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1. 发明授权

US08842163B2 Estimation of object properties in 3D world 有权
标题翻译： 3D世界中对象属性的估计
公开(公告)号：US08842163B2
公开(公告)日：2014-09-23
申请号：US13154843
申请日：2011-06-07
申请人： Ankur Datta , Rogerio S. Feris , Yun Zhai
发明人： Ankur Datta , Rogerio S. Feris , Yun Zhai
IPC分类号： H04N13/00 , G06T7/20
CPC分类号： G06T17/10 , G06K9/00711 , G06K9/00771 , G06K9/46 , G06K9/4604 , G06K9/52 , G06K2009/4666 , G06T3/20 , G06T3/40 , G06T7/20 , G06T7/251 , G06T7/62 , G06T7/75 , G06T15/205 , G06T19/20 , G06T2200/24 , G06T2207/10016 , G06T2207/30232 , G06T2207/30236 , G06T2219/2004 , G06T2219/2016 , H04N13/264 , H04N13/293 , H04N2013/0088
摘要： Objects within two-dimensional (2D) video data are modeled by three-dimensional (3D) models as a function of object type and motion through manually calibrating a 2D image to the three spatial dimensions of a 3D modeling cube. Calibrated 3D locations of an object in motion in the 2D image field of view of a video data input are computed and used to determine a heading direction of the object as a function of the camera calibration and determined movement between the computed 3D locations. The 2D object image is replaced in the video data input with an object-type 3D polygonal model having a projected bounding box that best matches a bounding box of an image blob, the model oriented in the determined heading direction. The bounding box of the replacing model is then scaled to fit the object image blob bounding box, and rendered with extracted image features.
摘要翻译：二维（2D）视频数据中的对象通过三维（3D）模型建模，作为对象类型和运动的函数，通过手动校准2D图像到3D建模立方体的三个空间维度。计算视频数据输入的2D图像视场中的运动对象的校准3D位置，并用于根据相机校准和所计算的3D位置之间确定的运动来确定对象的航向方向。 2D对象图像被替换为具有对象型3D多边形模型的视频数据输入，该模型具有最佳匹配图像斑点的边界框的投影边界框，该模型在确定的方位方向上定向。然后将替换模型的边界框缩放以适合对象图像Blob边界框，并使用提取的图像特征进行渲染。

2. 发明申请

US20140056479A1 DETERMINATION OF TRAIN PRESENCE AND MOTION STATE IN RAILWAY ENVIRONMENTS 有权
标题翻译：铁路环境中火车存在和运动状态的确定
公开(公告)号：US20140056479A1
公开(公告)日：2014-02-27
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： G06K9/62
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，则将帧标记为“列车存在”，否则，如果运动特征数据满足运动阈值，否则为“不存在运动;如运动特征数据满足运动阈值，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，即对于具有“列车不存在”和“静态”标签的组的“无列车存在”段内;在“列车存在和转换”段内在“火车现在”和“静态”标签组中，“列车现在”和“动作现状”标签组成的“火车现在和停止”部分中，列车在询问时的存在或运动状态为由各分段分类确定。

3. 发明申请

US20120316906A1 SPATIAL-TEMPORAL OPTIMIZATION OF PHYSICAL ASSET MAINTENANCE 审中-公开
标题翻译：物理资产维护的空间优化
公开(公告)号：US20120316906A1
公开(公告)日：2012-12-13
申请号：US13569891
申请日：2012-08-08
申请人： ARUN HAMPAPUR , Hongfei Li , Andrew J. Davenport , Shilpa Mahatma , Lexing Xie , Rogerio S. Feris , Wei Shan Dong , Zhong Bo Jiang , Hao Wang , Jing Xiao , Chunhua Tian
发明人： ARUN HAMPAPUR , Hongfei Li , Andrew J. Davenport , Shilpa Mahatma , Lexing Xie , Rogerio S. Feris , Wei Shan Dong , Zhong Bo Jiang , Hao Wang , Jing Xiao , Chunhua Tian
IPC分类号： G06Q10/06
CPC分类号： G06Q10/06 , G06Q10/0635 , Y02P90/86
摘要： A method for determining a maintenance schedule of geographically dispersed physical assets includes receiving asset data including infrastructure relationships between the assets, modeling failure risk of the assets based on spatial, temporal and network relationships, and producing the maintenance schedule according to a combination of the risk model, asset data, maintenance, and external operation constraints. The maintenance schedule may be corrective and/or strategic.
摘要翻译：用于确定地理上分散的物理资产的维护计划的方法包括接收资产数据，包括资产之间的基础设施关系，基于空间，时间和网络关系的资产的建模失败风险，以及根据风险的组合产生维护计划模型，资产数据，维护和外部操作限制。维护计划可能是纠正和/或策略性的。

