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公开(公告)号：WO2021037765A1
公开(公告)日：2021-03-04
申请号：PCT/EP2020/073568
申请日：2020-08-21
Applicant: FIVE AI LIMITED
Inventor： REDFORD, John , KALTWANG, Sebastian , SAMANGOOEI, Sina , ROGERS, Blain
IPC: G06N3/00 , G06N3/04 , G06N3/08 , G06N7/00 , G06K9/00 , G05D1/00 , 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 first 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, in order to compute a first time series of perception outputs. A second time series of perception outputs is computed using a second PSPM for modelling a second perception slice of the runtime stack, the first PSPM learned from data of a first sensor modality of the perception slice and the time series, and the second PSPM learned independently thereof from data of a second sensor modality of the second perception slice and the second time series.
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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
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.
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公开(公告)号：WO2019234175A1
公开(公告)日：2019-12-12
申请号：PCT/EP2019/064826
申请日：2019-06-06
Applicant: FIVE AI LIMITED
Inventor： REDFORD, John , SAMANGOOEI, Sina
Abstract: In one aspect, hierarchical image segmentation is applied to an image formed of a plurality of pixels, by classifying the pixels according to a hierarchical classification scheme, in which at least some of those pixels are classified by a parent level classifier in relation to a set of parent classes, each of which is associated with a subset of child classes, and each of those pixels is also classified by at least one child level classifier in relation to one of the subsets of child classes, wherein each of the parent classes corresponds to a category of visible structure, and each of the subset of child classes associated with it corresponds to a different type of visible structure within that category.
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公开(公告)号：WO2022157205A1
公开(公告)日：2022-07-28
申请号：PCT/EP2022/051151
申请日：2022-01-19
Applicant: FIVE AI LIMITED
Inventor： REDFORD, John , SAMANGOOEI, Sina , SHARMA, Anuj , DOKANIA, Puneet
Abstract: A computer implemented method of training an encoder to extract features from sensor data comprises generating a plurality of training examples, each training example comprising at least two data representations of a set of sensor data, the at least two data representations related by a transformation parameterized by at least one numerical transformation value; and training the encoder based on a self-supervised regression loss function applied to the training examples. The encoder extracts respective features from the at least two data representations of each training example, and at least one numerical output value is computed from the extracted features. The self-supervised regression loss function encourages the at least one numerical output value to match the at least one numerical transformation value parameterizing the transformation.
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公开(公告)号：WO2022157161A1
公开(公告)日：2022-07-28
申请号：PCT/EP2022/051048
申请日：2022-01-18
Applicant: FIVE AI LIMITED
Inventor： LAWSON, Andrew , PICKUP, David , SAMANGOOEI, Sina , REDFORD, John
Abstract: A computer-implemented method of computer-implemented method of perceiving structure in a point cloud comprises: applying clustering to the point cloud, and thereby identifying at least one moving object cluster within the point cloud, the point cloud comprising time-stamped points captured over a non-zero accumulation window; determining a motion model for the moving object cluster, by fitting one or more parameters of the motion model to the time-stamped points of that cluster; using the motion model to transform the time-stamped points of the moving object cluster to a common reference time; and applying a perception component to the transformed points of the moving object cluster to extract information about structure exhibited in the transformed points.
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Patent Agency Ranking
公开(公告)号：WO2022038260A1
公开(公告)日：2022-02-24
申请号：PCT/EP2021/073128
申请日：2021-08-20
Applicant: FIVE AI LIMITED
Inventor： CHAN, Ying , SAMANGOOEI, Sina , REDFORD, John
Abstract: A method of annotating known objects in road images captured from a sensor-equipped vehicle, the method implemented in an annotation system and comprising: receiving at the annotation system a road image containing a view of a known object; receiving ego localization data, as computed in a map frame of reference, via localization applied to sensor data captured by the sensor-equipped vehicle, the ego localization data indicating an image capture pose of the road image in the map frame of reference; determining, from a predetermined road map, an object location of the known object in the map frame of reference, the predetermined road map representing a road layout the map frame of reference, wherein the known object is one of: a piece of road structure, and an object on or adjacent a road; computing, in an image plane defined by the image capture pose, an object projection, by projecting an object model of the known object from the object location into the image plane; and storing, in an image database, image data of the road image, in association with annotation data of the object projection for annotating the image data with a location of the known object in the image plane.
