Light field image rendering method and system for creating see-through effects

    公开(公告)号:US11615547B2

    公开(公告)日:2023-03-28

    申请号:US16877471

    申请日:2020-05-18

    Abstract: A light field image processing method is disclosed for removing occluding foreground and blurring uninterested objects, by differentiating objects located at different depths of field and objects belonging to distinct categories, to create see-through effects. In various embodiments, the image processing method may blur a background object behind a specified object of interest. The image processing method may also at least partially remove from the rendered image any occluding object that may prevent a viewer from viewing the object of interest. The image processing method may further blur areas of the rendered image that represent an object in the light field other than the object of interest. The method includes steps of constructing a light field weight function comprising a depth component and a semantic component, where the weight function assigns a ray in the light field with a weight; and conducting light field rendering using the weight function.

    Face region detection based light field video compression

    公开(公告)号:US11153606B2

    公开(公告)日:2021-10-19

    申请号:US16891622

    申请日:2020-06-03

    Inventor: Zhiru Shi Qiang Hu

    Abstract: A method of perceptual video coding based on face detection is provided. The method includes calculating a bit allocation scheme for coding a light field video based on a saliency map of the face, calculating an LCU level Lagrange multiplier for coding a light field video based on a saliency map of the face and calculating an LCU level quantization parameter for coding a light field video based on a saliency map of the face.

    System and method for extracting planar surface from depth image

    公开(公告)号:US11861840B2

    公开(公告)日:2024-01-02

    申请号:US17219555

    申请日:2021-03-31

    CPC classification number: G06T7/11 G06T7/162 G06T7/187 G06T7/50 G06T2207/10028

    Abstract: According to some embodiments, an imaging processing method for extracting a plurality of planar surfaces from a depth map includes computing a depth change indication map (DCI) from a depth map in accordance with a smoothness threshold. The imaging processing method further includes recursively extracting a plurality of planar region from the depth map, wherein the size of each planar region is dynamically adjusted according to the DCI. The imaging processing method further includes clustering the extracted planar regions into a plurality of groups in accordance with a distance function; and growing each group to generate pixel-wise segmentation results and inlier points statistics simultaneously.

    FAST AND DETERMINISTIC ALGORITHM FOR CONSENSUS SET MAXIMIZATION

    公开(公告)号:US20210073443A1

    公开(公告)日:2021-03-11

    申请号:US17099445

    申请日:2020-11-16

    Abstract: A method for approximately solving a consensus set maximization (“CSM”) problem for a dataset is disclosed. The method comprises relaxing a maximum fitting residual constraint in the CSM problem to an average error bounded constraint; defining a plurality of decision problems related to the relaxed CSM problem; solving each decision problem by defining an optimization problem; and selecting a consensus size for the CSM problem based on solutions to the decision problems.

    Light field based reflection removal

    公开(公告)号:US11880964B2

    公开(公告)日:2024-01-23

    申请号:US17074123

    申请日:2020-10-19

    Abstract: A method of processing light field images for separating a transmitted layer from a reflection layer. The method comprises capturing a plurality of views at a plurality of viewpoints with different polarization angles; obtaining an initial disparity estimation for a first view using SIFT-flow, and warping the first view to a reference view; optimizing an objective function comprising a transmitted layer and a secondary layer using an Augmented Lagrange Multiplier (ALM) with Alternating Direction Minimizing (ADM) strategy; updating the disparity estimation for the first view; repeating the steps of optimizing the objective function and updating the disparity estimation until the change in the objective function between two consecutive iterations is below a threshold; and separating the transmitted layer and the secondary layer using the disparity estimation for the first view.

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