4. 发明申请

US20120314030A1 ESTIMATION OF OBJECT PROPERTIES IN 3D WORLD 有权
标题翻译： 3D世界对象特性的估计
公开(公告)号：US20120314030A1
公开(公告)日：2012-12-13
申请号：US13154843
申请日：2011-06-07
申请人： Ankur Datta , Rogerio S. Feris , Yun Zhai
发明人： Ankur Datta , Rogerio S. Feris , Yun Zhai
IPC分类号： H04N13/00
CPC分类号： G06T17/10 , G06K9/00711 , G06K9/00771 , G06K9/46 , G06K9/4604 , G06K9/52 , G06K2009/4666 , G06T3/20 , G06T3/40 , G06T7/20 , G06T7/251 , G06T7/62 , G06T7/75 , G06T15/205 , G06T19/20 , G06T2200/24 , G06T2207/10016 , G06T2207/30232 , G06T2207/30236 , G06T2219/2004 , G06T2219/2016 , H04N13/264 , H04N13/293 , H04N2013/0088
摘要： Objects within two-dimensional (2D) video data are modeled by three-dimensional (3D) models as a function of object type and motion through manually calibrating a 2D image to the three spatial dimensions of a 3D modeling cube. Calibrated 3D locations of an object in motion in the 2D image field of view of a video data input are computed and used to determine a heading direction of the object as a function of the camera calibration and determined movement between the computed 3D locations. The 2D object image is replaced in the video data input with an object-type 3D polygonal model having a projected bounding box that best matches a bounding box of an image blob, the model oriented in the determined heading direction. The bounding box of the replacing model is then scaled to fit the object image blob bounding box, and rendered with extracted image features.
摘要翻译：二维（2D）视频数据中的对象通过三维（3D）模型建模，作为对象类型和运动的函数，通过手动校准2D图像到3D建模立方体的三个空间维度。计算视频数据输入的2D图像视场中的运动对象的校准3D位置，并用于根据相机校准和所计算的3D位置之间的确定的运动来确定对象的方位方向。 2D对象图像被替换为具有对象型3D多边形模型的视频数据输入，该模型具有最佳匹配图像斑点的边界框的投影边界框，该模型在确定的方位方向上定向。然后将替换模型的边界框缩放以适合对象图像Blob边界框，并使用提取的图像特征进行渲染。

5. 发明申请

US20120121170A1 OBJECT DETECTION SYSTEM BASED ON A POOL OF ADAPTIVE FEATURES 有权
标题翻译：基于自适应特征的对象检测系统
公开(公告)号：US20120121170A1
公开(公告)日：2012-05-17
申请号：US13353485
申请日：2012-01-19
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。

6. 发明申请

US20120027297A1 Object Segmentation at a Self-Checkout 失效
标题翻译：自检中的对象分割
公开(公告)号：US20120027297A1
公开(公告)日：2012-02-02
申请号：US12844340
申请日：2010-07-27
申请人： Rogerio S. Feris , Charles A. Otto , Sharathchandra Pankanti , Duan D. Tran
发明人： Rogerio S. Feris , Charles A. Otto , Sharathchandra Pankanti , Duan D. Tran
IPC分类号： G06K9/34
CPC分类号： G06T7/0079 , G06K9/34 , G06T7/11 , G06T7/136 , G06T2207/10024 , G06T2207/20012 , G06T2207/20021
摘要： Techniques for segmenting an object at a self-checkout are provided. The techniques include capturing an image of an object at a self-checkout, dividing the image into one or more blocks, computing one or more features of the image, computing a confidence value for each of the one or more blocks, wherein computing a confidence value for each of the one or more blocks comprises using a minimum feature distance from one or more reference backgound blocks, and eliminating one or more blocks from consideration via use of an adaptive threshold computed on the confidence value for each of the one or more blocks, wherein the one or more blocks remaining map to a region of the image containing the object.
摘要翻译：提供了在自检结果中分割对象的技术。这些技术包括在自检结果中捕获对象的图像，将图像划分成一个或多个块，计算图像的一个或多个特征，计算一个或多个块中的每一个的置信度值，其中计算置信度一个或多个块中的每个块的值包括使用来自一个或多个参考背景块的最小特征距离，并且通过使用针对所述一个或多个块中的每个块的置信度值计算的自适应阈值来消除考虑中的一个或多个块，其中所述一个或多个块保持映射到包含所述对象的图像的区域。

