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    • 1. 发明申请
    • Camera-based lane marker detection
    • 基于相机的车道标记检测
    • US20100014714A1
    • 2010-01-21
    • US12175631
    • 2008-07-18
    • Wende ZhangVarsha Sadekar
    • Wende ZhangVarsha Sadekar
    • G06K9/78G06K9/00G05D1/02G06F17/00G06K9/46
    • G06K9/00798
    • A method is provided for detecting road lane markers in a vehicle road using an imaging device. Road input data is captured using the imaging device. Lighting normalization is applied to the road input data. The method detects the road lane markers in a few main orientations in the normalized input data. In each main orientation, the normalized input data is convolved with an oriented edge detection filter for generating an oriented edge-based filter response. The normalized input data is convolved with an oriented line detection filter for generating an oriented line-based filter response. Candidate lane markers are selected in response to the edge-based filter response and line-based filter response in each main orientation. A transformation technique is applied to the candidate lane markers for identifying the lane markings in each main orientation.
    • 提供一种用于使用成像装置来检测车辆道路中的道路车道标记的方法。 使用成像设备捕获道路输入数据。 照明归一化应用于道路输入数据。 该方法在标准化输入数据中的几个主要方向上检测道路车道标记。 在每个主要取向中,归一化输入数据与用于产生基于边缘的基于滤波器响应的定向边缘检测滤波器进行卷积。 归一化输入数据与用于生成基于定向的线路滤波器响应的定向线路检测滤波器进行卷积。 响应于每个主要方向上的基于边缘的滤波器响应和基于线路的滤波器响应来选择候选车道标记。 将候选车道标记应用于转换技术,用于识别每个主要取向中的车道标记。
    • 2. 发明授权
    • Visual guidance for vehicle navigation system
    • 车辆导航系统视觉指导
    • US09459113B2
    • 2016-10-04
    • US12276050
    • 2008-11-21
    • Wende ZhangVarsha Sadekar
    • Wende ZhangVarsha Sadekar
    • G01C21/36
    • G01C21/36G01C21/3647
    • A system and method that provide a video-based vehicle navigation system. The system positions an arrow on the video display that shows the specific turning direction for the vehicle for route guidance purposes. To determine the proper position of the guidance arrow, the process determines a distance from the current vehicle position to the location where the vehicle needs to turn using any suitable information, such as GPS position, range measurements and map information. The process then positions the guidance arrow on the ground at the turning location in world coordinates, and projects the guidance arrow onto the image. The camera can be calibrated to the ground using various techniques, such as an online automatic calibration process that uses detected objects in the scene around the vehicle.
    • 一种提供基于视频的车载导航系统的系统和方法。 系统在视频显示器上放置一个箭头,显示车辆的特定转向方向,用于路线引导目的。 为了确定导向箭头的正确位置,该过程使用诸如GPS位置,距离测量和地图信息之类的任何合适的信息确定从当前车辆位置到车辆需要转动的位置的距离。 然后,该过程将引导箭头定位在世界坐标中的转动位置的地面上,并将引导箭头投影到图像上。 摄像机可以使用各种技术进行校准,例如使用车辆周围场景中检测到的物体的在线自动校准过程。
    • 3. 发明授权
    • Apparatus and method for camera-bases lane marker detection
    • 相机底座车道标记检测装置及方法
    • US08204277B2
    • 2012-06-19
    • US12175631
    • 2008-07-18
    • Wende ZhangVarsha Sadekar
    • Wende ZhangVarsha Sadekar
    • G06K9/00
    • G06K9/00798
    • A method is provided for detecting road lane markers in a vehicle road using an imaging device. Road input data is captured using the imaging device. Lighting normalization is applied to the road input data. The method detects the road lane markers in a few main orientations in the normalized input data. In each main orientation, the normalized input data is convolved with an oriented edge detection filter for generating an oriented edge-based filter response. The normalized input data is convolved with an oriented line detection filter for generating an oriented line-based filter response. Candidate lane markers are selected in response to the edge-based filter response and line-based filter response in each main orientation. A transformation technique is applied to the candidate lane markers for identifying the lane markings in each main orientation.
