中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

6 records (took 0.011 seconds)

    DEPTH EXTRACTION
    1.
    发明申请
    DEPTH EXTRACTION 审中-公开

    公开(公告)号：WO2020188120A1

    公开(公告)日：2020-09-24

    申请号：PCT/EP2020/058036

    申请日：2020-03-23

    Applicant: FIVE AI LIMITED

    Inventor： SADEGHI, Jonathan ,  ELSON, Torran

    IPC: G06T7/593

    Abstract: A computer-implemented method of training a depth uncertainty estimator comprises receiving, at a training computer system, a set of training examples, each training example comprising (i) a stereo image pair and (ii) an estimated disparity map computed from at least one image of the stereo image pair by a depth estimator. The training computer system executes a training process to learn one or more uncertainty estimation parameters of a perturbation function, the uncertainty estimation parameters for estimating uncertainty in disparity maps computed by the depth estimator. The training process is performed by sampling a likelihood function based on the training examples and the perturbation function, thereby obtaining a set of sampled values for learning the one or more uncertainty estimation parameters. The likelihood function measures similarity between one image of each training example and a reconstructed image computed by transforming the other image of that training example based on a possible true disparity map derived from the estimated disparity map of that training example and the perturbation function.

    PERFORMANCE TESTING FOR ROBOTIC SYSTEMS
    2.
    发明申请
    PERFORMANCE TESTING FOR ROBOTIC SYSTEMS 审中-公开

    公开(公告)号：WO2022038257A1

    公开(公告)日：2022-02-24

    申请号：PCT/EP2021/073124

    申请日：2021-08-20

    Applicant: FIVE AI LIMITED

    Inventor： REDFORD, John ,  SAMANGOOEI, Sina ,  SADEGHI, Jonathan

    IPC: G06N3/04 ,  G06N3/00 ,  G06N3/08 ,  G06N20/00 ,  G06N7/00

    Abstract: A computer-implemented method of modelling a perception system, the perception system configured to receive sensor data and interpret the sensor data to generate actual perception outputs, comprises: receiving a plurality of input samples, wherein each input sample comprises sensor data and is associated with one or more training perception ground truths pertaining to one or more ground truth objects; providing the sensor data of each input sample to the perception system to be modelled, wherein the perception system interprets the sensor data, in order to generate one or more actual perception outputs for the input sample; and training a function approximator to model the perception system by: for each input sample, inputting the training perception ground truths to the function approximator, wherein the function approximator computes one or more predicted perception values by processing the training perception ground truths but not the sensor data from which the actual perception outputs are generated, and adapting parameters of the function approximator, so as to match the corresponding predicted perception values to the actual perception outputs for each of the input samples; wherein the training perception ground truths associated with at least one of the input samples comprise first and second training perception ground truths pertaining to first and second ground truth objects respectively, wherein at least one of the corresponding predicted perception values is computed from both the first and second training perception ground truths for modelling correlations between the first and second ground truth objects.

    PERFORMANCE TESTING FOR ROBOTIC SYSTEMS
    3.
    发明申请
    PERFORMANCE TESTING FOR ROBOTIC SYSTEMS 审中-公开

    公开(公告)号：WO2021037766A1

    公开(公告)日：2021-03-04

    申请号：PCT/EP2020/073569

    申请日：2020-08-21

    Applicant: FIVE AI LIMITED

    Inventor： REDFORD, John ,  SADEGHI, Jonathan

    IPC: G06N3/00 ,  G05D1/00 ,  G06K9/00 ,  G06N3/04 ,  G06N7/00 ,  G06N3/08 ,  G06T15/06 ,  G06N5/00 ,  G06N5/02 ,  G06N20/00

    Abstract: Herein, a "perception statistical performance model" (PSPM) for modelling a perception slice of a runtime stack for an autonomous vehicle or other robotic system may be used e.g. for safety/performance testing. A PSPM is configured to: receive a computed perception ground truth; determine from the perception ground truth, based on a set of learned parameters, a probabilistic perception uncertainty distribution, the parameters learned from a set of actual perception outputs generated using the perception slice to be modelled. The modelled perception slice includes an online error estimator, and the computer system is configured to use the PSPM to obtain a predicted online error estimate for the perception output in response to the perception ground truth. This recognizes that online perception error estimates may, themselves, be subject to error.

    PERCEPTION UNCERTAINTY
    6.
    发明申请
    PERCEPTION UNCERTAINTY 审中-公开

    公开(公告)号：WO2020188121A1

    公开(公告)日：2020-09-24

    申请号：PCT/EP2020/058038

    申请日：2020-03-23

    Applicant: FIVE AI LIMITED

    Inventor： REDFORD, John ,  KALTWANG, Sebastian ,  SADEGHI, Jonathan ,  ELSON, Torran

    IPC: G06T7/593

    Abstract: : A computer-implemented method of perceiving structure in an environment comprises steps of: receiving at least one structure observation input pertaining to the environment; processing the at least one structure observation input in a perception pipeline to compute a perception output; determining one or more uncertainty source inputs pertaining to the structure observation input; and determining for the perception output an associated uncertainty estimate by applying, to the one or more uncertainty source inputs, an uncertainty estimation function learned from statistical analysis of historical perception outputs.

Patent Agency Ranking