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31. 发明申请

US20120030208A1 Facilitating People Search in Video Surveillance 有权
标题翻译：促进人们在视频监控中的搜索
公开(公告)号：US20120030208A1
公开(公告)日：2012-02-02
申请号：US12845116
申请日：2010-07-28
申请人： Lisa M. Brown , Rogerio S. Feris , Arun Hampapur , Daniel A. Vaquero
发明人： Lisa M. Brown , Rogerio S. Feris , Arun Hampapur , Daniel A. Vaquero
IPC分类号： G06F17/30
摘要： Techniques for facilitating a video surveillance search of a person are provided. The techniques include maintaining a database of one or more attributes of one or more people captured on one or more video cameras, indexing the one or more attributes in the database extracted from the one or more video cameras, and pruning one or more images captured from the one or more video cameras using the one or more attributes and one or more items of qualifying information to facilitate a video surveillance search of a person.
摘要翻译：提供了一种用于促进人的视频监视搜索的技术。这些技术包括维护在一个或多个摄像机上捕获的一个或多个人的一个或多个属性的数据库，索引从一个或多个摄像机提取的数据库中的一个或多个属性，以及修剪从所述一个或多个摄像机使用一个或多个属性和一个或多个限定条件信息来促进人的视频监视搜索。

32. 发明申请

US20120027248A1 Foreground Analysis Based on Tracking Information 失效
标题翻译：基于跟踪信息的前景分析
公开(公告)号：US20120027248A1
公开(公告)日：2012-02-02
申请号：US12844330
申请日：2010-07-27
申请人： Rogerio S. Feris , Arun Hampapur , Frederik C. Kjeldsen , Hao-Wei Liu
发明人： Rogerio S. Feris , Arun Hampapur , Frederik C. Kjeldsen , Hao-Wei Liu
IPC分类号： G06K9/00
CPC分类号： G06K9/46 , G06K9/00711 , G06K9/00744 , G06K9/00771 , G06K2009/4666 , G06T11/20 , H04N7/18
摘要： Techniques for performing foreground analysis are provided. The techniques include identifying a region of interest in a video scene, applying a background subtraction algorithm to the region of interest to detect a static foreground object in the region of interest, and determining whether the static foreground object is abandoned or removed, wherein determining whether the static foreground object is abandoned or removed comprises performing a foreground analysis based on edge energy and region growing, and pruning one or more false alarms using one or more track statistics.
摘要翻译：提供了执行前景分析的技术。这些技术包括识别视频场景中的感兴趣区域，将感兴趣的区域应用背景减法算法来检测感兴趣区域中的静态前景对象，以及确定是否放弃或去除静态前景对象，其中确定是否静态前景对象被放弃或移除包括基于边缘能量和区域增长执行前景分析，以及使用一个或多个轨道统计修剪一个或多个虚假报警。

33. 发明授权

US09008359B2 Detection of static object on thoroughfare crossings 有权
公开(公告)号：US09008359B2
公开(公告)日：2015-04-14
申请号：US13535461
申请日：2012-06-28
申请人： Rogerio S. Feris , Yun Zhai
发明人： Rogerio S. Feris , Yun Zhai
IPC分类号： G06K9/00 , G06T7/20
CPC分类号： G06K9/00771 , G06K9/00805 , G06T7/194 , G06T7/254 , G06T7/269 , G06T2207/10016 , G06T2207/30232 , G06T2207/30236 , G06T2207/30241
摘要： Foreground object image features are extracted from input video via application of a background subtraction mask, and optical flow image features from a region of the input video image data defined by the extracted foreground object image features. If estimated movement features indicate that the underlying object is in motion, a dominant moving direction of the underlying object is determined. If the dominant moving direction is parallel to an orientation of the second, crossed thoroughfare, an event alarm indicating that a static object is blocking travel on the crossing second thoroughfare is not generated. If the estimated movement features indicate that the underlying object is static, or that its determined dominant moving direction is not parallel to the second thoroughfare, an appearance of the foreground object region is determined and a static-ness timer run while the foreground object region comprises the extracted foreground object image features.