    • 提供一种用于使用成像装置来检测车辆道路中的道路车道标记的方法。 使用成像设备捕获道路输入数据。 照明归一化应用于道路输入数据。 该方法在标准化输入数据中的几个主要方向上检测道路车道标记。 在每个主要取向中,归一化输入数据与用于产生基于边缘的基于滤波器响应的定向边缘检测滤波器进行卷积。 归一化输入数据与用于生成基于定向的线路滤波器响应的定向线路检测滤波器进行卷积。 响应于每个主要方向上的基于边缘的滤波器响应和基于线路的滤波器响应来选择候选车道标记。 将候选车道标记应用于转换技术,用于识别每个主要取向中的车道标记。
    • 4. 发明授权
    • Road-lane marker detection using light-based sensing technology
    • 使用基于光的感测技术的道路标记检测
    • US08194927B2
    • 2012-06-05
    • US12175622
    • 2008-07-18
    • Wende ZhangVarsha SadekarChristopher Paul Urmson
    • Wende ZhangVarsha SadekarChristopher Paul Urmson
    • G06K9/00
    • G06K9/00798
    • A method is provided for detecting road lane markers using a light-based sensing device. Reflectivity data is captured using the light-based sensing device. A light intensity signal is generated based on the captured reflectivity data. The light intensity signal is convolved with a differential filter for generating a filter response that identifies a candidate lane marker region and ground segment regions juxtaposed on each side of the candidate lane marker region. A weighted standard deviation of the data points within the identified candidate lane marker region and weighted standard deviation of the data points within the ground segment regions are calculated. An objective value is determined as a function of the respective weighted standard deviations. The objective value is compared to a respective threshold for determining whether the identified candidate lane marker region is a lane marker.
    • 提供了一种使用基于光的感测装置来检测道路标记的方法。 使用基于光的感测装置捕获反射率数据。 基于捕获的反射率数据生成光强度信号。 光强度信号与差分滤波器卷积,用于产生识别在候选车道标记区域的每一侧上并列的候选车道标记区域和地面段区域的过滤器响应。 计算所识别的候选车道标记区域内的数据点的加权标准偏差和地面段区域内的数据点的加权标准偏差。 作为各加权标准偏差的函数确定客观值。 将目标值与用于确定所识别的候选车道标记区域是否是车道标记的相应阈值进行比较。
    • 5. 发明申请
    • Road-lane marker detection
    • 道路标记检测
    • US20100014713A1
    • 2010-01-21
    • US12175622
    • 2008-07-18
    • Wende ZhangVarsha SadekarChristopher Paul Urmson
    • Wende ZhangVarsha SadekarChristopher Paul Urmson
    • G06K9/00
    • G06K9/00798
    • A method is provided for detecting road lane markers using a light-based sensing device. Reflectivity data is captured using the light-based sensing device. A light intensity signal is generated based on the captured reflectivity data. The light intensity signal is convolved with a differential filter for generating a filter response that identifies a candidate lane marker region and ground segment regions juxtaposed on each side of the candidate lane marker region. A weighted standard deviation of the data points within the identified candidate lane marker region and weighted standard deviation of the data points within the ground segment regions are calculated. An objective value is determined as a function of the respective weighted standard deviations. The objective value is compared to a respective threshold for determining whether the identified candidate lane marker region is a lane marker.
    • 提供了一种使用基于光的感测装置来检测道路标记的方法。 使用基于光的感测装置捕获反射率数据。 基于捕获的反射率数据生成光强度信号。 光强度信号与差分滤波器卷积,用于产生识别在候选车道标记区域的每一侧上并列的候选车道标记区域和地面段区域的过滤器响应。 计算所识别的候选车道标记区域内的数据点的加权标准偏差和地面段区域内的数据点的加权标准偏差。 作为各加权标准偏差的函数确定客观值。 将目标值与用于确定所识别的候选车道标记区域是否是车道标记的相应阈值进行比较。
    • 6. 发明申请
    • VISUAL GUIDANCE FOR VEHICLE NAVIGATION SYSTEM
    • 车辆导航系统视觉指导
    • US20100131197A1
    • 2010-05-27
    • US12276050
    • 2008-11-21
    • Wende ZhangVarsha Sadekar
    • Wende ZhangVarsha Sadekar
    • G01C21/36G06K9/00
    • G01C21/36G01C21/3647
    • A system and method that provide a video-based vehicle navigation system. The system positions an arrow on the video display that shows the specific turning direction for the vehicle for route guidance purposes. To determine the proper position of the guidance arrow, the process determines a distance from the current vehicle position to the location where the vehicle needs to turn using any suitable information, such as GPS position, range measurements and map information. The process then positions the guidance arrow on the ground at the turning location in world coordinates, and projects the guidance arrow onto the image. The camera can be calibrated to the ground using various techniques, such as an online automatic calibration process that uses detected objects in the scene around the vehicle.
