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1.发明授权Method for combining boosted classifiers for efficient multi-class object detection 有权用于组合升级分类器以实现高效多类对象检测的方法公开(公告)号：US07769228B2
公开(公告)日：2010-08-03
申请号：US11111640
申请日：2005-04-21
申请人： Claus Bahlmann , Ying Zhu , Dorin Comaniciu , Thorsten Köhler , Martin Pellkofer
发明人： Claus Bahlmann , Ying Zhu , Dorin Comaniciu , Thorsten Köhler , Martin Pellkofer
IPC分类号： G06K9/62
CPC分类号： G06K9/6256 , G06K9/6228
摘要： A method for training a system for detecting multi-class objects in an image or a video sequence is described. A common ensemble of weak classifiers for a set of object classes is identified. For each object class, a separate weighting scheme is adapted for the ensemble of weak classifiers. A method for detecting objects of multiple classes in an image or a video sequence is also disclosed. Each class is assigned a detector that is implemented by a weighted combination of weak classifiers such that all of the detectors are based on a common ensemble of weak classifiers. Then weights are individually set for each class.
摘要翻译： 描述了一种用于训练用于检测图像或视频序列中的多类对象的系统的方法。 识别一组对象类的弱分类器的常见集合。 对于每个对象类，单独的加权方案适用于弱分类器的集合。 还公开了一种用于检测图像或视频序列中的多个类别的对象的方法。 每个类被分配一个由弱分类器的加权组合实现的检测器，使得所有检测器都基于弱分类器的共同集合。 然后，每个课程都可以单独设置权重。
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2.发明申请Method for combining boosted classifiers for efficient multi-class object detection 有权用于组合升级分类器以实现高效多类对象检测的方法公开(公告)号：US20050249401A1
公开(公告)日：2005-11-10
申请号：US11111640
申请日：2005-04-21
申请人： Claus Bahlmann , Ying Zhu , Dorin Comaniciu , Thorsten Kohler , Martin Pellkofer
发明人： Claus Bahlmann , Ying Zhu , Dorin Comaniciu , Thorsten Kohler , Martin Pellkofer
IPC分类号： G06K9/62
CPC分类号： G06K9/6256 , G06K9/6228
摘要： A method for training a system for detecting multi-class objects in an image or a video sequence is described. A common ensemble of weak classifiers for a set of object classes is identified. For each object class, a separate weighting scheme is adapted for the ensemble of weak classifiers. A method for detecting objects of multiple classes in an image or a video sequence is also disclosed. Each class is assigned a detector that is implemented by a weighted combination of weak classifiers such that all of the detectors are based on a common ensemble of weak classifiers. Then weights are individually set for each class.
摘要翻译： 描述了一种用于训练用于检测图像或视频序列中的多类对象的系统的方法。 识别一组对象类的弱分类器的常见集合。 对于每个对象类，单独的加权方案适用于弱分类器的集合。 还公开了一种用于检测图像或视频序列中的多个类别的对象的方法。 每个类被分配一个由弱分类器的加权组合实现的检测器，使得所有检测器都基于弱分类器的共同集合。 然后，每个课程都可以单独设置权重。
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公开(公告)号：US07764808B2
公开(公告)日：2010-07-27
申请号：US10805946
申请日：2004-03-22
申请人： Ying Zhu , Dorin Comaniciu , Martin Pellkofer , Thorsten Köhler
发明人： Ying Zhu , Dorin Comaniciu , Martin Pellkofer , Thorsten Köhler
IPC分类号： G06K9/00
CPC分类号： G06K9/3241 , G06T7/20
摘要： A system and method for detecting and tracking an object is disclosed. A camera captures a video sequence comprised of a plurality of image frames. A processor receives the video sequence and analyzes each image frame to determine if an object is detected. The processor applies one or more classifiers to an object in each image frame and computes a confidence score based on the application of the one or more classifiers to the object. A database stores the one or more classifiers and vehicle training samples. A display displays the video sequence.
