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    • 3. 发明授权
    • Realtime object tracking system
    • 实时对象追踪系统
    • US07684592B2
    • 2010-03-23
    • US12013717
    • 2008-01-14
    • George V. PaulGlenn J. BeachCharles J. CohenCharles J. Jacobus
    • George V. PaulGlenn J. BeachCharles J. CohenCharles J. Jacobus
    • G06K9/00
    • G06K9/00335A63F2300/1093A63F2300/6045A63F2300/69G06F3/017G06K9/00355G06T7/246
    • A real-time computer vision system tracks one or more objects moving in a scene using a target location technique which does not involve searching. The imaging hardware includes a color camera, frame grabber and processor. The software consists of the low-level image grabbing software and a tracking algorithm. The system tracks objects based on the color, motion and/or shape of the object in the image. A color matching function is used to compute three measures of the target's probable location based on the target color, shape and motion. The method then computes the most probable location of the target using a weighting technique. Once the system is running, a graphical user interface displays the live image from the color camera on the computer screen. The operator can then use the mouse to select a target for tracking. The system will then keep track of the moving target in the scene in real-time.
    • 实时计算机视觉系统使用不涉及搜索的目标定位技术跟踪在场景中移动的一个或多个对象。 成像硬件包括彩色摄像机,帧采集器和处理器。 该软件由低级图像抓取软件和跟踪算法组成。 该系统基于图像中对象的颜色,运动和/或形状来跟踪对象。 颜色匹配功能用于基于目标颜色,形状和运动计算目标可能位置的三个度量。 该方法然后使用加权技术计算目标的最可能的位置。 一旦系统运行,图形用户界面将在计算机屏幕上显示来自彩色摄像机的实时图像。 然后,操作员可以使用鼠标选择要跟踪的目标。 然后系统将实时跟踪场景中的移动目标。
    • 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
    • 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。
    • 10. 发明授权
    • Orientation invariant object identification using model-based image processing
    • 使用基于模型的图像处理的方向不变对象识别
    • US08150101B2
    • 2012-04-03
    • US11938484
    • 2007-11-12
    • Douglas HaanpaaCharles J. CohenGlenn J. BeachCharles J. Jacobus
    • Douglas HaanpaaCharles J. CohenGlenn J. BeachCharles J. Jacobus
    • G06K9/00
    • G06T15/20G06F3/048G06K9/0063G06K9/3241G06K9/6202G06T3/20G06T3/60G06T7/20G06T15/00G06T15/10G06T2207/10012G06T2207/30212G06T2207/30248
    • A system for performing object identification combines pose determination, EO/IR sensor data, and novel computer graphics rendering techniques. A first module extracts the orientation and distance of a target in a truth chip given that the target type is known. A second is a module identifies the vehicle within a truth chip given the known distance and elevation angle from camera to target. Image matching is based on synthetic image and truth chip image comparison, where the synthetic image is rotated and moved through a 3-Dimensional space. To limit the search space, it is assumed that the object is positioned on relatively flat ground and that the camera roll angle stays near zero. This leaves three dimensions of motion (distance, heading, and pitch angle) to define the space in which the synthetic target is moved. A graphical user interface (GUI) front end allows the user to manually adjust the orientation of the target within the synthetic images. The system also includes the generation of shadows and allows the user to manipulate the sun angle to approximate the lighting conditions of the test range in the provided video.
    • 用于执行对象识别的系统结合了姿态确定,EO / IR传感器数据和新颖的计算机图形渲染技术。 鉴于目标类型是已知的,第一模块提取目标在真芯片中的方向和距离。 第二个是模块识别真实芯片内的车辆,给定从相机到目标的已知距离和仰角。 图像匹配基于合成图像和真值芯片图像比较,其中合成图像被旋转并移动通过三维空间。 为了限制搜索空间,假设物体位于相对平坦的地面上,并且摄像机倾斜角保持接近零。 这将留下三维运动(距离,航向和俯仰角)来定义合成目标移动的空间。 图形用户界面(GUI)前端允许用户手动调整合成图像内目标的方位。 该系统还包括产生阴影并且允许用户操纵太阳角以近似所提供的视频中的测试范围的照明条件。