34. 发明申请

US20120027249A1 Multispectral Detection of Personal Attributes for Video Surveillance 失效
标题翻译：用于视频监控的个人属性的多光谱检测
公开(公告)号：US20120027249A1
公开(公告)日：2012-02-02
申请号：US12845121
申请日：2010-07-28
申请人： Lisa M. Brown , Rogerio S. Feris , Arun Hampapur , Daniel A. Vaquero
发明人： Lisa M. Brown , Rogerio S. Feris , Arun Hampapur , Daniel A. Vaquero
IPC分类号： G06K9/00
CPC分类号： G06K9/00624 , G06K9/00771 , G06K9/2018 , G06K9/4614 , G06K9/6256
摘要： Techniques for detecting an attribute in video surveillance include generating training sets of multispectral images, generating a group of multispectral box features comprising receiving input of a detector size of a width and height, a number of spectral bands in the multispectral images, and integer values representing a minimum and maximum width and height of multispectral box features, fixing a feature width and to height, generating feature building blocks with the fixed width and height, placing a feature building block at a same location for each spectral band level, and enumerating combinations of the feature building blocks through each spectral level until all sizes within the integer values have been covered, and wherein each combination determines a multispectral box feature, using the training sets to select multispectral box features to generate a multispectral attribute detector, and using the multispectral attribute detector to identify a location of an attribute in video surveillance.
摘要翻译：用于检测视频监控中的属性的技术包括生成多光谱图像的训练集，生成一组多光谱特征，包括接收宽度和高度的检测器大小的输入，多光谱图像中的光谱带的数量，以及表示多光谱盒特征的最小和最大宽度和高度，固定特征宽度和高度，生成具有固定宽度和高度的特征构建块，将特征构建块放置在每个光谱带级的相同位置，并列举特征构成块通过每个光谱级别直到整数值中的所有尺寸已经被覆盖，并且其中每个组合确定多光谱特征，使用训练集来选择多光谱特征以产生多光谱属性检测器，并且使用多光谱属性检测器，以识别vi中属性的位置 deo监视。

35. 发明申请

US20080232681A1 OBJECT DETECTION SYSTEM BASED ON A POOL OF ADAPTIVE FEATURES 失效
标题翻译：基于自适应特征的对象检测系统
公开(公告)号：US20080232681A1
公开(公告)日：2008-09-25
申请号：US11688372
申请日：2007-03-20
申请人： Rogerio S. Feris , Arun Hampapur , Ying-Li Tian
发明人： Rogerio S. Feris , Arun Hampapur , Ying-Li Tian
IPC分类号： G06K9/62
CPC分类号： G06K9/6228
摘要： A method, system and computer program product for detecting presence of an object in an image are disclosed. According to an embodiment, a method for detecting a presence of an object in an image comprises: receiving multiple training image samples; determining a set of adaptive features for each training image sample, the set of adaptive features matching the local structure of each training image sample; integrating the sets of adaptive features of the multiple training image samples to generate an adaptive feature pool; determining a general feature based on the adaptive feature pool; and examining the image using a classifier determined based on the general feature to detect the presence of the object.
摘要翻译：公开了一种用于检测图像中的对象的存在的方法，系统和计算机程序产品。根据实施例，用于检测图像中的对象的存在的方法包括：接收多个训练图像样本; 确定每个训练图像样本的一组自适应特征，与每个训练图像样本的局部结构匹配的一组自适应特征; 整合多个训练图像样本的自适应特征的集合以生成自适应特征池; 基于自适应特征池确定一般特征; 以及使用基于一般特征确定的分类器来检查图像以检测对象的存在。

