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    • 2. 发明授权
    • Opportunistic cascade and cascade training, evaluation, and execution for vision-based object detection
    • 机会级联和级联培训,评估和执行基于视觉的对象检测
    • US09449259B1
    • 2016-09-20
    • US13558298
    • 2012-07-25
    • Shinko Y. ChengYuri OwechkoSwarup Medasani
    • Shinko Y. ChengYuri OwechkoSwarup Medasani
    • G06K9/62G06K9/46G06K9/66G06K9/68G06K9/70G06N99/00
    • G06K9/6257G06K9/3241G06K9/6217G06N99/005
    • The present invention relates to a classifier cascade object detection system. The system operates by inputting an image patch into parallel feature generation modules, each of the feature generation modules operable for extracting features from the image patch. The features are provided to an opportunistic classifier cascade, the opportunistic classifier cascade having a series of classifier stages. The opportunistic classifier cascade is executed by progressively evaluating, in each classifier in the classifier cascade, the features to produce a response, with each response progressively utilized by a decision function to generate a stage response for each classifier stage. If each stage response exceeds a stage threshold then the image patch is classified as a target object, and if the stage response from any of the decision functions does not exceed the stage threshold, then the image patch is classified as a non-target object.
    • 本发明涉及分级器级联物体检测系统。 该系统通过将图像补丁输入到并行特征生成模块中来操作,每个特征生成模块可操作用于从图像补片提取特征。 这些特征被提供给机会分类器级联,机会分类器级联具有一系列分类器级。 机会分类器级联是通过在分类器级联中的每个分类器中逐步评估产生响应的特征来执行的,每个响应由决策函数逐渐被利用以产生每个分类器阶段的阶段响应。 如果每个阶段响应超过阶段阈值,则图像补丁被分类为目标对象,并且如果来自任何决策函数的阶段响应不超过阶段阈值,则将图像补丁分类为非目标对象。
    • 3. 发明授权
    • Vision system for monitoring humans in dynamic environments
    • 用于在动态环境中监测人的视觉系统
    • US08253792B2
    • 2012-08-28
    • US12549425
    • 2009-08-28
    • James W. WellsRoland J. MenassaCharles W. Wampler, IISwarup MedasaniYuri OwechkoKyungnam KimYang Chen
    • James W. WellsRoland J. MenassaCharles W. Wampler, IISwarup MedasaniYuri OwechkoKyungnam KimYang Chen
    • H04N9/47
    • H04N7/181
    • 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.
    • 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。
    • 5. 发明申请
    • Vision System for Monitoring Humans in Dynamic Environments
    • 动态环境监测人的视觉系统
    • US20110050878A1
    • 2011-03-03
    • US12549425
    • 2009-08-28
    • James W. WellsRoland J. MenassaCharles W. Wampler, IISwarup MedasaniYuri OwechkoKyungnam KimYang Chen
    • James W. WellsRoland J. MenassaCharles W. Wampler, IISwarup MedasaniYuri OwechkoKyungnam KimYang Chen
    • H04N7/18
    • H04N7/181
    • 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.
    • 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. 发明申请
    • Graph-based cognitive swarms for object group recognition
    • 基于图的认知群体,用于对象组识别
    • US20070183670A1
    • 2007-08-09
    • US11433159
    • 2006-05-12
    • Yuri OwechkoSwarup Medasani
    • Yuri OwechkoSwarup Medasani
    • G06K9/62G06K9/46
    • G06K9/6292G06K9/00369G06K9/6229
    • 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.
    • 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。
    • 10. 发明授权
    • Hierarchical video search and recognition system
    • 分层视频搜索和识别系统
    • US08874584B1
    • 2014-10-28
    • US12660320
    • 2010-02-24
    • Yang ChenSwarup MedasaniDavid L. AllenQin JiangYuri OwechkoTsai-Ching Lu
    • Yang ChenSwarup MedasaniDavid L. AllenQin JiangYuri OwechkoTsai-Ching Lu
    • G06F17/30
    • G06F17/30805G06F17/30811
    • 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.
    • 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。