Multi-level duty cycling
    41.
    发明授权
    Multi-level duty cycling 失效
    多层次的骑自行车

    公开(公告)号:US08473013B2

    公开(公告)日:2013-06-25

    申请号:US12118376

    申请日:2008-05-09

    IPC分类号: H04B1/38 H04B7/00 H04B1/16

    摘要: A duty cycle scheme for wireless communication employs three or more duty cycle levels. In some aspects, a wireless device may continually scan for signals in an active state associated with a first duty cycle, periodically scan for signals during a periodic state associated with a second duty cycle, and periodically scan for signals during a standby state associated with a third duty cycle. Here, the second duty cycle may be lower than the first duty cycle and the third duty cycle may be lower than the second duty cycle. In some aspects the timing of different states may be correlated. In some aspects each wireless device in a system may independently control its duty cycle states.

    摘要翻译: 无线通信的占空比方案采用三个或更多个占空比水平。 在一些方面,无线设备可以连续地扫描与第一占空比关联的活动状态的信号,在与第二占空比相关联的周期性状态期间周期性地扫描信号,并且在与第一占空比相关联的待机状态期间周期性地扫描信号 第三个工作周期。 这里,第二占空比可以低于第一占空比,并且第三占空比可以低于第二占空比。 在某些方面,不同状态的时序可能相关。 在一些方面,系统中的每个无线设备可以独立地控制其占空比状态。

    Media access control for ultra-wide band communication
    42.
    发明授权
    Media access control for ultra-wide band communication 有权
    用于超宽带通信的媒体访问控制

    公开(公告)号:US09124357B2

    公开(公告)日:2015-09-01

    申请号:US11620021

    申请日:2007-01-04

    摘要: Media access control is provided for an ultra-wide band medium. The media access control may employ a peer-to-peer network topology. The media access control may employ a reduced addressing scheme. Concurrent ultra-wide band channels may be established through the use of a pulse division multiple access channelization scheme. Multiple media access control states may be defined whereby each state may be associated with one or more of different channel parameter state information, different duty cycles, and different synchronization status.

    摘要翻译: 为超宽带介质提供媒体访问控制。 媒体访问控制可以采用对等网络拓扑。 媒体访问控制可以采用简化的寻址方案。 并行的超宽带信道可以通过使用脉冲多址信道化方案来建立。 可以定义多个媒体访问控制状态,其中每个状态可以与不同信道参数状态信息,不同占空比和不同同步状态中的一个或多个相关联。

    Descriptor storage and searches of k-dimensional trees
    45.
    发明授权
    Descriptor storage and searches of k-dimensional trees 失效
    描述符存储和搜索k维树

    公开(公告)号:US08706711B2

    公开(公告)日:2014-04-22

    申请号:US13340024

    申请日:2011-12-29

    IPC分类号: G06F17/30

    CPC分类号: G06K9/6282 G06K9/6228

    摘要: Various arrangements for using a k-dimensional tree for a search are presented. A plurality of descriptors may be stored. Each of the plurality of descriptors stored is linked with a first number of stored dimensions. The search may be performed using the k-dimensional tree for one or more query descriptors that at least approximately match one or more of the plurality of descriptors linked with the first number of stored dimensions. The k-dimensional tree may be built using the plurality of descriptors wherein each of the plurality of descriptors is linked with a second number of dimensions when the k-dimensional tree is built. The second number of dimensions may be a greater number of dimensions than the first number of stored dimensions.

    摘要翻译: 提出了使用k维树进行搜索的各种布置。 可以存储多个描述符。 所存储的多个描述符中的每一个与存储维度的第一数量相关联。 可以使用k维树进行搜索,所述查询描述符至少近似地匹配与第一数量的存储维度相链接的多个描述符中的一个或多个。 可以使用多个描述符构建k维树,其中当构建k维树时,多个描述符中的每个描述符与第二数量的维度相关联。 第二数量的尺寸可以是比第一数量的存储尺寸更大的尺寸数量。

    Improving performance of image recognition algorithms by pruning features, image scaling, and spatially constrained feature matching
    46.
    发明授权
    Improving performance of image recognition algorithms by pruning features, image scaling, and spatially constrained feature matching 有权
    通过修剪特征,图像缩放和空间约束的特征匹配来提高图像识别算法的性能

    公开(公告)号:US08705876B2

    公开(公告)日:2014-04-22

    申请号:US12959056

    申请日:2010-12-02

    IPC分类号: G06K9/62

    CPC分类号: G06K9/6211

    摘要: A method for feature matching in image recognition is provided. First, image scaling may be based on a feature distribution across scale spaces for an image to estimate image size/resolution, where peak(s) in the keypoint distribution at different scales is used to track a dominant image scale and roughly track object sizes. Second, instead of using all detected features in an image for feature matching, keypoints may be pruned based on cluster density and/or the scale level in which the keypoints are detected. Keypoints falling within high-density clusters may be preferred over features falling within lower density clusters for purposes of feature matching. Third, inlier-to-outlier keypoint ratios are increased by spatially constraining keypoints into clusters in order to reduce or avoid geometric consistency checking for the image.