摘要翻译： 公开了一种用于检测和跟踪对象的系统和方法。 相机拍摄由多个图像帧组成的视频序列。 处理器接收视频序列并分析每个图像帧以确定是否检测到对象。 处理器将一个或多个分类器应用于每个图像帧中的对象，并基于对该对象的一个或多个分类器的应用来计算置信度分数。 数据库存储一个或多个分类器和车辆训练样本。 显示器显示视频序列。
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4.发明授权System and method for detecting a passing vehicle from dynamic background using robust information fusion 有权使用鲁棒信息融合从动态背景检测过往车辆的系统和方法公开(公告)号：US07248718B2
公开(公告)日：2007-07-24
申请号：US11054996
申请日：2005-02-10
申请人： Dorin Comaniciu , Ying Zhu , Martin Pellkofer , Thorsten Köhler
发明人： Dorin Comaniciu , Ying Zhu , Martin Pellkofer , Thorsten Köhler
IPC分类号： G06K9/80
CPC分类号： G06K9/00805 , G06T7/254
摘要： A system and method for detecting a passing vehicle is disclosed. A video sequence comprising a plurality of image frames is received. Image intensity is measured and image motion is estimated in each image frame. A hypothesis model describing background dynamics is formulated. The measured image intensity and motion estimation is used to determine if the background dynamics has been violated in a given image frame. If the background dynamics has been violated, motion coherency is used to determine whether the violation of the background dynamics is caused by a passing vehicle.
摘要翻译： 公开了一种用于检测过往车辆的系统和方法。 接收包括多个图像帧的视频序列。 测量图像强度，并在每个图像帧中估计图像运动。 制定描述背景动力学的假设模型。 测量的图像强度和运动估计用于确定在给定图像帧中是否违反了背景动力学。 如果背景动力学被违反，则使用运动一致性来确定背景动力学的违反是否由过去的车辆引起。
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公开(公告)号：US20060177099A1
公开(公告)日：2006-08-10
申请号：US11311500
申请日：2005-12-19
申请人： Ying Zhu , Dorin Comaniciu , Martin Pellkofer , Thorsten Köhler
发明人： Ying Zhu , Dorin Comaniciu , Martin Pellkofer , Thorsten Köhler
CPC分类号： G06K9/3241 , G06K9/00335 , G06K9/00664 , G06K2209/23
摘要： The present invention is directed to a system and method for on-road vehicle detection. A video sequence is received that is comprised of a plurality of image frames. A potential vehicle appearance is identified in an image frame. Known vehicle appearance information and scene geometry information are used to formulate initial hypotheses about vehicle appearance. The potential vehicle appearance is tracked over multiple successive image frames. Potential motion trajectories for the potential vehicle appearance are identified over the multiple image frames. Knowledge fusion of appearance, scene geometry and motion information models are applied to each image frame containing the trajectories. A confidence score is calculated for each trajectory. A trajectory with a high confidence score is determined to represent a vehicle appearance.
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6.发明授权System and method for on-road detection of a vehicle using knowledge fusion 有权使用知识融合对车辆进行路面检测的系统和方法公开(公告)号：US07639841B2
公开(公告)日：2009-12-29
申请号：US11311500
申请日：2005-12-19
申请人： Ying Zhu , Dorin Comaniciu , Martin Pellkofer , Thorsten Köhler
发明人： Ying Zhu , Dorin Comaniciu , Martin Pellkofer , Thorsten Köhler
CPC分类号： G06K9/3241 , G06K9/00335 , G06K9/00664 , G06K2209/23
摘要： The present invention is directed to a system and method for on-road vehicle detection. A video sequence is received that is comprised of a plurality of image frames. A potential vehicle appearance is identified in an image frame. Known vehicle appearance information and scene geometry information are used to formulate initial hypotheses about vehicle appearance. The potential vehicle appearance is tracked over multiple successive image frames. Potential motion trajectories for the potential vehicle appearance are identified over the multiple image frames. Knowledge fusion of appearance, scene geometry and motion information models are applied to each image frame containing the trajectories. A confidence score is calculated for each trajectory. A trajectory with a high confidence score is determined to represent a vehicle appearance.
摘要翻译： 本发明涉及一种用于道路车辆检测的系统和方法。 接收由多个图像帧组成的视频序列。 在图像帧中识别潜在的车辆外观。 已知的车辆外观信息和场景几何信息用于制定关于车辆外观的初始假设。 在多个连续的图像帧上跟踪潜在的车辆外观。 在多个图像帧上识别潜在车辆外观的潜在运动轨迹。 外观，场景几何和运动信息模型的知识融合应用于包含轨迹的每个图像帧。 计算每个轨迹的置信度。 确定具有高置信度得分的轨迹以表示车辆外观。
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公开(公告)号：US07466841B2
公开(公告)日：2008-12-16
申请号：US11109106
申请日：2005-04-19
IPC分类号： G06K9/00
CPC分类号： G06K9/00818 , G06K9/4633 , G06K9/4652
摘要： A method for detecting and recognizing at least one traffic sign is disclosed. A video sequence having a plurality of image frames is received. One or more filters are used to measure features in at least one image frame indicative of an object of interest. The measured features are combined and aggregated into a score indicating possible presence of an object. The scores are fused over multiple image frames for a robust detection. If a score indicates possible presence of an object in an area of the image frame, the area is aligned with a model. A determination is then made as to whether the area indicates a traffic sign. If the area indicates a traffic sign, the area is classified into a particular type of traffic sign. The present invention is also directed to training a system to detect and recognize traffic signs.
