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    Method and system for camera-free light field video processing with all-optical neural network
    2.
    发明授权
    Method and system for camera-free light field video processing with all-optical neural network 有权

    公开(公告)号：US11514667B1

    公开(公告)日：2022-11-29

    申请号：US17704202

    申请日：2022-03-25

    申请人： Tsinghua University

    发明人： Lu Fang ,  Tiankuang Zhou ,  Siyuan Gu ,  Xiaoyun Yuan ,  Qionghai Dai

    IPC分类号： G06V10/82 ,  G06V10/774 ,  G06V10/145 ,  G06N3/067

    摘要： A method and an apparatus for camera-free light field video processing with all-optical neural network are disclosed. The method includes: mapping the light field video by a digital micro-mirror device (DMD) and an optical fiber coupler, a two-dimensional 2D spatial optical signal into a one-dimensional 1D input optical signal; realizing a multiply-accumulate computing model in a structure of all-optical recurrent neural network structure, and processing the 1D input signal to obtain the processed signal; and receiving the processed signal and outputting an electronic signal by a photodetector, or receiving the processed signal by a relay optical fiber for relay transmission of the processed signal. The method and system here realize light field video processing without the use of a camera and the whole system is all-optical, thus possessing the advantage in computing speed and energy-efficiency.

    3-DIMENSIONAL RECONSTRUCTION METHOD, 3-DIMENSIONAL RECONSTRUCTION DEVICE, AND STORAGE MEDIUM
    3.
    发明申请
    3-DIMENSIONAL RECONSTRUCTION METHOD, 3-DIMENSIONAL RECONSTRUCTION DEVICE, AND STORAGE MEDIUM 有权

    公开(公告)号：US20210110576A1

    公开(公告)日：2021-04-15

    申请号：US17036457

    申请日：2020-09-29

    申请人： TSINGHUA UNIVERSITY

    发明人： Lu Fang ,  Dawei Zhong ,  Qionghai Dai

    IPC分类号： G06T7/80 ,  G06T15/10 ,  G06T7/246

    摘要： The disclosure provides 3D reconstruction methods and devices. The method includes: obtaining data captured by the camera and data captured by the inertial measurement unit; obtaining a pose of the camera based on the data; obtaining an adjustment value of the pose of the camera and an adjustment value of bias of the inertial measurement unit; updating the pose of the camera based on the adjustment value of the pose of the camera; determining whether the adjustment value of bias of the inertial measurement unit is less than a preset value; in response to the adjustment value of bias of the inertial measurement unit being greater than or equal to the preset value, determining that a current loop for 3-dimensional reconstruction is an error loop; removing the error loop; and constructing a 3-dimensional model for surroundings of the camera based on the updated pose of the camera and remaining loops.

    Method and apparatus for camera-free light field imaging with optoelectronic intelligent computing
    4.
    发明授权
    Method and apparatus for camera-free light field imaging with optoelectronic intelligent computing 有权

    公开(公告)号：US11425292B1

    公开(公告)日：2022-08-23

    申请号：US17678759

    申请日：2022-02-23

    申请人： Tsinghua University

    发明人： Lu Fang ,  Yong Wang ,  Xiaoyun Yuan ,  Tiankuang Zhou ,  Qionghai Dai

    IPC分类号： G02F1/365 ,  H04N5/225 ,  G06N3/04 ,  G02F1/35

    摘要： A method and an apparatus for camera-free light field imaging with optoelectronic intelligent computing are provided. The method includes: obtaining an optical computing result by an optical computing module in response to receiving a light signal of an object to be imaged, in which the optical computing result includes light field imaging of the object to be imaged; computing by an electronic computing module the optical computing result to obtain an electronic computing result; and in response to determining based on the electronic computing result that cascading is required, forming a cascade structure by taking the electronic computing result at a previous level as an input of the optical computing module at a current level, and in response to determining that cascading is not required, outputting a final result.

    MATERIAL IDENTIFICATION METHOD AND DEVICE BASED ON LASER SPECKLE AND MODAL FUSION
    5.
    发明申请
    MATERIAL IDENTIFICATION METHOD AND DEVICE BASED ON LASER SPECKLE AND MODAL FUSION 有权

    公开(公告)号：US20210118123A1

    公开(公告)日：2021-04-22

    申请号：US17036475

    申请日：2020-09-29

    申请人： TSINGHUA UNIVERSITY

    发明人： Lu Fang ,  Mengqi Ji ,  Shi Mao ,  Qionghai Dai

    IPC分类号： G06T7/00 ,  G06T5/00 ,  G01N21/39 ,  G02B27/48 ,  G06K9/62

    摘要： The present disclosure provides a material identification method and a device based on laser speckle and modal fusion, an electronic device and a non-transitory computer readable storage medium. The method includes: performing data acquisition on an object by using a structured light camera to obtain a color modal image, a depth modal image and an infrared modal image; preprocessing the color modal image, the depth modal image and the infrared modal image; and inputting the color modal image, the depth modal image and the infrared modal image preprocessed into a preset depth neural network for training, to learn a material characteristic from a speckle structure and a coupling relation between color modal and depth modal, to generate a material classification model for classifying materials, and to generate a material prediction result in testing by the material classification model of the object.

    DYNAMIC SCENE THREE-DIMENSIONAL RECONSTRUCTION METHOD, APPARATUS AND SYSTEM, SERVER, AND MEDIUM
    6.
    发明申请
    DYNAMIC SCENE THREE-DIMENSIONAL RECONSTRUCTION METHOD, APPARATUS AND SYSTEM, SERVER, AND MEDIUM 有权

    公开(公告)号：US20210074012A1

    公开(公告)日：2021-03-11

    申请号：US16975242

    申请日：2019-04-23

    申请人： Tsinghua University

    发明人： Lu Fang ,  Mengqi Ji ,  Yebin Liu ,  Lan Xu ,  Wei Cheng ,  Qionghai Dai

    IPC分类号： G06T7/593 ,  G06T7/292 ,  G06T17/00 ,  G06K9/00 ,  B64C39/02

    摘要： Provided are a three-dimensional reconstruction method, apparatus and system of a dynamic scene, a server and a medium. The method includes: acquiring multiple continuous depth image sequences of the dynamic scene, where the multiple continuous depth image sequences are captured by an array of drones equipped with depth cameras; fusing the multiple continuous depth image sequences to establish a three-dimensional reconstruction model of the dynamic scene; obtaining target observation points of the array of drones through calculation according to the three-dimensional reconstruction model and current poses of the array of drones; and instructing the array of drones to move to the target observation points to capture, and updating the three-dimensional reconstruction model according to multiple continuous depth image sequences captured by the array of drones at the target observation points.