专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

31. 发明申请

US20060129843A1 Method and apparatus for electronically extracting application specific multidimensional information from documents selected from a set of documents electronically extracted from a library of electronically searchable documents 审中-公开
公开(公告)号：US20060129843A1
公开(公告)日：2006-06-15
申请号：US11198798
申请日：2005-08-05
申请人： Narayan Srinivasa , Swarup Medasani , Yuri Owechko , Deepak Khosla
发明人： Narayan Srinivasa , Swarup Medasani , Yuri Owechko , Deepak Khosla
IPC分类号： G06F12/14
CPC分类号： G06F16/335 , Y10S707/99933 , Y10S707/99935 , Y10S707/99942 , Y10S707/99943 , Y10S707/99945
摘要： An apparatus and method is disclosed for providing application specific multi-dimensional information to an application running on a user computing device, wherein at least one dimension of the information is a category, from a plurality of member documents electronically extracted from a library of electronically searchable documents, which may comprise an application specific multidimensional information extractor adapted to extract occurrences of prospective representations of dimensions of application specific multidimensional information from the member documents, and to extract occurrences of non-application specific multidimensional information from the member documents; and, an encoder adapted to encode the occurrences of prospective dimensions of application specific multidimensional information and non-application specific multidimensional information contained in member documents according to a dimension specific coded representation of each dimension of application specific multidimensional information and a non-application specific coded representation of each non-application specific multidimensional information element. The apparatus and method may further comprise a member document identifier adapted to determine whether a member document contains coded formatting, and if not, whether the member document is a dense document, and if not, for rejecting the document from further processing, and the coded formatting may comprise network markup language coding. The apparatus and method may further comprise an application specific multidimensional information verification unit adapted verify the extraction of application specific multi-dimensional information from the member documents, and may further comprise a database for storing the application specific multi-dimensional information adapted to provide an application running on a user computing device access to the application specific multidimensional information. The application specific multidimensional information may be scheduled events having the dimensions of time, location and event identity, and the application running on the user computer can be an electronic calendar or other similar scheduling software program.

32. 发明授权

US09361523B1 Video content-based retrieval 有权
标题翻译：基于视频内容的检索
公开(公告)号：US09361523B1
公开(公告)日：2016-06-07
申请号：US12841078
申请日：2010-07-21
申请人： Yang Chen , Swarup Medasani , Qin Jiang , David L. Allen , Tsai-Ching Lu
发明人： Yang Chen , Swarup Medasani , Qin Jiang , David L. Allen , Tsai-Ching Lu
IPC分类号： G06K9/03 , G06K9/00
CPC分类号： G06K9/00758 , G06K9/00711 , G06K9/00718 , G06K9/00744 , G06K9/4676 , G06T2207/10016 , G06T2210/00
摘要： A method and system for video-content based retrieval is described. A query video depicting an activity is processed using interest point selection to find locations in the video that are relevant to that activity. A set of spatio-temporal descriptors such as self-similarity and 3-D SIFT are calculated within a local neighborhood of the set of interest points. An indexed video database containing videos similar to the query video is searched using the set of descriptors to obtain a set of candidate videos. The videos in the video database are indexed hierarchically using a vocabulary tree or other hierarchical indexing mechanism.
摘要翻译：描述了基于视频内容的检索的方法和系统。使用兴趣点选择来处理描绘活动的查询视频，以查找视频中与该活动相关的位置。在一组感兴趣点的本地邻域内计算一组空间 - 时间描述符，例如自相似性和3-D SIFT。使用该组描述符搜索包含与查询视频类似的视频的索引视频数据库，以获得一组候选视频。视频数据库中的视频使用词汇树或其他分层索引机制分层索引。

