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1. 发明授权

US08874584B1 Hierarchical video search and recognition system 有权
标题翻译：分层视频搜索和识别系统
公开(公告)号：US08874584B1
公开(公告)日：2014-10-28
申请号：US12660320
申请日：2010-02-24
申请人： Yang Chen , Swarup Medasani , David L. Allen , Qin Jiang , Yuri Owechko , Tsai-Ching Lu
发明人： Yang Chen , Swarup Medasani , David L. Allen , Qin Jiang , Yuri Owechko , Tsai-Ching Lu
IPC分类号： G06F17/30
CPC分类号： G06F17/30805 , G06F17/30811
摘要： Described is a system for content recognition, search, and retrieval in visual data. The system is configured to perform operations of receiving visual data as an input, processing the visual data, and extracting distinct activity-agnostic content descriptors from the visual data at each level of a hierarchical content descriptor module. The resulting content descriptors are then indexed with a hierarchical content indexing module, wherein each level of the content indexing module comprises a distinct set of indexed content descriptors. The visual data, generated content descriptors, and indexed content descriptors are then stored in a storage module. Finally, based on a content-based query by a user, the storage module is searched, and visual data containing the content of interest is retrieved and presented to the user. A method and computer program product for content recognition, search, and retrieval in visual data are also described.
摘要翻译：描述了用于视觉数据中的内容识别，搜索和检索的系统。该系统被配置为执行接收视觉数据作为输入，处理可视数据以及从分层内容描述符模块的每个级别的视觉数据中提取不同的活动不可知内容描述符的操作。所得到的内容描述符然后用分层内容索引模块进行索引，其中内容索引模块的每个级别包括不同的索引内容描述符集合。然后将可视数据，生成的内容描述符和索引的内容描述符存储在存储模块中。最后，基于用户的基于内容的查询，搜索存储模块，并且检索包含感兴趣内容的视觉数据并呈现给用户。还描述了用于视觉数据中的内容识别，搜索和检索的方法和计算机程序产品。

2. 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。

3. 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。

4. 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。

5. 发明授权

US08645294B1 Method for image registration utilizing particle swarm optimization 有权
标题翻译：使用粒子群优化的图像配准方法
公开(公告)号：US08645294B1
公开(公告)日：2014-02-04
申请号：US12583238
申请日：2009-08-17
申请人： Yuri Owechko , Yang Chen , Swarup Medasani
发明人： Yuri Owechko , Yang Chen , Swarup Medasani
IPC分类号： G06F15/18
CPC分类号： G06N5/043 , G06K9/6229 , G06N3/006 , G06T7/337 , G06T7/35
摘要： Described is a method for image registration utilizing particle swarm optimization (PSO). In order to register two images, a set of image windows is first selected from a test image and transformed. A plurality of software agents is configured to operate as a cooperative swarm to optimize an objective function, and an objective function is then evaluated at the location of each agent. The objective function represents a measure of the difference or registration quality between at least one transformed image window and a reference image. The position vectors representing the current individual best solution found and the current global best solution found by all agents are then updated according to PSO dynamics. Finally, the current global best solution is compared with a maximum pixel value which signifies a match between an image window and the reference image. A system and a computer program product are also described.
摘要翻译：描述了使用粒子群优化（PSO）的图像配准的方法。为了注册两个图像，首先从测试图像中选择一组图像窗口并进行变换。多个软件代理被配置为作为协作群来操作以优化目标函数，然后在每个代理的位置处评估目标函数。目标函数表示至少一个变换的图像窗口和参考图像之间的差异或注册质量的度量。然后根据PSO动态更新表示当前找到的最佳解决方案的位置向量和所有代理发现的当前全局最佳解。最后，将当前全局最佳解决方案与表示图像窗口和参考图像之间的匹配的最大像素值进行比较。还描述了系统和计算机程序产品。

