Automatic large-scale imaging device diagnostics

    公开(公告)号:US10579906B1

    公开(公告)日:2020-03-03

    申请号:US16048909

    申请日:2018-07-30

    Abstract: Diagnostics may be performed on imaging devices such as digital cameras that are provided in large numbers, or mounted in arrays or networks, by providing imaging data captured from such devices to a machine learning system or classifier that has been trained to recognize anomalies based on imaging data. The machine learning system or classifier may be trained using a training set of imaging data previously captured by one or more imaging devices that has been labeled with regard to whether such imaging devices encountered any anomalies when the imaging data was captured, and if so, which anomalies were encountered. Additionally, a perceptual score which represents the quality of a given image or imaging data may be calculated and used to rank or define the image or imaging data in terms of quality, or determine whether the image or imaging data is suitable for its intended purpose.

    Obfuscating portions of video data

    公开(公告)号:US11600094B1

    公开(公告)日:2023-03-07

    申请号:US17204228

    申请日:2021-03-17

    Abstract: Described are systems and methods for detecting objects using calibrated imaging devices and obfuscating, in real-time or near real time, portions of the video data to protect the privacy of operators represented in the video data. For example, a position of an operator within a fulfillment center may be determined or tracked in video data and the pixels representative of that operator may be obfuscated using pixilation and/or other techniques so that a reviewing agent that is viewing the video data cannot determine the identity of the operator. Such obfuscation may be performed in real-time or near real-time using automated processing. In addition, only portions of the video data may be obfuscated so that events (e.g., item picks, item place) and/or other objects represented in the video data are still viewable to the reviewing agent.

    Obfuscating portions of video data

    公开(公告)号:US10956726B1

    公开(公告)日:2021-03-23

    申请号:US15839399

    申请日:2017-12-12

    Abstract: Described are systems and methods for detecting objects using calibrated imaging devices and obfuscating, in real-time or near real time, portions of the video data to protect the privacy of operators represented in the video data. For example, a position of an operator within a fulfillment center may be determined or tracked in video data and the pixels representative of that operator may be obfuscated using pixilation and/or other techniques so that a reviewing agent that is viewing the video data cannot determine the identity of the operator. Such obfuscation may be performed in real-time or near real-time using automated processing. In addition, only portions of the video data may be obfuscated so that events (e.g., item picks, item place) and/or other objects represented in the video data are still viewable to the reviewing agent.

    Visual content analysis system with semantic framework

    公开(公告)号:US10282672B1

    公开(公告)日:2019-05-07

    申请号:US14316031

    申请日:2014-06-26

    Abstract: A processing device determines a plurality of visual concepts for visual data based on at least one of visual entities in the visual data or feature-level attributes in the visual data, wherein the visual entities are based on the feature-level attributes, and wherein each of the plurality of visual concepts comprises a subject visual entity related to an object visual entity by a predicate. The processing device further determines one or more visual semantics for the visual data based on the plurality of visual concepts, wherein the one or more visual semantics define relationships between the plurality of visual concepts.

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