36. 发明授权

US09070020B2 Determination of train presence and motion state in railway environments 有权
标题翻译：确定铁路环境中的列车存在和运动状态
公开(公告)号：US09070020B2
公开(公告)日：2015-06-30
申请号：US13590269
申请日：2012-08-21
申请人： Russell P. Bobbitt , Rogerio S. Feris , Yun Zhai
发明人： Russell P. Bobbitt , Rogerio S. Feris , Yun Zhai
IPC分类号： G06K9/00
CPC分类号： G06K9/00771 , G06K9/00718 , G06K9/00765 , G06K9/6212 , G06T7/11
摘要： Foreground feature data and motion feature data is determined for frames of video data acquired from a train track area region of interest. The frames are labeled as “train present” if the determined foreground feature data value meets a threshold value, else as “train absent”; and as “motion present” if the motion feature data meets a motion threshold, else as “static.” The labels are used to classify segments of the video data comprising groups of consecutive video frames, namely as within a “no train present” segment for groups with “train absent” and “static” labels; within a “train present and in transition” segment for groups “train present” and “motion present” labels; and within a “train present and stopped” segment for groups with “train present” and “static” labels. The presence or motion state of a train at a time of inquiry is thereby determined from the respective segment classification.
摘要翻译：确定从感兴趣的列车轨道区域获取的视频数据的帧的前景特征数据和运动特征数据。如果确定的前景特征数据值满足阈值，则帧被标记为“列车存在”，否则被标记为“列车存在”，否则被标记为“列车存在” 如果运动特征数据满足运动阈值，则作为“运动呈现”，否则为“静态”。标签用于对包括连续视频帧组的视频数据的段进行分类，即在“无列车存在”段内对于具有“火车不在”和“静态”标签的组; 在“火车现在”和“现场演出”标签的“火车现在和转型期”段内，在“火车现在”和“静态”标签的组别内的“火车现在和停止”部分。因此，从相应的段分类确定列车在询问时的存在或运动状态。

37. 发明授权

US08675917B2 Abandoned object recognition using pedestrian detection 有权
标题翻译：放弃对象识别使用行人检测
公开(公告)号：US08675917B2
公开(公告)日：2014-03-18
申请号：US13285354
申请日：2011-10-31
申请人： Lisa M. Brown , Rogerio S. Feris , Frederik C. Kjeldsen , Kristina Scherbaum
发明人： Lisa M. Brown , Rogerio S. Feris , Frederik C. Kjeldsen , Kristina Scherbaum
IPC分类号： G06K9/00 , H04N5/225
CPC分类号： G06K9/00369 , G06K9/626 , G06K9/6857
摘要： Methods and apparatus are provided for improved abandoned object recognition using pedestrian detection. An abandoned object is detected in one or more images by determining if one or more detected objects in a foreground of the images comprises a potential abandoned object; applying a trained pedestrian detector to the potential abandoned object to determine if the potential abandoned object comprises at least a portion of a pedestrian; and classifying the potential abandoned object as an abandoned object based on whether the potential abandoned object is not at least a portion of a pedestrian. The trained pedestrian detector is trained using positive training samples comprised of at least portions of human bodies in one or more poses and/or negative training samples comprised of at least portions of abandoned objects.
摘要翻译：提供了使用行人检测改进废弃物识别的方法和装置。通过确定图像的前景中的一个或多个检测到的对象是否包括潜在废弃对象，在一个或多个图像中检测到废弃物体; 将经过训练的行人检测器应用于潜在废弃物体以确定潜在废弃物体是否包括行人的至少一部分; 并且基于潜在废弃物体是否不是行人的至少一部分，将潜在废弃物体分类为废弃物体。训练有素的行人检测器使用由至少部分被遗弃物体组成的一个或多个姿势和/或负训练样本中的人体的至少部分组成的训练有素的训练样本进行训练。

38. 发明授权

US08532336B2 Multi-mode video event indexing 有权
公开(公告)号：US08532336B2
公开(公告)日：2013-09-10
申请号：US12857755
申请日：2010-08-17
申请人： Russell P. Bobbitt , Lisa M. Brown , Rogerio S. Feris , Arun Hampapur , Yun Zhai
发明人： Russell P. Bobbitt , Lisa M. Brown , Rogerio S. Feris , Arun Hampapur , Yun Zhai
IPC分类号： G06K9/00
CPC分类号： G06T7/254 , G06K9/00536 , G06K9/00771 , G06K9/4647 , G06K9/6212 , G06T7/20 , G06T7/74 , G06T7/97 , G06T2207/10016 , G06T2207/20224 , G06T2207/30232 , H04N7/18
摘要： Multi-mode video event indexing includes determining a quality of object distinctiveness with respect to images from a video stream input. A high-quality analytic mode is selected from multiple modes and applied to video input images via a hardware device to determine object activity within the video input images if the determined level of detected quality of object distinctiveness meets a threshold level of quality, else a low-quality analytic mode is selected and applied to the video input images via a hardware device to determine object activity within the video input images, wherein the low-quality analytic mode is different from the high-quality analytic mode.

