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1. 发明申请

US20070055427A1 Vision-based occupant classification method and system for controlling airbag deployment in a vehicle restraint system 有权
标题翻译：基于视觉的乘员分类方法和系统，用于控制车辆约束系统中的安全气囊展开
公开(公告)号：US20070055427A1
公开(公告)日：2007-03-08
申请号：US11218671
申请日：2005-09-02
申请人： Qin Sun , Hongzhi Kong , David Eiche , Victor Nieto
发明人： Qin Sun , Hongzhi Kong , David Eiche , Victor Nieto
IPC分类号： E05F15/00
CPC分类号： G06K9/00362 , B60R21/01538 , G06K9/00832
摘要： A vehicle restraint system has a vision-based occupant classification system for control of airbag deployment during a crash scenario. The classification system utilizes two imaging sensors which together create a stream of paired images received and stored by an occupant classification controller. A computer program product of the controller utilizes the paired images to extract disparity/range features and stereo-vision differential edge density features. Moreover, the controller extracts wavelet features from one of the two paired images. All three features or maps are classified amongst preferably seven classifications by algorithms of the computer program product producing class confidence data fed to a sensor fusion engine of the controller for processing and output of an airbag control signal input into a restraint controller of the vehicle restraint system.
摘要翻译：车辆约束系统具有基于视觉的乘员分类系统，用于在碰撞场景期间控制气囊展开。分类系统利用两个成像传感器，它们共同创建由乘员分类控制器接收和存储的配对图像流。控制器的计算机程序产品利用配对图像来提取视差/范围特征和立体视差差边缘密度特征。此外，控制器从两个配对图像之一中提取小波特征。所有三个特征或地图通过计算机程序产品的算法被分类为优选的七个分类，所述计算机程序产品产生提供给控制器的传感器融合引擎的类别置信数据，用于处理和输出输入到车辆限制系统的约束控制器中的安全气囊控制信号。

2. 发明申请

US20070055428A1 Method of classifying vehicle occupants 有权
标题翻译：车辆乘员分类方法
公开(公告)号：US20070055428A1
公开(公告)日：2007-03-08
申请号：US11219233
申请日：2005-09-02
申请人： Hongzhi Kong , Qin Sun , David Eiche , Victor Nieto
发明人： Hongzhi Kong , Qin Sun , David Eiche , Victor Nieto
IPC分类号： B60R22/00
CPC分类号： B60R21/01538 , G06K9/00369
摘要： A method of classifying vehicle occupants utilizes a neural network engine having a state machine for determining if an occupant has changed preferably between an adult and adult, an adult and child, and a child and child from a pair of images. If no change has occurred, the method utilizes the prior occupant type and then decides if the occupant has changed in position. If no, the occupant is deemed static and the prior type is valid as a classification or output to preferably a vehicle restraint system. If the occupant has changed in position, a dynamic classification process is initiated by either an adult or a child dynamic classifier as dictated by the state machine. Valid dynamic classifier outputs or classifications can be sent to the restraint system and invalid dynamic classifier outputs are sent to a static classifier for update of the occupant type.
摘要翻译：对车辆乘员进行分类的方法利用具有状态机的神经网络引擎，用于确定乘客是否优选地在成人和成人，成人和儿童之间以及来自一对图像的儿童和孩子之间进行改变。如果没有发生变化，则该方法利用先前的乘员类型，然后判定乘客是否已经改变了位置。如果否，乘客被认为是静止的，并且先前类型作为优选车辆约束系统的分类或输出是有效的。如果乘员位置发生变化，动态分类过程由成员或儿童动态分类器根据状态机发出。有效的动态分类器输出或分类可以发送到约束系统，无效的动态分类器输出被发送到静态分类器以更新乘员类型。

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