过基于由RGBD获取的数据,检测和跟踪诸如手臂,手和手指的身体部位,并且通过执行时空分割和对预定义手势的集合的识别,来支持手势识别。传感器。在一个实现中,采用手的模型来检测手和手指候选。在较高级别上,手势姿势模型被定义并用作基于检测到的姿势的时间演变来识别手势的构造块。

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