6. 发明授权

US08253792B2 Vision system for monitoring humans in dynamic environments 有权
标题翻译：用于在动态环境中监测人的视觉系统
公开(公告)号：US08253792B2
公开(公告)日：2012-08-28
申请号：US12549425
申请日：2009-08-28
申请人： James W. Wells , Roland J. Menassa , Charles W. Wampler, II , Swarup Medasani , Yuri Owechko , Kyungnam Kim , Yang Chen
发明人： James W. Wells , Roland J. Menassa , Charles W. Wampler, II , Swarup Medasani , Yuri Owechko , Kyungnam Kim , Yang Chen
IPC分类号： H04N9/47
CPC分类号： H04N7/181
摘要： A safety monitoring system for a workspace area. The workspace area related to a region having automated moveable equipment. A plurality of vision-based imaging devices capturing time-synchronized image data of the workspace area. Each vision-based imaging device repeatedly capturing a time synchronized image of the workspace area from a respective viewpoint that is substantially different from the other respective vision-based imaging devices. A visual processing unit for analyzing the time-synchronized image data. The visual processing unit processes the captured image data for identifying a human from a non-human object within the workspace area. The visual processing unit further determining potential interactions between a human and the automated moveable equipment. The visual processing unit further generating control signals for enabling dynamic reconfiguration of the automated moveable equipment based on the potential interactions between the human and the automated moveable equipment in the workspace area.
摘要翻译：用于工作区的安全监控系统。与具有自动移动设备的区域相关的工作空间区域。多个基于视觉的成像设备捕获工作区域的时间同步图像数据。每个基于视觉的成像设备从与其他各自的基于视觉的成像设备基本上不同的相应视点重复地捕获工作区域的时间同步图像。一种用于分析时间同步图像数据的可视处理单元。视觉处理单元从工作区域内的非人物对象处理用于识别人的拍摄图像数据。视觉处理单元进一步确定人与自动移动设备之间的潜在交互作用。视觉处理单元还基于人与工作空间区域中的自动移动设备之间的潜在交互，进一步产生用于实现自动移动设备的动态重新配置的控制信号。

7. 发明授权

US08793200B1 Method for particle swarm optimization with random walk 有权
标题翻译：随机散乱的粒子群优化方法
公开(公告)号：US08793200B1
公开(公告)日：2014-07-29
申请号：US12586505
申请日：2009-09-22
申请人： Yang Chen , Yuri Owechko , Swarup Medasani
发明人： Yang Chen , Yuri Owechko , Swarup Medasani
IPC分类号： G06N5/00
CPC分类号： G06N5/003 , G06N3/006
摘要： Described is a method for particle swarm optimization (PSO) utilizing a random walk process. A plurality of software agents is configured to operate as a cooperative swarm to locate an optimum of an objective function. The method described herein comprises two phases. In a first phase, the plurality of software agents randomly explores the multi-dimensional solution space by undergoing a Brownian motion style random walk process. In a second phase, the velocity and position vectors for each particle are updated probabilistically according to a PSO algorithm. By allowing the particles to undergo a random walk phase, the particles have an increased opportunity to explore their neighborhood, land in the neighborhood of a true optimum, and avoid prematurely converging on a sub-optimum. The present invention improves on what is currently known by increasing the success rate of the PSO algorithm in addition to reducing the required computation.
摘要翻译：描述了利用随机游走过程的粒子群优化（PSO）的方法。多个软件代理被配置为作为协作群操作以定位目标函数的最优。本文描述的方法包括两个阶段。在第一阶段，多个软件代理人通过经历布朗运动风格随机游走过程随机探索多维解决方案空间。在第二阶段，根据PSO算法概率地更新每个粒子的速度和位置向量。通过允许颗粒经历随机游走阶段，颗粒具有增加的机会来探索它们的邻域，附近的真实最优值，并避免过早地收敛于次优。除了减少所需的计算之外，本发明通过增加PSO算法的成功率来改进当前所知道的内容。

8. 发明申请

US20110050878A1 Vision System for Monitoring Humans in Dynamic Environments 有权
标题翻译：动态环境监测人的视觉系统
公开(公告)号：US20110050878A1
公开(公告)日：2011-03-03
申请号：US12549425
申请日：2009-08-28
申请人： James W. Wells , Roland J. Menassa , Charles W. Wampler, II , Swarup Medasani , Yuri Owechko , Kyungnam Kim , Yang Chen
发明人： James W. Wells , Roland J. Menassa , Charles W. Wampler, II , Swarup Medasani , Yuri Owechko , Kyungnam Kim , Yang Chen
IPC分类号： H04N7/18
CPC分类号： H04N7/181
摘要： A safety monitoring system for a workspace area. The workspace area related to a region having automated moveable equipment. A plurality of vision-based imaging devices capturing time-synchronized image data of the workspace area. Each vision-based imaging device repeatedly capturing a time synchronized image of the workspace area from a respective viewpoint that is substantially different from the other respective vision-based imaging devices. A visual processing unit for analyzing the time-synchronized image data. The visual processing unit processes the captured image data for identifying a human from a non-human object within the workspace area. The visual processing unit further determining potential interactions between a human and the automated moveable equipment. The visual processing unit further generating control signals for enabling dynamic reconfiguration of the automated moveable equipment based on the potential interactions between the human and the automated moveable equipment in the workspace area.
摘要翻译：用于工作区的安全监控系统。与具有自动移动设备的区域相关的工作空间区域。多个基于视觉的成像设备捕获工作区域的时间同步图像数据。每个基于视觉的成像设备从与其他各自的基于视觉的成像设备基本上不同的相应视点重复地捕获工作区域的时间同步图像。一种用于分析时间同步图像数据的可视处理单元。视觉处理单元从工作区域内的非人物对象处理用于识别人的拍摄图像数据。视觉处理单元进一步确定人与自动移动设备之间的潜在交互作用。视觉处理单元还基于人与工作空间区域中的自动移动设备之间的潜在交互，进一步产生用于实现自动移动设备的动态重新配置的控制信号。