33. 发明授权

US09129158B1 Method and system for embedding visual intelligence 有权
标题翻译：嵌入视觉智能的方法和系统
公开(公告)号：US09129158B1
公开(公告)日：2015-09-08
申请号：US13412527
申请日：2012-03-05
申请人： Swarup Medasani , Suhas E. Chelian , Shinko Y. Cheng , Rashmi N. Sundareswara , Howard Neely, III
发明人： Swarup Medasani , Suhas E. Chelian , Shinko Y. Cheng , Rashmi N. Sundareswara , Howard Neely, III
IPC分类号： G06K9/62 , G06K9/00 , G06T7/20
CPC分类号： G06K9/00718 , G06K9/00335 , G06K9/00342 , G06K9/6219 , G06K9/6263 , G06K9/6296 , G06T2207/10016
摘要： Described is a method and system for embedding unsupervised learning into three critical processing stages of the spatio-temporal visual stream. The system first receives input video comprising input video pixels representing at least one action and at least one object having a location. Microactions are generated from the input image using a set of motion sensitive filters. A relationship between the input video pixels and the microactions is then learned, and a set of spatio-temporal concepts is learned from the microactions. The system then learns to acquire new knowledge from the spatio-temporal concepts using mental imagery processes. Finally, a visual output is presented to a user based on the learned set of spatio-temporal concepts and the new knowledge to aid the user in visually comprehending the at least one action in the input video.
摘要翻译：描述了将无监督学习嵌入时空视觉流的三个关键处理阶段的方法和系统。系统首先接收包括表示至少一个动作的输入视频像素和至少一个具有位置的对象的输入视频。使用一组运动敏感滤波器从输入图像生成微反应。然后学习输入视频像素和微动作之间的关系，并从微动态学习一组时空概念。该系统然后学习从使用心理图像过程的时空概念中获取新知识。最后，基于学习的时空概念和新知识，向用户呈现视觉输出，以帮助用户直观地理解输入视频中的至少一个动作。

34. 发明授权

US08948501B1 Three-dimensional (3D) object detection and multi-agent behavior recognition using 3D motion data 有权
标题翻译：使用3D运动数据的三维（3D）物体检测和多代理行为识别
公开(公告)号：US08948501B1
公开(公告)日：2015-02-03
申请号：US13535286
申请日：2012-06-27
申请人： Kyungnam Kim , Shankar R. Rao , Yuri Owechko , Swarup Medasani , Michael Cao , Jiejun Xu
发明人： Kyungnam Kim , Shankar R. Rao , Yuri Owechko , Swarup Medasani , Michael Cao , Jiejun Xu
IPC分类号： G06K9/62
CPC分类号： G01S7/4808 , G01S17/89 , G06K9/00201 , G06K9/00335 , G06K9/00711 , G06T7/11 , G06T7/136 , G06T7/187 , G06T2207/10044 , G06T2207/20021
摘要： The present invention relates to an object detection and behavior recognition system using three-dimensional motion data. The system receives three-dimensional (3D) motion data of a scene from at least one sensor, such as a LIDAR sensor. An object is identified in the 3D motion data. Thereafter, an object track is extracted, the object track being indicative of object motion in the scene over time. Through Dynamic Time Warping (DTW) or other comparison techniques, the object track is compared to a database to identify the behavior of the object based on its object track.
摘要翻译：本发明涉及使用三维运动数据的物体检测和行为识别系统。该系统从诸如LIDAR传感器的至少一个传感器接收场景的三维（3D）运动数据。在3D运动数据中识别对象。此后，提取对象轨道，物体轨迹指示场景中的物体运动随着时间的推移。通过动态时间扭曲（DTW）或其他比较技术，将对象轨迹与数据库进行比较，以基于其对象轨迹来识别对象的行为。

35. 发明授权

US08948499B1 Method for online learning and recognition of visual behaviors 有权
标题翻译：在线学习和识别视觉行为的方法
公开(公告)号：US08948499B1
公开(公告)日：2015-02-03
申请号：US12962548
申请日：2010-12-07
申请人： Swarup Medasani , David L. Allen , Suhas E. Chelian , Yuri Owechko
发明人： Swarup Medasani , David L. Allen , Suhas E. Chelian , Yuri Owechko
IPC分类号： G06K9/62
CPC分类号： G06K9/469 , G06K9/00771 , G06K9/00785 , G06K9/6296
摘要： Described is a system for object and behavior recognition which utilizes a collection of modules which, when integrated, can automatically recognize, learn, and adapt to simple and complex visual behaviors. An object recognition module utilizes a cooperative swarm algorithm to classify an object in a domain. A graph-based object representation module is configured to use a graphical model to represent a spatial organization of the object within the domain. Additionally, a reasoning and recognition engine module consists of two sub-modules: a knowledge sub-module and a behavior recognition sub-module. The knowledge sub-module utilizes a Bayesian network, while the behavior recognition sub-module consists of layers of adaptive resonance theory clustering networks and a layer of a sustained temporal order recurrent temporal order network. The described invention has applications in video forensics, data mining, and intelligent video archiving.
摘要翻译：描述了一种用于对象和行为识别的系统，其利用模块集合，当集成时，可以自动识别，学习和适应简单和复杂的视觉行为。对象识别模块利用协作群算法对域中的对象进行分类。基于图形的对象表示模块被配置为使用图形模型来表示域内对象的空间组织。另外，推理和识别引擎模块由两个子模块组成：知识子模块和行为识别子模块。知识子模块利用贝叶斯网络，而行为识别子模块由自适应共振理论聚类网络层和持续时间顺序复现时间顺序网络层组成。所描述的发明在视频取证，数据挖掘和智能视频归档中具有应用。

