Super-Resolution in Structured Light Imaging
    13.
    发明申请

    公开(公告)号:US20200374502A1

    公开(公告)日:2020-11-26

    申请号:US16989946

    申请日:2020-08-11

    Abstract: A method of image processing in a structured light imaging device is provided that includes capturing a plurality of images of a scene into which a structured light pattern is projected by a projector in the structured light imaging device, extracting features in each of the captured images, finding feature matches between a reference image of the plurality of captured images and each of the other images in the plurality of captured images, rectifying each of the other images to align with the reference image, wherein each image of the other images is rectified based on feature matches between the image and the reference image, combining the rectified other images and the reference image using interpolation to generate a high resolution image, and generating a depth image using the high resolution image.

    Time-of-flight (TOF) assisted structured light imaging

    公开(公告)号:US10739463B2

    公开(公告)日:2020-08-11

    申请号:US16039114

    申请日:2018-07-18

    Abstract: A method for computing a depth map of a scene in a structured light imaging system including a time-of-flight (TOF) sensor and a projector is provided that includes capturing a plurality of high frequency phase-shifted structured light images of the scene using a camera in the structured light imaging system, generating, concurrently with the capturing of the plurality of high frequency phase-shifted structured light images, a time-of-flight (TOF) depth image of the scene using the TOF sensor, and computing the depth map from the plurality of high frequency phase-shifted structured light images wherein the TOF depth image is used for phase unwrapping.

    Image classification
    16.
    发明授权

    公开(公告)号:US10452960B1

    公开(公告)日:2019-10-22

    申请号:US16147966

    申请日:2018-10-01

    Abstract: An image classification system includes a convolutional neural network, a confidence predictor, and a fusion classifier. The convolutional neural network is configured to assign a plurality of probability values to each pixel of a first image of a scene and a second image of the scene. Each of the probability values corresponds to a different feature that the convolutional neural network is trained to identify. The confidence predictor is configured to assign a confidence value to each pixel of the first image and to each pixel of the second image. The confidence values correspond to a greatest of the probability values generated by the convolutional neural network for each pixel. The fusion classifier is configured to assign, to each pixel of the first image, a feature that corresponds to a higher of the confidence values assigned to the pixel of the first image and the second image.

    Adaptive structured light patterns
    17.
    发明授权

    公开(公告)号:US09769461B2

    公开(公告)日:2017-09-19

    申请号:US14322741

    申请日:2014-07-02

    CPC classification number: H04N13/271 H04N13/254

    Abstract: A method of depth map optimization using an adaptive structured light pattern is provided that includes capturing, by a camera in a structured light imaging device, a first image of a scene into which a pre-determined structured light pattern is projected by a projector in the structured light imaging device, generating a first disparity map based on the captured first image and the structured light pattern, adapting the structured light pattern based on the first disparity map to generate an adaptive pattern, wherein at least one region of the structured light pattern is replaced by a different pattern, capturing, by the camera, a second image of the scene into which the adaptive pattern is projected by the projector, generating a second disparity map based on the captured second image and the adaptive pattern, and generating a depth image using the second disparity map.

    Structured Light Depth Imaging Under Various Lighting Conditions
    18.
    发明申请
    Structured Light Depth Imaging Under Various Lighting Conditions 审中-公开
    各种照明条件下的结构光深度成像

    公开(公告)号:US20150003684A1

    公开(公告)日:2015-01-01

    申请号:US14296172

    申请日:2014-06-04

    Abstract: A method of image processing in a structured light imaging system is provided that includes receiving a captured image of a scene, wherein the captured image is captured by a camera of a projector-camera pair, and wherein the captured image includes a binary pattern projected into the scene by the projector, applying a filter to the rectified captured image to generate a local threshold image, wherein the local threshold image includes a local threshold value for each pixel in the rectified captured image, and extracting a binary image from the rectified captured image wherein a value of each location in the binary image is determined based on a comparison of a value of a pixel in a corresponding location in the rectified captured image to a local threshold value in a corresponding location in the local threshold image.

    Abstract translation: 提供了一种结构化光成像系统中的图像处理方法,包括接收场景的拍摄图像,其中所述拍摄图像由投影仪 - 照相机对的相机拍摄,并且其中所述拍摄图像包括投影到 通过投影仪的场景,对经整流的拍摄图像应用滤波器以产生局部阈值图像,其中所述局部阈值图像包括经整流的拍摄图像中的每个像素的局部阈值,并且从经整流的捕获图像中提取二进制图像 其中,基于将所述经整流的拍摄图像中的相应位置中的像素的值与所述局部阈值图像中的对应位置中的本地阈值的比较来确定所述二值图像中的每个位置的值。

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