Detecting and locating actors in scenes based on degraded or supersaturated depth data

    公开(公告)号:US10915783B1

    公开(公告)日:2021-02-09

    申请号:US16220461

    申请日:2018-12-14

    Abstract: An imaging device may capture images of a scene, where the scene includes retroreflective materials. Where visual images and depth images are captured from a scene, and the depth images have ratios of supersaturated pixels that are less than a predetermined threshold, a location map of the scene is generated or updated based on the depth images. Where the ratios are greater than the predetermined threshold, the location map of the scene is generated or updated based on the visual images. Additionally, where each of a plurality of imaging devices detect concentrations of supersaturated pixels beyond a predetermined threshold or limit within their respective fields of view, an actor present on the scene may be determined to be wearing retroreflective material, or otherwise designated as a source of the supersaturation, and tracked with the scene based on coverage areas that are determined to have excessive ratios of supersaturated pixels.

    MACHINE LEARNING MEMORY MANAGEMENT AND DISTRIBUTED RULE EVALUATION
    5.
    发明申请
    MACHINE LEARNING MEMORY MANAGEMENT AND DISTRIBUTED RULE EVALUATION 审中-公开
    机器学习记忆管理和分布式规则评估

    公开(公告)号:US20140351185A1

    公开(公告)日:2014-11-27

    申请号:US14456950

    申请日:2014-08-11

    CPC classification number: G06N99/005

    Abstract: Aspects of the present disclosure relate to management of evaluated rule data sets. Specifically, a unreduced evaluated rule data set may contain a number of items to be compared or analyzed according to a number of rules, and may also contain the results of such analysis. An illustrative reduced evaluated data set can include the results of evaluated rules. When utilized in conjunction with an item data set and a rule data set, the information contained within the unreduced evaluated rule data set may be maintained. The reduce memory requirements of the reduced evaluated rule data set may facilitate storage of the reduced evaluated rule data set in faster to access memory, or may facilitate distributed computation of the reduced evaluated rule data set.

    Abstract translation: 本公开的方面涉及评估的规则数据集的管理。 具体而言,未减少的评估规则数据集可以包含根据规则数量进行比较或分析的多个项目,并且还可以包含这种分析的结果。 说明性的减少评估数据集可以包括评估规则的结果。 当与项目数据集和规则数据集合一起使用时,可以保持包含在未减少的评估规则数据集中的信息。 减少的评估规则数据集的减少存储器要求可以促进将减少的评估规则数据集存储在更快的存取存储器中,或者可以促进减少的评估规则数据集的分布式计算。

    Machine learning memory management and distributed rule evaluation
    7.
    发明授权
    Machine learning memory management and distributed rule evaluation 有权
    机器学习内存管理和分布式规则评估

    公开(公告)号:US09235814B2

    公开(公告)日:2016-01-12

    申请号:US14456950

    申请日:2014-08-11

    CPC classification number: G06N99/005

    Abstract: Aspects of the present disclosure relate to management of evaluated rule data sets. Specifically, a unreduced evaluated rule data set may contain a number of items to be compared or analyzed according to a number of rules, and may also contain the results of such analysis. An illustrative reduced evaluated data set can include the results of evaluated rules. When utilized in conjunction with an item data set and a rule data set, the information contained within the unreduced evaluated rule data set may be maintained. The reduce memory requirements of the reduced evaluated rule data set may facilitate storage of the reduced evaluated rule data set in faster to access memory, or may facilitate distributed computation of the reduced evaluated rule data set.

    Abstract translation: 本公开的方面涉及评估的规则数据集的管理。 具体而言,未减少的评估规则数据集可以包含根据规则数量进行比较或分析的多个项目,并且还可以包含这种分析的结果。 说明性的减少评估数据集可以包括评估规则的结果。 当与项目数据集和规则数据集合一起使用时,可以保持包含在未减少的评估规则数据集中的信息。 减少的评估规则数据集的减少存储器要求可以促进将减少的评估规则数据集存储在更快的存取存储器中,或者可以促进减少的评估规则数据集的分布式计算。

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