EFFICIENT VISION PERCEPTION
    1.
    发明申请

    公开(公告)号:WO2023059962A1

    公开(公告)日:2023-04-13

    申请号:PCT/US2022/075542

    申请日:2022-08-26

    Abstract: Systems and techniques are provided for vision perception processing. An example method can include determining an attention demand score or characteristic per region of a frame from a sequence of frames; generating attention votes per region of the frame based on the attention demand score or characteristic per region, the attention votes per region providing attention demands and/or attention requests; determining an attention score or characteristic per region of the frame based on a number of attention votes from one or more computer vision functions; based on the attention score or characteristic per region of the frame, selecting one or more regions of the frame for processing using a neural network; and detecting or tracking one or more objects in the one or more regions of the frame based on processing of the one or more regions using the neural network.

    FOCUSED COMPUTER DETECTION OF OBJECTS IN IMAGES

    公开(公告)号:WO2023003646A1

    公开(公告)日:2023-01-26

    申请号:PCT/US2022/032588

    申请日:2022-06-08

    Abstract: To improve the accuracy and efficiency of object detection through computer digital image analysis, the detection of some objects can inform the sub-portion of the digital image to which subsequent computer digital image analysis is directed to detect other objects. In such a manner object detection can be made more efficient by limiting the image area of a digital image that is analyzed. Such efficiencies can represent both computational efficiencies and communicational efficiencies arising due to the smaller quantity of digital image data that is analyzed. Additionally, the detection of some objects can render the detection of other objects more accurate by adjusting confidence thresholds based on the detection of those related objects. Relationships between objects can be utilized to inform both the image area on which subsequent object detection is performed and the confidence level of such subsequent object detection.

    METHOD OF TRANSFORMING TEXTUAL ARCHITECTURAL DATA INTO INSTRUCTIONS FOR ARCHITECTURAL CAD SOFTWARE

    公开(公告)号:WO2022250740A1

    公开(公告)日:2022-12-01

    申请号:PCT/US2021/071251

    申请日:2021-08-23

    Abstract: A method for generating computer-readable instructions to automatically generate a three-dimensional architectural model Including: receiving a human-readable text file comprising a description of functional elements of a structure, parsing the text file to identify keywords comprised by the text file, generating a plurality of datasets responsive to the key words; generating instructions to create level objects responsive to the datasets, instructions to create floor objects responsive to the datasets and the level objects, instructions to create exterior wall objects responsive to the plurality of datasets and the one or more level objects, instructions to create interior wall objects responsive to the and level objects, instructions to create room objects responsive to the datasets, level objects, exterior wall objects, and interior wall objects, and providing the instructions to architectural modeling software.

    CHANGE DETECTION AND CHARACTERIZATION OF ASSETS

    公开(公告)号:WO2022236277A1

    公开(公告)日:2022-11-10

    申请号:PCT/US2022/072101

    申请日:2022-05-04

    Abstract: A method for determining a change in an asset and/or a characterization of an asset is provided. In an embodiment, the method can include receiving first data characterizing a target site including one or more assets. The method can also include generating a three-dimensional model of the target site based on the first data. The method can further include registering the first data with the three-dimensional model. The method can also include generating at least one three-dimensional projection onto at least one asset of the one or more assets included in the first data. The method can further include determining second data characterizing the at least one asset based on the at least on three-dimensional projection and providing the second data. In some embodiments, the method can be performed by systems or stored as instructions on computer readable mediums described herein.

    OBJECT COUNTING SYSTEM FOR HIGH VOLUME TRAFFIC

    公开(公告)号:WO2022198190A1

    公开(公告)日:2022-09-22

    申请号:PCT/US2022/071129

    申请日:2022-03-14

    Abstract: A system may be configured to perform object counting in high volume traffic. In some aspects, the system may detect a candidate object within the region of interest in a current video frame, and determine that the candidate object is a detected object based at least in part on comparing an attribute value of the candidate object to historic attribute information determined during a plurality of previous video frames. Further, the system may determine track information based on the detected object and determine an object count representing a number of the objects that have entered the region of interest and/or a number of the objects that have exited the region of interest.

    OBJECT COUNTING SYSTEM FOR HIGH VOLUME TRAFFIC

    公开(公告)号:WO2022198185A1

    公开(公告)日:2022-09-22

    申请号:PCT/US2022/071124

    申请日:2022-03-14

    Abstract: A system may be configured to perform object counting in high volume traffic. In some aspects, the system may determine object detection information defining an absence of an object within the region of interest in a current video frame, and determine that a location associated with the object is within a placeholder-eligible area within the region of interest based on first tracker information determined in a previous video frame. Further, the system may determine second tracker information including a bounding representation for the object based at least in part on the location and object detection information, and determine, based on the second tracker information, an object count representing a number of the objects that have entered the region of interest and/or a number of the objects that have exited the region of interest.

    基于深度卷积神经网络的沉底油声呐探测图像识别方法

    公开(公告)号:WO2021243743A1

    公开(公告)日:2021-12-09

    申请号:PCT/CN2020/095549

    申请日:2020-06-11

    Abstract: 本发明涉及沉底油探测技术领域,具体涉及基于深度卷积神经网络的沉底油声呐探测图像识别方法。包含声呐探测图像预处理模块和深度卷积神经网络沉底油目标识别模块。本发明将深度卷积神经网络算法引入沉底油探测与识别,解决沉底油目标识别自动化、泄漏位置定位自动化、估算沉底油污染面积自动化等关键难题,为海洋溢油事故应急决策及处置提供依据,提高我国沉底油探测与识别技术的水平,为国家海洋安全和石油安全提供技术支持,具有重要的工程意义和应用价值。

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