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    • 3. 发明申请
    • Tracking Moving Objects Using a Camera Network
    • 使用相机网络跟踪移动对象
    • US20120169882A1
    • 2012-07-05
    • US12982138
    • 2010-12-30
    • Greg MillarFarzin AghdasiLei Wang
    • Greg MillarFarzin AghdasiLei Wang
    • H04N7/18H04N5/225
    • H04N7/181G08B13/19608
    • Techniques are described for tracking moving objects using a plurality of security cameras. Multiple cameras may capture frames that contain images of a moving object. These images may be processed by the cameras to create metadata associated with the images of the objects. Frames of each camera's video feed and metadata may be transmitted to a host computer system. The host computer system may use the metadata received from each camera to determine whether the moving objects imaged by the cameras represent the same moving object. Based upon properties of the images of the objects described in the metadata received from each camera, the host computer system may select a preferable video feed containing images of the moving object for display to a user.
    • 描述了使用多个安全摄像机跟踪移动物体的技术。 多个相机可以捕获包含移动物体的图像的帧。 这些图像可以由相机处理以创建与对象的图像相关联的元数据。 每个摄像机的视频馈送和元数据的帧可以被发送到主机系统。 主计算机系统可以使用从每个摄像机接收到的元数据来确定由摄像机成像的移动物体是否表示相同的移动物体。 基于从每个摄像机接收的元数据中描述的对象的图像的属性,主计算机系统可以选择包含用于显示给用户的移动物体的图像的优选视频馈送。
    • 5. 发明申请
    • METHOD OF IMPROVING THE VIDEO IMAGES FROM A VIDEO CAMERA
    • 从视频摄像机改进视频图像的方法
    • US20100214425A1
    • 2010-08-26
    • US12527619
    • 2008-03-26
    • Chien-Min HuangFarzin Aghdasi
    • Chien-Min HuangFarzin Aghdasi
    • H04N5/225
    • H04N5/23248G06T5/003G06T2207/10016G06T2207/20201G06T2207/30232
    • A method of improving a video image by removing the effects of camera vibration comprising the steps of, obtaining a reference frame, receiving an incoming frame, determining the frame translation vector for the incoming frame, translating the incoming frame to generate a realigned frame, performing low pass filtering in the spatial domain on pixels in the realigned frame, performing low pass filtering in the spatial domain on pixels in the reference frame, determining the absolute difference between the filtered pixels in the reference frame and the filtered pixels in the realigned frame, performing low pass filtering in the temporal domain on the pixels in the realigned frame to generate the output frame if the absolute difference is less than a predetermined threshold, and providing the realigned frame as the output frame if the absolute difference is greater than the predetermined threshold.
    • 通过消除摄像机振动的影响来改善视频图像的方法包括以下步骤:获得参考帧,接收输入帧,确定输入帧的帧转换向量,翻译输入帧以产生重新排列的帧,执行 在重新排列的帧中的像素上的空间域中进行低通滤波,对参考帧中的像素执行空间域中的低通滤波,确定参考帧中的滤波像素与重新排列的帧中的滤波像素之间的绝对差, 在所述重新排列的帧中的所述像素上执行所述时域上的低通滤波以在所述绝对差小于预定阈值时产生所述输出帧,并且如果所述绝对差大于所述预定阈值,则将所述重新排列的帧提供为所述输出帧 。
    • 8. 发明授权
    • Clustering-based object classification
    • 基于聚类的对象分类
    • US08744125B2
    • 2014-06-03
    • US13338617
    • 2011-12-28
    • Hongwei ZhuFarzin AghdasiGreg Millar
    • Hongwei ZhuFarzin AghdasiGreg Millar
    • G06K9/00
    • G06K9/68
    • An example of a method for identifying objects in video content according to the disclosure includes receiving video content of a scene captured by a video camera, detecting an object in the video content, identifying a track that the object follows over a series of frames of the video content, extracting object features for the object from the video content, and classifying the object based on the object features. Classifying the object further comprises: determining a track-level classification for the object using spatially invariant object features, determining a global-clustering classification for the object using spatially variant features, and determining an object type for the object based on the track-level classification and the global-clustering classification for the object.
    • 根据本公开的用于识别视频内容中的对象的方法的示例包括:接收由摄像机捕获的场景的视频内容,检测视频内容中的对象,识别该对象在一系列帧上跟随的轨迹 视频内容,从视频内容提取对象的对象特征,以及基于对象特征对对象进行分类。 分类对象还包括:使用空间不变对象特征来确定对象的轨道级分类,使用空间变异特征确定对象的全局聚类分类,以及基于轨道级分类确定对象的对象类型 和对象的全局聚类分类。
    • 10. 发明申请
    • CONTEXT AWARE MOVING OBJECT DETECTION
    • 背景知识移动物体检测
    • US20130176430A1
    • 2013-07-11
    • US13345228
    • 2012-01-06
    • Hongwei ZhuFarzin AghdasiGreg MillarLei Wang
    • Hongwei ZhuFarzin AghdasiGreg MillarLei Wang
    • H04N7/18
    • G06T7/2053G06T7/254G06T2207/10016G06T2207/30196G06T2207/30232
    • An image capture system includes: an image capture unit configured to capture a first image frame comprising a set of pixels; and a processor coupled to the image capture unit and configured to: determine a normalized distance of a pixel characteristic between the first image frame and a second image frame for each pixel in the first image frame; compare the normalized distance for each pixel in the first image frame against a pixel sensitivity value for that pixel; determine that a particular pixel of the first image frame is a foreground or background pixel based on the normalized distance of the particular pixel relative to the pixel sensitivity value for the particular pixel; and adapt the pixel sensitivity value for each pixel over a range of allowable pixel sensitivity values.
    • 图像拍摄系统包括:图像拍摄单元,被配置为捕获包括一组像素的第一图像帧; 以及处理器,其耦合到所述图像捕获单元并且被配置为:确定所述第一图像帧中的每个像素的所述第一图像帧和第二图像帧之间的像素特性的归一化距离; 将第一图像帧中的每个像素的归一化距离与该像素的像素灵敏度值进行比较; 基于特定像素相对于特定像素的像素灵敏度值的归一化距离,确定第一图像帧的特定像素是前景或背景像素; 并且在允许的像素灵敏度值的范围内适应每个像素的像素灵敏度值。