7. 发明申请

US20100106707A1 INDEXING AND SEARCHING ACCORDING TO ATTRIBUTES OF A PERSON 有权
标题翻译：根据个人的特征进行索引和搜索
公开(公告)号：US20100106707A1
公开(公告)日：2010-04-29
申请号：US12260418
申请日：2008-10-29
申请人： Lisa M. Brown , Raymond A. Cooke , Rogerio S. Feris , Arun Hampapur , Frederik C. M. Kjeldsen , Christopher S. Milite , Stephen R. Russo , Chiao-Fe Shu , Ying-li Tian , Yun Zhai , Zuoxuan Lu
发明人： Lisa M. Brown , Raymond A. Cooke , Rogerio S. Feris , Arun Hampapur , Frederik C. M. Kjeldsen , Christopher S. Milite , Stephen R. Russo , Chiao-Fe Shu , Ying-li Tian , Yun Zhai , Zuoxuan Lu
IPC分类号： G06F17/30 , G06F7/00
CPC分类号： G06F17/30793 , G06K9/6254
摘要： An approach that indexes and searches according to a set of attributes of a person is provided. In one embodiment, there is an extensible indexing and search tool, including an extraction component configured to extract a set of attributes of a person monitored by a set of sensors in a zone of interest. An index component is configured to index each of the set of attributes of the person within an index of an extensible indexing and search tool. A search component is configured to enable a search of the index of the extensible indexing and search tool according to at least one of the set of attributes of the person.
摘要翻译：提供了一种根据人的一组属性进行索引和搜索的方法。在一个实施例中，存在可扩展索引和搜索工具，其包括提取组件，其被配置为提取由感兴趣区域中的一组传感器监视的人的一组属性。索引组件被配置为对可扩展索引和搜索工具的索引内的人的一组属性进行索引。搜索组件被配置为根据人的一组属性中的至少一个来启用对可扩展索引和搜索工具的索引的搜索。

8. 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.

9. 发明授权

US08917934B2 Multi-cue object detection and analysis 有权
标题翻译：多提示对象检测和分析
公开(公告)号：US08917934B2
公开(公告)日：2014-12-23
申请号：US13523074
申请日：2012-06-14
申请人： Ankur Datta , Rogerio S. Feris , Sharathchandra U. Pankanti , Xiaoyu Wang
发明人： Ankur Datta , Rogerio S. Feris , Sharathchandra U. Pankanti , Xiaoyu Wang
IPC分类号： G06K9/00 , G06K9/34 , H04N1/40 , H04N1/46
CPC分类号： G06T7/11 , G06K9/00536 , G06K9/00785 , G06K9/3241 , G06K9/38 , G06K9/4642 , G06T7/13 , G06T7/194 , G06T2207/10016 , G06T2207/10024 , G06T2207/20021 , G06T2207/30236
摘要： Foreground objects of interest are distinguished from a background model by dividing a region of interest of a video data image into a grid array of individual cells that are each smaller than that a foreground object of interest. More particularly, image data of the foreground object of interest spans a contiguous plurality of the cells. Each of the cells are labeled as foreground if accumulated edge energy within the cell meets an edge energy threshold, if color intensities for different colors within each cell differ by a color intensity differential threshold, or as a function of combinations of said determinations in view of one or more combination rules.
摘要翻译：将感兴趣的前景物体与背景模型区分开，将视频数据图像的感兴趣区域划分为各自小于感兴趣的前景对象的各个单元格的网格阵列。更具体地，感兴趣的前景对象的图像数据跨越连续的多个单元。如果每个单元内的不同颜色的颜色强度与颜色强度差异阈值相差，或者作为所述确定的组合的函数，则单元格内的累积边缘能量满足边缘能量阈值时，每个单元格被标记为前景一个或多个组合规则。

10. 发明授权

US08903198B2 Image ranking based on attribute correlation 有权
标题翻译：基于属性相关的图像排名
公开(公告)号：US08903198B2
公开(公告)日：2014-12-02
申请号：US13152615
申请日：2011-06-03
申请人： Ankur Datta , Rogerio S. Feris , Sharathchandra U. Pankanti , Behjat Siddiquie
发明人： Ankur Datta , Rogerio S. Feris , Sharathchandra U. Pankanti , Behjat Siddiquie
IPC分类号： G06K9/60 , G06F17/30 , G06K9/62
CPC分类号： G06F17/30256 , G06F17/30277 , G06F17/3028 , G06F17/3053 , G06K9/00268 , G06K9/481 , G06K9/6263 , G06K9/66 , G06N99/005
摘要： Images are retrieved and ranked according to relevance to attributes of a multi-attribute query through training image attribute detectors for different attributes annotated in a training dataset. Pair-wise correlations are learned between pairs of the annotated attributes from the training dataset of images. Image datasets may then be searched via the trained attribute detectors for images comprising attributes in a multi-attribute query, wherein images are retrieved from the searching that each comprise one or more of the query attributes and also in response to information from the trained attribute detectors corresponding to attributes that are not a part of the query but are relevant to the query attributes as a function of the learned plurality of pair-wise correlations. The retrieved images are ranked as a function of respective total numbers of attributes within the query subset attributes.
摘要翻译：根据与训练数据集中注释的不同属性的训练图像属性检测器，根据与多属性查询的属性的相关性来检索和排列图像。在图像训练数据集的注释属性对之间学习成对相关。然后可以经由经训练的属性检测器搜索包括多属性查询中的属性的图像的图像数据集，其中从搜索中检索每个包括一个或多个查询属性的图像，并且还响应于来自经训练的属性检测器的信息对应于不是查询的一部分但与所学习的多个成对相关性的函数的查询属性相关的属性。检索到的图像根据查询子集属性内的各个属性总数的顺序排列。

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