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公开(公告)号：US20210070322A1
公开(公告)日：2021-03-11
申请号：US17011854
申请日：2020-09-03
Applicant: Humanising Autonomy Limited
Inventor： Dominic Noy , Matthew Cameron Angus , James Over Everard , Wassim El Youssoufi , Raunaq Bose , Leslie Cees Nooteboom , Maya Audrey Lara Pindeus
Abstract: A device performs operations including determining a probability that a vulnerable road user (VRU) will continue on a current path (e.g., in connection with controlling an autonomous vehicle). The device receives an image depicting a vulnerable road user (VRU). The device inputs at least a portion of the image into a model, and receives, as output from the model, a plurality of probabilities describing the VRU, each of the probabilities corresponding to a probability that the VRU is in a given state. The device determines, based on at least some of the plurality of probabilities, a probability that the VRU will exhibit a behavior, and outputs the probability that the VRU will exhibit the behavior to a control system.
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公开(公告)号：US10913454B2
公开(公告)日：2021-02-09
申请号：US16219566
申请日：2018-12-13
Applicant: Humanising Autonomy Limited
Abstract: A system and a method are disclosed for determining intent of a human based on human pose. In some embodiments, a processor obtains a plurality of sequential images from a video feed, and determines respective keypoints corresponding a human in each respective image of the plurality of sequential images. The processor aggregates the respective keypoints for each respective image into a pose of the human and transmits a query to a database to find a template that matches the pose by comparing the pose to a plurality of templates poses that translate candidate poses to intent, each template corresponding to an associated intent. The processor receives a reply message from the database that either indicates an intent of the human based on a matching template, or an inability to locate the matching template, and, in response to the reply message indicating the intent of the human, outputs the intent.
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Patent Agency Ranking
公开(公告)号：US20240029467A1
公开(公告)日：2024-01-25
申请号：US18479797
申请日：2023-10-02
Applicant: Humanising Autonomy Limited
Inventor： Dominic Noy , Matthew Cameron Angus , James Over Everard , Wassim El Youssoufi , Raunaq Bose , Leslie Cees Nooteboom , Maya Audrey Lara Pindeus
IPC: G06V40/10 , B60W60/00 , G06N3/08 , G06V20/58 , G06F18/20 , G06N7/01 , G06V10/764 , G06V10/82 , G06V20/56
CPC classification number: G06V40/103 , B60W60/0027 , G06N3/08 , G06V20/58 , G06F18/295 , G06N7/01 , G06V10/764 , G06V10/82 , G06V20/56 , B60W2554/4046
Abstract: A device performs operations including determining a probability that a vulnerable road user (VRU) will continue on a current path (e.g., in connection with controlling an autonomous vehicle). The device receives an image depicting a vulnerable road user (VRU). The device inputs at least a portion of the image into a model, and receives, as output from the model, a plurality of probabilities describing the VRU, each of the probabilities corresponding to a probability that the VRU is in a given state. The device determines, based on at least some of the plurality of probabilities, a probability that the VRU will exhibit a behavior, and outputs the probability that the VRU will exhibit the behavior to a control system.
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公开(公告)号：US11783710B2
公开(公告)日：2023-10-10
申请号：US17357446
申请日：2021-06-24
Applicant: Humanising Autonomy Limited
Inventor： Raunaq Bose , Leslie Cees Nooteboom , Maya Audrey Lara Pindeus
IPC: G08B23/00 , G08G1/16 , G06N20/00 , G06V20/52 , B60W40/09 , B60W50/14 , G08G1/017 , G06V10/80 , G06V20/40 , G06V20/58 , G06V40/20 , B60W40/08
CPC classification number: G08G1/166 , B60W40/09 , B60W50/14 , G06N20/00 , G06V10/809 , G06V20/46 , G06V20/52 , G06V20/58 , G06V40/20 , G08G1/0175 , B60W2040/0863 , B60W2540/26 , B60W2540/30 , G06V2201/07 , G06V2201/08
Abstract: The systems and methods disclosed herein provide a risk prediction system that uses trained machine learning models to make predictions that a VRU will take a particular action. The system first receives, in a video stream, an image depicting a VRU operating a micro-mobility vehicle and extract the depictions from the image. The extraction process may be determined by bounding box classifiers trained to identify various VRUs and micro-mobility vehicles. The system feeds the extracted depictions to machine learning models and receives, as an output, risk profiles for the VRU and the micro-mobility vehicle. The risk profile may include data associated with the VRU/micro-mobility vehicle determined based on classifications of the VRU and the micro-mobility vehicles. The system may then generate a prediction that the VRU operating the micro-mobility vehicle will take a particular action based on the risk profile.
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公开(公告)号：US20230048304A1
公开(公告)日：2023-02-16
申请号：US17402418
申请日：2021-08-13
Applicant: Humanising Autonomy Limited
Inventor： Leslie Cees Nooteboom , Raunaq Bose , Maya Audrey Lara Pindeus , Dominic Noy , James Over Everard , Yazhini Chitra Pradeep
Abstract: A behavior prediction system predicts human behaviors based on environment-aware information such as camera movement data and geospatial data. The system receives sensor data of a vehicle reflecting a state of the vehicle at a given time and a given location. The system determines a field of concern in images of a video stream and determines one or more portions of images of the video stream that correspond to the field of concern. The system may apply different levels of processing powers to objects in the images based on whether an object is in the field of concern. The system then generates features of objects and identify VRUs from the objects of the video stream. For the identified VRUs, the system inputs a representation of the VRUs and the features into a machine learning model, and outputs from the machine learning model a behavioral risk assessment of the VRUs.
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公开(公告)号：US20210403003A1
公开(公告)日：2021-12-30
申请号：US17357446
申请日：2021-06-24
Applicant: Humanising Autonomy Limited
Inventor： Raunaq Bose , Leslie Cees Nooteboom , Maya Audrey Lara Pindeus
Abstract: The systems and methods disclosed herein provide a risk prediction system that uses trained machine learning models to make predictions that a VRU will take a particular action. The system first receives, in a video stream, an image depicting a VRU operating a micro-mobility vehicle and extract the depictions from the image. The extraction process may be determined by bounding box classifiers trained to identify various VRUs and micro-mobility vehicles. The system feeds the extracted depictions to machine learning models and receives, as an output, risk profiles for the VRU and the micro-mobility vehicle. The risk profile may include data associated with the VRU/micro-mobility vehicle determined based on classifications of the VRU and the micro-mobility vehicles. The system may then generate a prediction that the VRU operating the micro-mobility vehicle will take a particular action based on the risk profile.
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公开(公告)号：US20190176820A1
公开(公告)日：2019-06-13
申请号：US16219566
申请日：2018-12-13
Applicant: Humanising Autonomy Limited
Inventor： Maya Audrey Lara Pindeus , Raunaq Bose , Leslie Cees Nooteboom
IPC: B60W30/095 , B60W30/09 , G06K9/00 , G06F16/29
Abstract: A system and a method are disclosed for determining intent of a human based on human pose. In some embodiments, a processor obtains a plurality of sequential images from a video feed, and determines respective keypoints corresponding a human in each respective image of the plurality of sequential images. The processor aggregates the respective keypoints for each respective image into a pose of the human and transmits a query to a database to find a template that matches the pose by comparing the pose to a plurality of templates poses that translate candidate poses to intent, each template corresponding to an associated intent. The processor receives a reply message from the database that either indicates an intent of the human based on a matching template, or an inability to locate the matching template, and, in response to the reply message indicating the intent of the human, outputs the intent.
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