36. 发明授权

US08798372B1 Method for detecting bridges using lidar point cloud data 有权
标题翻译：使用激光雷达云数据检测桥梁的方法
公开(公告)号：US08798372B1
公开(公告)日：2014-08-05
申请号：US13414391
申请日：2012-03-07
申请人： Dmitriy Korchev , Swarup Medasani , Yuri Owechko
发明人： Dmitriy Korchev , Swarup Medasani , Yuri Owechko
IPC分类号： G06K9/46
CPC分类号： G06K9/00637 , G06K9/00651 , G06K9/6211
摘要： Described is a system and method for detecting elevated structures, such as bridges and overpasses, in point cloud data. A set of data from a three-dimensional point cloud of a landscape is received by the system. The set of data points comprises inlier data points and outlier data points. The inlier data points in the three-dimensional point cloud data are identified and combined into at least one segment. The segment is converted into an image comprising at least one image level. Each image level is processed with an edge detection algorithm to detect elevated edges. The elevated edges are vectorized to identify an elevated structure of interest in the landscape. The present invention is useful in applications that require three-dimensional sensing systems, such as autonomous navigation and surveillance applications.
摘要翻译：描述了用于在点云数据中检测诸如桥梁和立交桥的升高结构的系统和方法。由系统接收来自景观的三维点云的一组数据。数据点集合包括异常数据点和异常值数据点。三维点云数据中的上位数据点被识别并组合成至少一个段。该片段被转换成包括至少一个图像级别的图像。每个图像级别都使用边缘检测算法进行处理，以检测提升的边缘。提升的边缘被矢量化以识别景观中兴趣兴高的结构。本发明在需要诸如自主导航和监视应用的三维感测系统的应用中是有用的。

37. 发明授权

US08744200B1 Hybrid compressive/Nyquist sampling for enhanced sensing 有权
标题翻译：混合压缩/奈奎斯特采样用于增强感测
公开(公告)号：US08744200B1
公开(公告)日：2014-06-03
申请号：US13464887
申请日：2012-05-04
申请人： Yuri Owechko , Swarup Medasani
发明人： Yuri Owechko , Swarup Medasani
IPC分类号： G06K9/54 , G06K9/60
CPC分类号： H04N5/23245 , G06K9/00496 , H04N5/23229 , H04N19/136 , H04N19/194
摘要： Described is a knowledge-enhanced compressive imaging system. The system first initializes a compressive measurement basis set and a measurement matrix using task- and scene-specific prior knowledge. An image captured using the imaging mode of the dual-mode sensor is then sampled to extract context knowledge. The compressive measurement basis set and the measurement matrix are adapted using the extracted context knowledge and the prior knowledge. Task-relevant compressive measurements of the image are performed using the compressive measurement mode of the dual-mode sensor, and compressive reconstruction of the image is performed. Finally, a task and context optimized signal representation of the image is generated.
摘要翻译：描述了一种知识增强的压缩成像系统。系统首先使用任务和场景特定的先验知识初始化压缩测量基础集和测量矩阵。然后对使用双模传感器的成像模式捕获的图像进行采样以提取上下文知识。使用提取的上下文知识和现有知识来调整压缩测量基础集和测量矩阵。使用双模传感器的压缩测量模式执行图像的任务相关的压缩测量，并且执行图像的压缩重建。最后，生成图像的任务和上下文优化的信号表示。

38. 发明授权

US08589315B2 Behavior recognition using cognitive swarms and fuzzy graphs 有权
标题翻译：使用认知群体和模糊图的行为识别
公开(公告)号：US08589315B2
公开(公告)日：2013-11-19
申请号：US11800264
申请日：2007-05-03
申请人： Swarup Medasani , Yuri Owechko
发明人： Swarup Medasani , Yuri Owechko
IPC分类号： G06F15/18 , G06F15/00
CPC分类号： G06K9/6292 , G06K9/00369 , G06K9/6229
摘要： Described is a behavior recognition system for detecting the behavior of objects in a scene. The system comprises a semantic object stream module for receiving a video stream having at least two frames and detecting objects in the video stream. Also included is a group organization module for utilizing the detected objects from the video stream to detect a behavior of the detected objects. The group organization module further comprises an object group stream module for spatially organizing the detected objects to have relative spatial relationships. The group organization module also comprises a group action stream module for modeling a temporal structure of the detected objects. The temporal structure is an action of the detected objects between the two frames, whereby through detecting, organizing and modeling actions of objects, a user can detect the behavior of the objects.
摘要翻译：描述了用于检测场景中的对象的行为的行为识别系统。该系统包括语义对象流模块，用于接收具有至少两个帧的视频流并检测视频流中的对象。还包括用于利用来自视频流的检测对象的组织组织模块来检测检测到的对象的行为。组织模块还包括用于空间组织所检测到的对象以具有相对空间关系的对象组流模块。组织模块还包括用于对所检测到的对象的时间结构建模的组动作流模块。时间结构是两帧之间检测到的对象的动作，由此通过检测，组织和建模对象的动作，用户可以检测对象的行为。

