METHOD AND SYSTEM FOR GENERATING A TWO-DIMENSIONAL AND A THREE-DIMENSIONAL IMAGE STREAM

    公开(公告)号:US20200380708A1

    公开(公告)日:2020-12-03

    申请号:US16425764

    申请日:2019-05-29

    Abstract: Methods, systems, and techniques for generating two-dimensional (2D) and three-dimensional (3D) images and image streams. The images and image streams may be generated using active stereo cameras projecting at least one illumination pattern, or by using a structured light camera and a pair of different illumination patterns of which at least one is a structured light illumination pattern. When using an active stereo camera, a 3D image may be generated by performing a stereoscopic combination of a first set of images (depicting a first illumination pattern) and a 2D image may be generated using a second set of images (optionally depicting a second illumination pattern). When using a structured light camera, a 3D image may be generated based on a first image that depicts a structured light illumination pattern, and a 2D image may be generated from the first image and a second image that depicts a different illumination pattern.

    METHOD AND SYSTEM FOR GENERATING A TWO-DIMENSIONAL AND A THREE-DIMENSIONAL IMAGE STREAM

    公开(公告)号:US20200382765A1

    公开(公告)日:2020-12-03

    申请号:US16435042

    申请日:2019-06-07

    Abstract: Methods, systems, and techniques for generating two-dimensional (2D) and three-dimensional (3D) images and image streams. The images and image streams may be generated using active stereo cameras projecting at least one illumination pattern, or by using a structured light camera and a pair of different illumination patterns of which at least one is a structured light illumination pattern. When using an active stereo camera, a 3D image may be generated by performing a stereoscopic combination of a first set of images (depicting a first illumination pattern) and a 2D image may be generated using a second set of images (optionally depicting a second illumination pattern). When using a structured light camera, a 3D image may be generated based on a first image that depicts a structured light illumination pattern, and a 2D image may be generated from the first image and a second image that depicts a different illumination pattern.

    METHOD AND SYSTEM FOR OBJECT CLASSIFICATION USING VISIBLE AND INVISIBLE LIGHT IMAGES

    公开(公告)号:US20190258885A1

    公开(公告)日:2019-08-22

    申请号:US16279975

    申请日:2019-02-19

    Abstract: Methods, systems, and techniques for classifying and/or detecting objects using visible and invisible light images. A visible light image and an invisible light image are received at a convolutional neural network (CNN). The visible light image depicts a region-of-interest imaged using visible light. The invisible light image depicts at least a portion of the region-of-interest imaged using invisible light, and at least one of the images depicts an object-of-interest within the portion of the region-of-interest shared between the images. The CNN then classifies and/or detects the object-of-interest using the images. The CNN may be trained to perform this classification and/or detection using pairs of visible and invisible light training images.

    METHOD AND SYSTEM FOR ENHANCING USE OF TWO-DIMENSIONAL VIDEO ANALYTICS BY USING DEPTH DATA

    公开(公告)号:US20210051312A1

    公开(公告)日:2021-02-18

    申请号:US16539888

    申请日:2019-08-13

    Abstract: Methods, systems, and techniques for enhancing use of two-dimensional (2D) video analytics by using depth data. Two-dimensional image data representing an image comprising a first object is obtained, as well as depth data of a portion of the image that includes the first object. The depth data indicates a depth of the first object. An initial 2D classification of the portion of the image is generated using the 2D image data without using the depth data. The initial 2D classification is stored as an approved 2D classification when the initial 2D classification is determined consistent with the depth data. Additionally or alternatively, a confidence level of the initial 2D classification may be adjusted depending on whether the initial 2D classification is determined to be consistent with the depth data, or the depth data may be used with the 2D image data for classification.

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