    • 一种提供基于视频的车载导航系统的系统和方法。 系统在视频显示器上放置一个箭头,显示车辆的特定转向方向,用于路线引导目的。 为了确定导向箭头的正确位置,该过程使用诸如GPS位置,距离测量和地图信息之类的任何合适的信息确定从当前车辆位置到车辆需要转动的位置的距离。 然后,该过程将引导箭头定位在世界坐标中的转动位置的地面上,并将引导箭头投影到图像上。 摄像机可以使用各种技术进行校准,例如使用车辆周围场景中检测到的物体的在线自动校准过程。
    • 7. 发明授权
    • Road-edge detection
    • 路边检测
    • US08099213B2
    • 2012-01-17
    • US12175634
    • 2008-07-18
    • Wende ZhangVarsha Sadekar
    • Wende ZhangVarsha Sadekar
    • G06K9/00G06K9/78E01F9/06
    • G01S7/4802G01S17/89G01S17/936G06T7/73G06T2207/10028G06T2207/30256
    • A method is provided for detecting road-side edges in a road segment using a light-based sensing system. Input range data is captured using the light-based sensing system. An elevation-based road segment is generated based on the captured input range data. The elevation-based road segment is processed by filtering techniques to identify the road segment candidate region and by pattern recognition techniques to determine whether the candidate region is a road segment. The input range data is also projected onto the ground plane for further validation. The line representation of the projected points are identified. The line representation of the candidate regions is compared to a simple road/road-edge model in the top-down view to determine whether the candidate region is a road segment with its edges. The proposed method provides fast processing speeds and reliable detection performance for both road and road-side edges simultaneously in the captured range data.
    • 提供一种使用基于光的感测系统来检测道路段中的路侧边缘的方法。 使用基于光的感测系统捕获输入范围数据。 基于捕获的输入范围数据生成基于海拔的路段。 基于高程的道路段通过过滤技术来处理以识别道路段候选区域,并通过模式识别技术来确定候选区域是否是道路段。 输入范围数据也投射到地平面上以进一步验证。 确定投影点的线表示。 将候选区域的线表示与自上而下的简单道路/道路边缘模型进行比较,以确定候选区域是否是具有边缘的路段。 所提出的方法在捕获的范围数据中同时为道路和路侧边缘提供快速的处理速度和可靠的检测性能。
    • 8. 发明申请
    • Road-edge detection
    • 路边检测
    • US20100017060A1
    • 2010-01-21
    • US12175634
    • 2008-07-18
    • Wende ZhangVarsha Sadekar
    • Wende ZhangVarsha Sadekar
    • G05D1/00
    • G01S7/4802G01S17/89G01S17/936G06T7/73G06T2207/10028G06T2207/30256
    • A method is provided for detecting road-side edges in a road segment using a light-based sensing system. Input range data is captured using the light-based sensing system. An elevation-based road segment is generated based on the captured input range data. The elevation-based road segment is processed by filtering techniques to identify the road segment candidate region and by pattern recognition techniques to determine whether the candidate region is a road segment. The input range data is also projected onto the ground plane for further validation. The line representation of the projected points are identified. The line representation of the candidate regions is compared to a simple road/road-edge model in the top-down view to determine whether the candidate region is a road segment with its edges. The proposed method provides fast processing speeds and reliable detection performance for both road and road-side edges simultaneously in the captured range data.
    • 提供一种使用基于光的感测系统来检测道路段中的路侧边缘的方法。 使用基于光的感测系统捕获输入范围数据。 基于捕获的输入范围数据生成基于海拔的路段。 基于高程的道路段通过过滤技术来处理以识别道路段候选区域,并通过模式识别技术来确定候选区域是否是道路段。 输入范围数据也投射到地平面上以进一步验证。 确定投影点的线表示。 将候选区域的线表示与自上而下的简单道路/道路边缘模型进行比较,以确定候选区域是否是具有边缘的路段。 所提出的方法在捕获的范围数据中同时为道路和路侧边缘提供快速的处理速度和可靠的检测性能。
    • 10. 发明授权
    • Adaptation for clear path detection using reliable local model updating
    • 使用可靠的本地模型更新来适应清晰的路径检测
    • US08773535B2
    • 2014-07-08
    • US12963404
    • 2010-12-08
    • Wende Zhang
    • Wende Zhang
    • H04N5/14
    • G06K9/00791
    • A method and system for vehicular clear path detection using adaptive machine learning techniques including reliable local model updating. Digital camera images are segmented into patches, from which characteristic features are extracted representing attributes such as color and texture. The patch features are analyzed by a Support Vector Machine (SVM) or other machine learning classifier, which has been previously trained to recognize clear path image regions. The SVM classifier is adaptively updated using reliable local test samples, such as positive clear path samples which just passed by the vehicle. The resultant classifier, being continuously and adaptively updated with recent, reliable training samples, exhibits improved performance and accuracy in analyzing subsequent image regions or patches for the existence of a clear driving path.
    • 一种使用自适应机器学习技术进行车辆清除路径检测的方法和系统,包括可靠的本地模型更新。 数码相机图像被分割成补丁,从中提取表征诸如颜色和​​纹理等属性的特征。 补丁功能由支持向量机(SVM)或其他机器学习分类器进行分析,该分类器先前已经被训练以识别清除路径图像区域。 使用可靠的本地测试样本(例如刚刚通过车辆的正清晰路径样本)自适应地更新SVM分类器。 所得到的分类器,通过近来可靠的训练样本连续地和自适应地更新,在分析随后的图像区域或补片中存在清晰的驾驶路径时,表现出改善的性能和准确性。