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    • 4. 发明申请
    • Automotive wheel with a retaining sealing groove
    • 汽车轮与保持密封槽
    • US20050236081A1
    • 2005-10-27
    • US10832270
    • 2004-04-27
    • Olivier MarsalyJinjun WangLarry Rogers
    • Olivier MarsalyJinjun WangLarry Rogers
    • B60B25/00B60C7/24
    • B60B25/002B60B3/02B60B23/10B60B25/004B60B25/008B60B25/22B60B2900/5116
    • A multi-part automotive wheel comprises first and second wheel discs having first and second mating surfaces, respectively, where the first and second discs are to be joined to each other. An annular radial groove is disposed on one of the first and second surfaces for receiving an O-ring for sealing the first surface in respect of the second surface. The groove includes a substantially radial basewall and first and second sidewalls which extend from the basewall toward an intermediate section and from the section toward both edges of the groove, the edges defining a radial groove opening which is smaller than a distance between the sidewalls at the section such that an O-ring having a larger cross-sectional diameter larger than the opening will be retained within the groove prior to the discs being joined together. The basewall merges with the first and second sidewalls with rounded corners to reduce concentration of stress at the corners.
    • 多部分汽车轮包括分别具有第一和第二配对表面的第一和第二轮盘,其中第一和第二盘彼此接合。 环形径向槽设置在第一和第二表面中的一个上,用于接收用于相对于第二表面密封第一表面的O形环。 凹槽包括基本上径向的基座和第一和第二侧壁,所述第一和第二侧壁从所述基座向着中间部分延伸,并且从所述部分朝向所述凹槽的两个边缘延伸,所述边缘限定径向凹槽开口,所述径向凹槽开口小于所述凹槽的侧壁之间的距离 使得在盘连接在一起之前,具有比开口大的截面直径的O形环将保持在凹槽内。 底盘与第一和第二侧壁合并,具有圆角,以减少拐角处的应力集中。
    • 6. 发明申请
    • Substructure and Boundary Modeling for Continuous Action Recognition
    • 连续动作识别的子结构和边界建模
    • US20130132316A1
    • 2013-05-23
    • US13491108
    • 2012-06-07
    • Jinjun WangZhaowen WangJing Xiao
    • Jinjun WangZhaowen WangJing Xiao
    • G06N5/02
    • G06N99/005
    • Embodiments of the present invention include systems and methods for improved state space modeling (SSM) comprising two added layers to model the substructure transition dynamics and action duration distribution. In embodiments, the first layer represents a substructure transition model that encodes the sparse and global temporal transition probability. In embodiments, the second layer models the action boundary characteristics by injecting discriminative information into a logistic duration model such that transition boundaries between successive actions can be located more accurately; thus, the second layer exploits discriminative information to discover action boundaries adaptively.
    • 本发明的实施例包括用于改进状态空间建模(SSM)的系统和方法,所述状态空间建模(SSM)包括两个附加的层,以模拟子结构转变动力学和动作持续时间分布。 在实施例中,第一层表示编码稀疏和全局时间转移概率的子结构转换模型。 在实施例中,第二层通过将识别信息注入逻辑持续时间模型来建模动作边界特征,使得可以更准确地定位连续动作之间的转移边界; 因此,第二层利用辨别信息自动发现行动界限。
    • 7. 发明申请
    • Embedded Optical Flow Features
    • 嵌入式光流特性
    • US20120219213A1
    • 2012-08-30
    • US13405986
    • 2012-02-27
    • Jinjun WangJing Xiao
    • Jinjun WangJing Xiao
    • G06K9/48G06K9/62
    • G06K9/00765G06K9/00335G06K9/6297
    • Aspects of the present invention include systems and methods for generating an optical flow-based feature. In embodiments, to extract an optical flow feature, the optical flow at sparse interest points is obtained, and Locality-constrained Linear Coding (LLC) is applied to the sparse interest points to embed each flow into a higher-dimensional code. In embodiments, for an image frame, the multiple codes are combined together using a weighted pooling that is related to the distribution of the optical flows in the image frame. In embodiments, the feature may be used in training models to detect actions, in trained models for action detection, or both.
    • 本发明的方面包括用于产生基于光流的特征的系统和方法。 在实施例中,为了提取光流特征,获得稀疏兴趣点处的光流,并将局部约束线性编码(LLC)应用于稀疏兴趣点以将每个流嵌入更高维码中。 在实施例中,对于图像帧,使用与图像帧中的光流的分布相关的加权池来将多个代码组合在一起。 在实施例中,可以在训练模型中使用该特征以在用于动作检测的训练模型中或两者中检测动作。
    • 8. 发明授权
    • Embedded optical flow features
    • 嵌入式光流特征
    • US08774499B2
    • 2014-07-08
    • US13405986
    • 2012-02-27
    • Jinjun WangJing Xiao
    • Jinjun WangJing Xiao
    • G06K9/00
    • G06K9/00765G06K9/00335G06K9/6297
    • Aspects of the present invention include systems and methods for generating an optical flow-based feature. In embodiments, to extract an optical flow feature, the optical flow at sparse interest points is obtained, and Locality-constrained Linear Coding (LLC) is applied to the sparse interest points to embed each flow into a higher-dimensional code. In embodiments, for an image frame, the multiple codes are combined together using a weighted pooling that is related to the distribution of the optical flows in the image frame. In embodiments, the feature may be used in training models to detect actions, in trained models for action detection, or both.
    • 本发明的方面包括用于产生基于光流的特征的系统和方法。 在实施例中,为了提取光流特征,获得稀疏兴趣点处的光流,并将局部约束线性编码(LLC)应用于稀疏兴趣点以将每个流嵌入更高维码中。 在实施例中,对于图像帧,使用与图像帧中的光流的分布相关的加权池来将多个代码组合在一起。 在实施例中,可以在训练模型中使用该特征以在用于动作检测的训练模型中或两者中检测动作。