39. 发明授权

US08488877B1 System for object recognition in colorized point clouds 有权
标题翻译：彩色点云中物体识别系统
公开(公告)号：US08488877B1
公开(公告)日：2013-07-16
申请号：US12592836
申请日：2009-12-02
申请人： Yuri Owechko , Swarup Medasani , Ronald T. Azuma , Jim Nelson
发明人： Yuri Owechko , Swarup Medasani , Ronald T. Azuma , Jim Nelson
IPC分类号： G06K9/00
CPC分类号： G06K9/00201 , G06K9/00704
摘要： Described is a system for object recognition in colorized point clouds. The system includes an implicit geometry engine that is configured to receive three-dimensional (3D) colorized cloud point data regarding a 3D object of interest and to convert the cloud point data into implicit representations. The engine also generates geometric features. A geometric grammar block is included to generate object cues and recognize geometric objects using geometric tokens and grammars based on object taxonomy. A visual attention cueing block is included to generate object cues based on 3D geometric properties. Finally, an object recognition block is included to perform a local search for objects using cues from the cueing block and the geometric grammar block and to classify the 3D object of interest as a particular object upon a classifier reaching a predetermined threshold.
摘要翻译：描述了在彩色点云中的对象识别系统。该系统包括隐式几何引擎，其被配置为接收关于感兴趣的3D对象的三维（3D）着色浊点数据，并将该浊点数据转换为隐含表示。引擎还生成几何特征。包含几何语法块以生成对象提示，并使用基于对象分类法的几何令牌和语法来识别几何对象。包括视觉注意提示块，以根据3D几何属性生成对象提示。最后，包括对象识别块，以使用来自提示块和几何语法块的提示来执行对象的本地搜索，并且在分类器达到预定阈值时将感兴趣的3D对象分类为特定对象。

40. 发明授权

US08213709B1 Method and system for directed area search using cognitive swarm vision and cognitive Bayesian reasoning 有权
标题翻译：使用认知群体视觉和认知贝叶斯推理的定向区域搜索的方法和系统
公开(公告)号：US08213709B1
公开(公告)日：2012-07-03
申请号：US12590110
申请日：2009-11-03
申请人： Swarup Medasani , Yuri Owechko , Tsai-Ching Lu , Deepak Khosla , David L. Allen
发明人： Swarup Medasani , Yuri Owechko , Tsai-Ching Lu , Deepak Khosla , David L. Allen
IPC分类号： G06K9/62
CPC分类号： G06K9/6278 , G06K9/00671 , G06K9/6263 , G06N7/005
摘要： A method and system for a directed area search using cognitive swarm vision and cognitive Bayesian reasoning is disclosed. The system comprises a domain knowledge database, a top-down reasoning module, and a bottom-up module. The domain knowledge database is configured to store Bayesian network models comprising visual features and observables associated with various sets of entities. The top-down module is configured to receive a search goal, generate a plan of action using Bayesian network models, and partition the plan into a set of tasks/observables to be located in the imagery. The bottom-up module is configured to select relevant feature/attention models for the observables, and search the visual imagery using a cognitive swarm for the at least one observable. The system further provides for operator feedback and updating of the domain knowledge database to perform better future searches.
摘要翻译：公开了一种使用认知群体视觉和认知贝叶斯推理的定向区域搜索的方法和系统。该系统包括域知识数据库，自上而下推理模块和自下而上模块。域知识数据库被配置为存储包括与各组实体相关联的视觉特征和可观察性的贝叶斯网络模型。自顶向下模块被配置为接收搜索目标，使用贝叶斯网络模型生成行动计划，并将计划分成一组要在图像中的任务/可观察值。自下而上模块被配置为选择可观察的相关特征/关注模型，并且使用用于至少一个可观察的认知群搜索视觉图像。该系统进一步提供操作者反馈和更新领域知识数据库以执行更好的未来搜索。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式