摘要翻译： 公开了一种用于检测和识别至少一个交通标志的方法。 接收具有多个图像帧的视频序列。 使用一个或多个过滤器来测量指示感兴趣对象的至少一个图像帧中的特征。 测量的特征被组合并聚合成表示对象可能存在的分数。 分数融合在多个图像帧上以进行鲁棒检测。 如果分数表示在图像帧的区域中可能存在对象，则该区域与模型对齐。 然后确定该区域是否指示交通标志。 如果该区域指示交通标志，该区域被分类为特定类型的交通标志。 本发明还涉及训练用于检测和识别交通标志的系统。
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8.发明申请System and method for detecting a passing vehicle from dynamic background using robust information fusion 有权使用鲁棒信息融合从动态背景检测过往车辆的系统和方法公开(公告)号：US20050196020A1
公开(公告)日：2005-09-08
申请号：US11054996
申请日：2005-02-10
申请人： Dorin Comaniciu , Ying Zhu , Martin Pellkofer , Thorsten Kohler
发明人： Dorin Comaniciu , Ying Zhu , Martin Pellkofer , Thorsten Kohler
CPC分类号： G06K9/00805 , G06T7/254
摘要： A system and method for detecting a passing vehicle is disclosed. A video sequence comprising a plurality of image frames is received. Image intensity is measured and image motion is estimated in each image frame. A hypothesis model describing background dynamics is formulated. The measured image intensity and motion estimation is used to determine if the background dynamics has been violated in a given image frame. If the background dynamics has been violated, motion coherency is used to determine whether the violation of the background dynamics is caused by a passing vehicle.
摘要翻译： 公开了一种用于检测过往车辆的系统和方法。 接收包括多个图像帧的视频序列。 测量图像强度，并在每个图像帧中估计图像运动。 制定描述背景动力学的假设模型。 测量的图像强度和运动估计用于确定在给定图像帧中是否违反了背景动力学。 如果背景动力学被违反，则使用运动一致性来确定背景动力学的违反是否由过去的车辆引起。
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公开(公告)号：US20060034484A1
公开(公告)日：2006-02-16
申请号：US11109106
申请日：2005-04-19
IPC分类号： G06K9/00
CPC分类号： G06K9/00818 , G06K9/4633 , G06K9/4652
摘要： A method for detecting and recognizing at least one traffic sign is disclosed. A video sequence having a plurality of image frames is received. One or more filters are used to measure features in at least one image frame indicative of an object of interest. The measured features are combined and aggregated into a score indicating possible presence of an object. The scores are fused over multiple image frames for a robust detection. If a score indicates possible presence of an object in an area of the image frame, the area is aligned with a model. A determination is then made as to whether the area indicates a traffic sign. If the area indicates a traffic sign, the area is classified into a particular type of traffic sign. The present invention is also directed to training a system to detect and recognize traffic signs.
摘要翻译： 公开了一种用于检测和识别至少一个交通标志的方法。 接收具有多个图像帧的视频序列。 使用一个或多个过滤器来测量指示感兴趣对象的至少一个图像帧中的特征。 测量的特征被组合并聚合成表示对象可能存在的分数。 分数融合在多个图像帧上以进行鲁棒检测。 如果分数表示在图像帧的区域中可能存在对象，则该区域与模型对齐。 然后确定该区域是否指示交通标志。 如果该区域指示交通标志，该区域被分类为特定类型的交通标志。 本发明还涉及训练用于检测和识别交通标志的系统。
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公开(公告)号：US07620208B2
公开(公告)日：2009-11-17
申请号：US11313599
申请日：2005-12-21
CPC分类号： G06K9/4609 , G06K2209/23
摘要： A method of detecting a feature of a vehicle in an image of a vehicle includes providing a digitized image of a vehicle, providing a first filter mask over a first subdomain of the image, where the filter mask is placed to detect a feature in the image, calculating a function of a gradient of the image inside the first masked subdomain, and detecting the presence or absence of a vehicle feature within the first masked subdomain based on the value of the gradient function.
摘要翻译： 一种在车辆图像中检测车辆的特征的方法包括提供车辆的数字化图像，在图像的第一子域上提供第一滤波器掩模，其中放置滤波器掩码以检测图像中的特征 计算第一掩蔽子域内的图像的梯度的函数，以及基于梯度函数的值来检测第一掩蔽子域内的车辆特征的存在或不存在。
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