39. 发明授权

US08515127B2 Multispectral detection of personal attributes for video surveillance 失效
标题翻译：用于视频监控的个人属性的多光谱检测
公开(公告)号：US08515127B2
公开(公告)日：2013-08-20
申请号：US12845121
申请日：2010-07-28
申请人： Lisa M. Brown , Rogerio S. Feris , Arun Hampapur , Daniel A. Vaquero
发明人： Lisa M. Brown , Rogerio S. Feris , Arun Hampapur , Daniel A. Vaquero
IPC分类号： G06K9/00
CPC分类号： G06K9/00624 , G06K9/00771 , G06K9/2018 , G06K9/4614 , G06K9/6256
摘要： Techniques for detecting an attribute in video surveillance include generating training sets of multispectral images, generating a group of multispectral box features comprising receiving input of a detector size of a width and height, a number of spectral bands in the multispectral images, and integer values representing a minimum and maximum width and height of multispectral box features, fixing a feature width and height, generating feature building blocks with the fixed width and height, placing a feature building block at a same location for each spectral band level, and enumerating combinations of the feature building blocks through each spectral level until all sizes within the integer values have been covered, and wherein each combination determines a multispectral box feature, using the training sets to select multispectral box features to generate a multispectral attribute detector, and using the multispectral attribute detector to identify a location of an attribute in video surveillance.
摘要翻译：用于检测视频监控中的属性的技术包括生成多光谱图像的训练集，生成一组多光谱特征，包括接收宽度和高度的检测器大小的输入，多光谱图像中的光谱带的数量，以及表示多光谱盒特征的最小和最大宽度和高度，固定特征宽度和高度，生成具有固定宽度和高度的特征构建块，将特征构建块放置在每个光谱带级的相同位置，并列举通过每个光谱级别的特征构建块，直到整数值中的所有大小被覆盖，并且其中每个组合确定多光谱特征，使用训练集选择多光谱特征以产生多光谱属性检测器，并使用多光谱属性检测器识别视频中属性的位置监视。

40. 发明申请

US20130108102A1 Abandoned Object Recognition Using Pedestrian Detection 有权
标题翻译：放弃对象识别使用行人检测
公开(公告)号：US20130108102A1
公开(公告)日：2013-05-02
申请号：US13285354
申请日：2011-10-31
申请人： Lisa M. Brown , Rogerio S. Feris , Frederik C. Kjeldsen , Kristina Scherbaum
发明人： Lisa M. Brown , Rogerio S. Feris , Frederik C. Kjeldsen , Kristina Scherbaum
IPC分类号： G06K9/62
CPC分类号： G06K9/00369 , G06K9/626 , G06K9/6857
摘要： Methods and apparatus are provided for improved abandoned object recognition using pedestrian detection. An abandoned object is detected in one or more images by determining if one or more detected objects in a foreground of the images comprises a potential abandoned object; applying a trained pedestrian detector to the potential abandoned object to determine if the potential abandoned object comprises at least a portion of a pedestrian; and classifying the potential abandoned object as an abandoned object based on whether the potential abandoned object is not at least a portion of a pedestrian. The trained pedestrian detector is trained using positive training samples comprised of at least portions of human bodies in one or more poses and/or negative training samples comprised of at least portions of abandoned objects.
摘要翻译：提供了使用行人检测改进废弃物识别的方法和装置。通过确定图像的前景中的一个或多个检测到的对象是否包括潜在废弃对象，在一个或多个图像中检测到废弃物体; 将经过训练的行人检测器应用于潜在废弃物体以确定潜在废弃物体是否包括行人的至少一部分; 并且基于潜在废弃物体是否不是行人的至少一部分，将潜在废弃物体分类为废弃物体。训练有素的行人检测器使用由至少部分被遗弃物体组成的一个或多个姿势和/或负训练样本中的人体的至少部分组成的训练有素的训练样本进行训练。

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