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    • 4. 发明授权
    • Gesture-controlled interfaces for self-service machines and other applications
    • 用于自助服务机器和其他应用的手势控制接口
    • US06950534B2
    • 2005-09-27
    • US10759459
    • 2004-01-16
    • Charles J. CohenGlenn BeachBrook CavellGene FoulkCharles J. JacobusJay ObermarkGeorge Paul
    • Charles J. CohenGlenn BeachBrook CavellGene FoulkCharles J. JacobusJay ObermarkGeorge Paul
    • G06F3/00G06F3/01G06K9/00G06T7/20
    • G06K9/00355A63F2300/1093A63F2300/6045G06F3/017G06T7/246
    • A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines.
    • 公开了一种用于控制自助服务机器和其他设备的手势识别界面。 手势被定义为人类,动物或机器产生的运动和运动姿态。 跟踪特定身体特征,并解释静态和运动手势。 运动手势被定义为参数定界的振荡运动系列,被建模为参数线性参数动态系统,附加的几何约束允许使用少量的存储器和处理时间进行实时识别。 优选使用线性最小二乘法来确定表示每个姿态的参数。 特征位置测量结合使用手势参数种子的预测器仓组,并且系统确定哪个箱最适合观察到的运动。 识别静态姿势手势优选地通过将来自图像的其余部分的身体/物体定位,描述该对象并识别该描述来执行。 本公开详细描述了用于手势识别的方法,以及用于使用手势识别来控制设备(包括自助服务机器)的整体架构。
    • 6. 发明授权
    • Gesture-controlled interfaces for self-service machines and other applications
    • 用于自助服务机器和其他应用的手势控制接口
    • US07460690B2
    • 2008-12-02
    • US11226831
    • 2005-09-14
    • Charles J. CohenGlenn BeachBrook CavellGene FoulkCharles J. JacobusJay ObermarkGeorge Paul
    • Charles J. CohenGlenn BeachBrook CavellGene FoulkCharles J. JacobusJay ObermarkGeorge Paul
    • G06K9/00G06K9/36G06F3/033
    • G06K9/00355A63F2300/1093A63F2300/6045G06F3/017G06T7/246
    • A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines.
    • 公开了一种用于控制自助服务机器和其他设备的手势识别界面。 手势被定义为人类,动物或机器产生的运动和运动姿态。 跟踪特定身体特征,并解释静态和运动手势。 运动手势被定义为参数定界的振荡运动系列,被建模为参数线性参数动态系统,附加的几何约束允许使用少量的存储器和处理时间进行实时识别。 优选使用线性最小二乘法来确定表示每个姿态的参数。 特征位置测量结合使用手势参数种子的预测器仓组,并且系统确定哪个箱最适合观察到的运动。 识别静态姿势手势优选地通过将来自图像的其余部分的身体/物体定位,描述该对象并识别该描述来执行。 本公开详细描述了用于手势识别的方法,以及用于使用手势识别来控制设备(包括自助服务机器)的整体架构。
    • 7. 发明申请
    • Tracking and gesture recognition system particularly suited to vehicular control applications
    • 跟踪和姿态识别系统特别适用于车辆控制应用
    • US20070195997A1
    • 2007-08-23
    • US11440228
    • 2006-05-23
    • George PaulGlenn BeachCharles CohenCharles Jacobus
    • George PaulGlenn BeachCharles CohenCharles Jacobus
    • G06K9/00
    • G06K9/00355A63F2300/1093A63F2300/6045A63F2300/69G06F3/017G06K9/00335G06K9/4652G06K9/6212G06T7/246G06T7/251G06T2207/10016G06T2207/30196G06T2207/30268
    • A system and method tracks the movements of a driver or passenger in a vehicle (ground, water, air, or other) and controls devices in accordance with position, motion, and/or body or hand gestures or movements. According to one embodiment, an operator or passenger uses the invention to control comfort or entertainment features such the heater, air conditioner, lights, mirror positions or the radio/CD player using hand gestures. An alternative embodiment facilitates the automatic adjustment of car seating restraints based on head position. Yet another embodiment is used to determine when to fire an airbag (and at what velocity or orientation) based on the position of a person in a vehicle seat. The invention may also be used to control systems outside of the vehicle. The on-board sensor system would be used to track the driver or passenger, but when the algorithms produce a command for a desired response, that response (or just position and gesture information) could be transmitted via various methods (wireless, light, whatever) to other systems outside the vehicle to control devices located outside the vehicle. For example, this would allow a person to use gestures inside the car to interact with a kiosk located outside of the car.
    • 系统和方法跟踪车辆(地面,水,空气或其他)中的驾驶员或乘客的运动,并根据位置,运动和/或身体或手势或运动来控制装置。 根据一个实施例,操作者或乘客使用本发明来使用手势来控制诸如加热器,空调,灯,镜子位置或无线电/ CD播放器之类的舒适性或娱乐特征。 一个替代实施例有助于基于头部位置自动调节汽车座椅限制器。 另一个实施例用于基于车辆座椅中的人的位置来确定何时触发安全气囊(并以什么速度或取向)。 本发明还可以用于控制车辆外部的系统。 车载传感器系统将用于跟踪驾驶员或乘客,但是当算法产生所需响应的命令时,可以通过各种方法(无线,轻,无论什么)传送该响应(或仅位置和手势信息) )到车辆外部的其他系统以控制位于车辆外部的装置。 例如,这将允许人们使用车内的手势来与位于汽车外部的信息亭进行交互。
    • 10. 发明申请
    • GESTURE-CONTROLLED INTERFACES FOR SELF-SERVICE MACHINES AND OTHER APPLICATIONS
    • 用于自助服务机器和其他应用程序的控制接口
    • US20090074248A1
    • 2009-03-19
    • US12326540
    • 2008-12-02
    • Charles J. CohenGlenn BeachBrook CavellGene FoulkCharles J. JacobusJay ObermarkGeorge Paul
    • Charles J. CohenGlenn BeachBrook CavellGene FoulkCharles J. JacobusJay ObermarkGeorge Paul
    • G06K9/00
    • G06K9/00355A63F2300/1093A63F2300/6045G06F3/017G06T7/246
    • A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines.
    • 公开了一种用于控制自助服务机器和其他设备的手势识别界面。 手势被定义为人类,动物或机器产生的运动和运动姿态。 跟踪特定身体特征,并解释静态和运动手势。 运动手势被定义为参数定界的振荡运动系列,被建模为参数线性参数动态系统,附加的几何约束允许使用少量的存储器和处理时间进行实时识别。 优选使用线性最小二乘法来确定表示每个姿态的参数。 特征位置测量结合使用手势参数种子的预测器仓组,并且系统确定哪个箱最适合观察到的运动。 识别静态姿势手势优选地通过将来自图像的其余部分的身体/物体定位,描述该对象并识别该描述来执行。 本公开详细描述了用于手势识别的方法,以及用于使用手势识别来控制设备(包括自助服务机器)的整体架构。