9. 发明授权

US07715591B2 High-performance sensor fusion architecture 有权
标题翻译：高性能传感器融合架构
公开(公告)号：US07715591B2
公开(公告)日：2010-05-11
申请号：US10132875
申请日：2002-04-24
申请人： Yuri Owechko , Narayan Srinivasa , Swarup Medasani , Riccardo Boscolo
发明人： Yuri Owechko , Narayan Srinivasa , Swarup Medasani , Riccardo Boscolo
IPC分类号： G06K9/00
CPC分类号： G06K9/6292 , G06K9/00201 , G06K9/00369 , G06K9/00832 , G06K9/209 , G06K9/522 , G06T7/97 , G06T2207/10021 , G06T2207/20064 , G06T2207/30268 , H04N2013/0081 , H04N2013/0092
摘要： A vision-based system for automatically detecting the type of object within a specified area, such as the type of occupant within a vehicle is presented. The type of occupant can then be used to determine whether an airbag deployment system should be enabled or not. The system extracts different features, including wavelet features and/or a disparity map from images captured by image sensors. These features are then processed by classification algorithms to produce class confidences for various occupant types. The occupant class confidences are fused and processed to determine occupant type. In a preferred embodiment, image features from image edges, wavelet features, and disparity are used. Various classification algorithms may be implemented to classify the object. Use of the disparity map and/or wavelet features provides greater computational efficiency.
摘要翻译：提出了一种基于视觉的系统，用于自动检测指定区域内物体的类型，例如车辆内乘客的类型。然后可以使用乘客的类型来确定是否应启用安全气囊展开系统。该系统从图像传感器捕获的图像中提取不同的特征，包括小波特征和/或视差图。然后通过分类算法对这些特征进行处理，以便为各种乘客类型生成类别信息。乘员班信心被融合和处理以确定乘客类型。在优选实施例中，使用来自图像边缘的图像特征，小波特征和视差。可以实现各种分类算法来对对象进行分类。使用视差图和/或小波特征提供更大的计算效率。

10. 发明申请

US20070183670A1 Graph-based cognitive swarms for object group recognition 有权
标题翻译：基于图的认知群体，用于对象组识别
公开(公告)号：US20070183670A1
公开(公告)日：2007-08-09
申请号：US11433159
申请日：2006-05-12
申请人： Yuri Owechko , Swarup Medasani
发明人： Yuri Owechko , Swarup Medasani
IPC分类号： G06K9/62 , G06K9/46
CPC分类号： G06K9/6292 , G06K9/00369 , G06K9/6229
摘要： An object recognition system is described that incorporates swarming classifiers. The swarming classifiers comprise a plurality of software agents configured to operate as a cooperative swarm to classify an object group in a domain. Each node N represents an object in the group having K object attributes. Each agent is assigned an initial velocity vector to explore a KN-dimensional solution space for solutions matching the agent's graph. Further, each agent is configured to search the solution space for an optimum solution. The agents keep track of their coordinates in the KN-dimensional solution space that are associated with an observed best solution (pbest) and a global best solution (gbest). The gbest is used to store the best solution among all agents which corresponds to a best graph among all agents. Each velocity vector thereafter changes towards pbest and gbest, allowing the cooperative swarm to classify of the object group.
摘要翻译：描述了包含群组分类器的对象识别系统。群集分类器包括被配置为作为协作群进行操作以将域中的对象组分类的多个软件代理。每个节点N表示具有K个对象属性的组中的对象。为每个代理分配一个初始速度向量，以探索与代理图相匹配的解决方案的KN维解决方案空间。此外，每个代理被配置为搜索解空间以获得最佳解决方案。代理人跟踪与观察到的最佳解决方案（pbest）和全局最佳解决方案（gbest）相关联的KN维解决方案空间中的坐标。 gbest用于在所有代理之间存储对应于最佳图形的所有代理中的最佳解决方案。其后每个速度矢量向pbest和gbest变化，允许协作群对目标群进行分类。

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