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公开(公告)号：WO2021013790A1
公开(公告)日：2021-01-28
申请号：PCT/EP2020/070442
申请日：2020-07-20
Applicant: FIVE AI LIMITED
Inventor： CHANDLER, Robert , WESTMACOTT, Tom , SAMANGOOEI, Sina , FULLER, Ben , CRUICKSHANK, Jamie , FROOM, William , GOLODETZ, Stuart , CAVALARI, Tommasso
Abstract: A computer- implemented method of creating 2D annotation data for annotating one or more perception inputs comprises: receiving at the annotation computer system at least one captured frame comprising a set of 3D structure points, in which at least a portion of a structure component is captured; computing a reference position for the structure component within the frame; generating a 3D model for the structure component by selectively extracting 3D structure points of the frame based on the reference position; computing a projection of the 3D model into an image plane; and storing 2D annotation data of the computed projection in persistent computer storage for annotating the structure component within the image plane.
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公开(公告)号：WO2022157202A1
公开(公告)日：2022-07-28
申请号：PCT/EP2022/051147
申请日：2022-01-19
Applicant: FIVE AI LIMITED
Inventor： REDFORD, John , SAMANGOOEI, Sina , SHARMA, Anuj , DOKANIA, Puneet
IPC: G01S13/931 , G01S7/41 , G06K9/62 , G06N3/08 , G01S7/417 , G06N3/0454 , G06V10/255 , G06V10/454 , G06V10/774 , G06V20/58 , G06V20/64
Abstract: A computer implemented method of training an encoder to extract features from sensor data comprises training a machine learning (ML) system based on a self-supervised loss function applied to a training set, the ML system comprising the encoder. The training set comprises sets of real sensor data and corresponding sets of synthetic sensor data. The encoder extracts features from each set of real and synthetic sensor data, and the self-supervised loss function encourages the ML system to associate each set of real sensor data with its corresponding set of synthetic sensor data based on their respective features.
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公开(公告)号：WO2022038259A1
公开(公告)日：2022-02-24
申请号：PCT/EP2021/073126
申请日：2021-08-20
Applicant: FIVE AI LIMITED
Inventor： CHAN, Ying , SAMANGOOEI, Sina , REDFORD, John
IPC: G06K9/00
Abstract: A computer-implemented method of processing images for extracting information about known objects comprises the steps of receiving an image containing a view of a known object at a scale dependent on an object distance of the known object from an image capture location of the image; determining, from a world model representing one or more known objects in the vicinity of the image capture location, an object location of the known object, the object location and the image capture location defined in a world frame of reference; and based on the image capture location and the object location in the world frame of reference, applying image scaling to the image, to extract a rescaled image containing a rescaled view of the known object at a scale that is substantially independent of the object distance from the image capture location.
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公开(公告)号：WO2023021208A1
公开(公告)日：2023-02-23
申请号：PCT/EP2022/073253
申请日：2022-08-19
Applicant: FIVE AI LIMITED
Inventor： SADEGHI, Jonathan , ROGERS, Blaine , GUNN, James , SAUNDERS, Thomas , SAMANGOOEI, Sina , DOKANIA, Puneet Kumar , REDFORD, John
IPC: G06F11/36 , B60W40/00 , G05D1/00 , G06F30/00 , G06F11/34 , G06F11/3447 , G06F11/3664 , G06F11/3696 , G06F30/15 , G06F30/27
Abstract: Performance of a substitute upstream processing component is tested, in order to determine whether that performance is sufficient to support a downstream processing component, within an autonomous driving system, in place of an existing upstream processing component. The existing upstream processing component and the substitute upstream processing component are mutually interchangeable in so far as they provide the same form of outputs interpretable by the downstream processing component, such that either upstream processing component may be used without modification to the downstream processing component. A direct or indirect metric-based comparison is formulated in terms of the resulting performance of the downstream processing component.
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