    摘要翻译: 提供了图像识别中特征匹配的方法。 首先,图像缩放可以基于用于图像的尺度空间上的特征分布来估计图像尺寸/分辨率,其中使用不同尺度的关键点分布中的峰值来跟踪主要图像尺度并粗略跟踪对象尺寸。 其次,代替使用图像中的所有检测到的特征进行特征匹配,可以基于检测到关键点的聚类密度和/或比例级别来修剪关键点。 落入高密度群集中的关键点可能优于落入低密度群集中的特征,用于特征匹配。 第三,通过将关键点空间约束成簇,从而增加关键点比率,以减少或避免图像的几何一致性检查。

    Scale space normalization technique for improved feature detection in uniform and non-uniform illumination changes
    47.
    发明授权
    Scale space normalization technique for improved feature detection in uniform and non-uniform illumination changes 有权
    尺度空间归一化技术,用于改进均匀和不均匀照明变化中的特征检测

    公开(公告)号:US08582889B2

    公开(公告)日:2013-11-12

    申请号:US12986607

    申请日:2011-01-07

    IPC分类号: G06K9/00

    CPC分类号: G06K9/4671

    摘要: A normalization process is implemented at a difference of scale space to completely or substantially reduce the effect that illumination changes has on feature/keypoint detection in an image. An image may be processed by progressively blurring the image using a smoothening function to generate a smoothened scale space for the image. A difference of scale space may be generated by taking the difference between two different smoothened versions of the image. A normalized difference of scale space image may be generated by dividing the difference of scale space image by a third smoothened version of the image, where the third smoothened version of the image that is as smooth or smoother than the smoothest of the two different smoothened versions of the image. The normalized difference of scale space image may then be used to detect one or more features/keypoints for the image.

    摘要翻译: 在尺度空间的差异上实现归一化过程以完全或基本上减少照明变化对图像中的特征/关键点检测的影响。 可以通过使用平滑函数逐渐模糊图像来生成图像来生成图像,以生成平滑的图像尺度空间。 可以通过获取图像的两个不同平滑版本之间的差异来产生比例空间的差异。 尺度空间图像的归一化差异可以通过将尺度空间图像的差除以图像的第三平滑版本而生成,其中图像的第三平滑版本比两个不同平滑版本中最平滑的平滑或平滑 的图像。 尺度空间图像的归一化差异可以用于检测图像的一个或多个特征/关键点。

    VIRTUAL RULER
    48.
    发明申请
    VIRTUAL RULER 审中-公开
    虚拟规则

    公开(公告)号:US20130201210A1

    公开(公告)日:2013-08-08

    申请号:US13563330

    申请日:2012-07-31

    IPC分类号: G06T19/00

    CPC分类号: G06T19/006 G01B11/25

    摘要: In some embodiments, first information indicative of an image of a scene is accessed. One or more reference features are detected, the reference features being associated with a reference object in the image. A transformation between an image space and a real-world space is determined based on the first information. Second information indicative of input from a user is accessed, the second information identifying an image-space distance in the image space corresponding to a real-world distance of interest in the real-world space. The real-world distance of interest is then estimated based on the second information and the determined transformation.

    摘要翻译: 在一些实施例中,访问指示场景的图像的第一信息。 检测到一个或多个参考特征,参考特征与图像中的参考对象相关联。 基于第一信息确定图像空间与真实世界空间之间的变换。 访问指示来自用户的输入的第二信息,第二信息识别与真实世界空间中的真实世界距离相对应的图像空间中的图像空间距离。 然后基于第二信息和确定的变换来估计现实世界的兴趣距离。

    Descriptor storage and searches of k-dimensional trees
    50.
    发明申请
    Descriptor storage and searches of k-dimensional trees 失效
    描述符存储和搜索k维树

    公开(公告)号:US20120330967A1

    公开(公告)日:2012-12-27

    申请号:US13340024

    申请日:2011-12-29

    IPC分类号: G06F17/30

    CPC分类号: G06K9/6282 G06K9/6228

    摘要: Various arrangements for using a k-dimensional tree for a search are presented. A plurality of descriptors may be stored. Each of the plurality of descriptors stored is linked with a first number of stored dimensions. The search may be performed using the k-dimensional tree for one or more query descriptors that at least approximately match one or more of the plurality of descriptors linked with the first number of stored dimensions. The k-dimensional tree may be built using the plurality of descriptors wherein each of the plurality of descriptors is linked with a second number of dimensions when the k-dimensional tree is built. The second number of dimensions may be a greater number of dimensions than the first number of stored dimensions.

    摘要翻译: 提出了使用k维树进行搜索的各种布置。 可以存储多个描述符。 所存储的多个描述符中的每一个与存储维度的第一数量相关联。 可以使用k维树进行搜索,所述查询描述符至少近似地匹配与第一数量的存储维度相链接的多个描述符中的一个或多个。 可以使用多个描述符构建k维树,其中当构建k维树时,多个描述符中的每个描述符与第二数量的维度相关联。 第二数量的尺寸可以是比第一数量的存储尺寸更大的尺寸数量。