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    • 1. 发明授权
    • Sensor fusion architecture for vision-based occupant detection
    • 用于基于视觉的乘员检测的传感器融合架构
    • US06801662B1
    • 2004-10-05
    • US09685235
    • 2000-10-10
    • Yuri OwechkoNarayan SrinivasaSwarup S. MedasaniRiccardo Boscolo
    • Yuri OwechkoNarayan SrinivasaSwarup S. MedasaniRiccardo Boscolo
    • G06K962
    • B60R21/01538B60R21/01542G06K9/00201G06K9/00362G06K9/6293
    • A vision-based system for automatically detecting the type of object within a specified area, such as the type of occupant within a vehicle. Determination of the type of occupant can then be used to determine whether an airbag deployment system should be enabled or not. The system extracts different features from images captured by image sensors. These features are then processed by classification algorithms to produce occupant class confidences for various occupant types. The occupant class confidences are then fused and processed to determine the type of occupant. In a preferred embodiment, image features derived from image edges, motion, and range are used. Classification algorithms may be implemented by using trained C5 decision trees, trained Nonlinear Discriminant Analysis networks, Hausdorff template matching and trained Fuzzy Aggregate Networks. In an exemplary embodiment, class confidences are provided for a rear-facing infant seat, a front-facing infant seat, an adult out of position, and an adult in a normal or twisted position. Fusion of these class confidences derived from multiple image features increases the accuracy of the system and provides for correct determination of an airbag deployment decision.
    • 一种基于视觉的系统,用于自动检测指定区域内物体的类型,例如车辆内的乘客类型。 然后可以确定乘客的类型,以确定是否应启用安全气囊展开系统。 该系统从图像传感器捕获的图像中提取不同的特征。 然后通过分类算法对这些特征进行处理,以便为各种乘员类型产生乘员级别信心。 然后对乘员班级信心进行融合和处理,以确定乘客的类型。 在优选实施例中,使用从图像边缘,运动和范围导出的图像特征。 分类算法可以通过使用经过训练的C5决策树,经过训练的非线性判别分析网络,Hausdorff模板匹配和经过训练的模糊聚合网络来实现。 在一个示例性实施例中,提供了用于面向后方的婴儿座椅,前置婴儿座椅,成人不在位置以及处于正常或扭转位置的成年人的类别信号。 从多个图像特征导出的这些类别信息的融合增加了系统的准确性,并提供了安全气囊部署决定的正确确定。
    • 3. 发明授权
    • Application-specific object-based segmentation and recognition system
    • 特定于应用程序的基于对象的分割和识别系统
    • US07227893B1
    • 2007-06-05
    • US10646585
    • 2003-08-22
    • Narayan SrinivasaSwarup S. MedasaniYuri OwechkoDeepak Khosla
    • Narayan SrinivasaSwarup S. MedasaniYuri OwechkoDeepak Khosla
    • H04N7/18
    • G08B13/19606G06K9/00771G08B13/19602G08B13/19608G08B13/19613
    • A video detection and monitoring method and apparatus utilizes an application-specific object based segmentation and recognition system for locating and tracking an object of interest within a number of sequential frames of data collected by a video camera or similar device. One embodiment includes a background modeling and object segmentation module to isolate from a current frame at least one segment of the current frame containing a possible object of interest, and a classification module adapted to determine whether or not any segment of the output from the background modeling apparatus includes an object of interest and to characterize any such segment as an object segment. An object segment tracking apparatus is adapted to track the location within a current frame of any object segment and to determine a projected location of the object segment in a subsequent frame.
    • 视频检测和监测方法和装置利用基于特定目标的对象分割和识别系统来定位和跟踪由摄像机或类似设备收集的多个数据的连续数据帧内的感兴趣对象。 一个实施例包括背景建模和对象分割模块,以从当前帧与当前帧的至少一个分段包含可能的感兴趣对象隔离,并且分类模块适于确定来自背景建模的输出的任何分段 装置包括感兴趣的对象并且将任何这样的片段表征为对象片段。 对象段跟踪装置适于跟踪任何对象段的当前帧内的位置,并且确定对象段在随后帧中的投影位置。