公开(公告)号：US20240404297A1

公开(公告)日：2024-12-05

申请号：US18328921

申请日：2023-06-05

Applicant: Honda Motor Co., Ltd. ,  The Board of Trustees of the Leland Stanford Junior University

Inventor： Enna SACHDEVA ,  Nakul AGARWAL ,  Sean F. ROELOFS ,  Jiachen LI ,  Behzad DARIUSH ,  Chiho CHOI

IPC: G06V20/58 ,  G06V10/778 ,  G06V10/82

Abstract: Systems and methods for training a neural network for generating a reasoning statement are provided. In one embodiment, a method includes receiving sensor data from a perspective of an ego agent. The method includes identifying a plurality of captured objects in the at least one roadway environment. The method includes receiving a set of ranking classifications for a captured object of the plurality of captured objects. The annotator reasoning statement is a natural language explanation for the applied attribute. The method includes generating a training dataset for the object type including the annotator reasoning statements of the set of ranking classifications that include the applied attribute from the plurality of importance attributes in the importance category. The method includes training the neural network to generate a generated reasoning statement based on the training dataset in response to a training agent detecting a detected object of the object type.

公开(公告)号：US20230141037A1

公开(公告)日：2023-05-11

申请号：US17590379

申请日：2022-02-01

Applicant: Honda Motor Co., Ltd.

Inventor： Reza GHODDOOSIAN ,  Isht DWIVEDI ,  Nakul AGARWAL ,  Chiho CHOI ,  Behzad DARIUSH

IPC: G06V10/778 ,  G06V10/26 ,  G06V20/40 ,  G06V40/20 ,  G06V10/82

CPC classification number: G06V10/7792 ,  G06V10/26 ,  G06V20/49 ,  G06V40/20 ,  G06V10/82

Abstract: A system and method for providing weakly-supervised online action segmentation that include receiving image data associated with multi-view videos of a procedure, wherein the procedure involves a plurality of atomic actions. The system and method also include analyzing the image data using weakly-supervised action segmentation to identify each of the plurality of atomic actions by using an ordered sequence of action labels. The system and method additionally include training a neural network with data pertaining to the plurality of atomic actions based on the weakly-supervised action segmentation. The system and method further include executing online action segmentation to label atomic actions that are occurring in real-time based on the plurality of atomic actions trained to the neural network.

公开(公告)号：US20210271866A1

公开(公告)日：2021-09-02

申请号：US16805607

申请日：2020-02-28

Applicant: Honda Motor Co., Ltd.

Inventor： Jun HAYAKAWA ,  Behzad DARIUSH

IPC: G06K9/00 ,  G06N3/02

Abstract: In some examples, a first set of image data is received, the first set of image data corresponding to images of a first type and being of a person in an environment of a vehicle and including a first plurality of images of the person over a time interval. In some examples, a second set of image data is received, the second set of image data corresponding to images of a second type and being of the person in the environment of the vehicle and including a second plurality of images of the person over the time interval. In some examples, the first set of image data and the second set of image data are processed to determine a recognized action of the person, which includes using a first neural network to determine the recognized action of the person.

公开(公告)号：US20240394309A1

公开(公告)日：2024-11-28

申请号：US18323027

申请日：2023-05-24

Applicant: Honda Motor Co., Ltd.

Inventor： Aolin XU ,  Enna SACHDEVA ,  Yichen SONG ,  Teruhisa MISU ,  Behzad DARIUSH ,  Kikuo FUJIMURA ,  Kentaro YAMADA

IPC: G06F16/901

Abstract: According to one aspect, causal graph chain reasoning predictions may be implemented by generating a causal graph of one or more participants within an operating environment including an ego-vehicle, one or more agents, and one or more potential obstacles, generating a prediction for each participant within the operating environment based on the causal graph, and generating an action for the ego-vehicle based on the prediction for each participant within the operating environment. Nodes of the causal graph may represent the ego-vehicle or one or more of the agents. Edges of the causal graph may represent a causal relationship between two nodes of the causal graph. The causal relationship may be a leader-follower relationship, a trajectory-dependency relationship, or a collision relationship.

公开(公告)号：US20240371166A1

公开(公告)日：2024-11-07

申请号：US18308542

申请日：2023-04-27

Applicant: Honda Motor Co., Ltd.

Inventor： Reza GHODDOOSIAN ,  Isht DWIVEDI ,  Nakul AGARWAL ,  Behzad DARIUSH

IPC: G06V20/40 ,  G06V10/774

Abstract: According to one aspect, weakly-supervised action segmentation may include performing feature extraction to extract one or more features associated with a current frame of a video including a series of one or more actions, feeding one or more of the features to a recognition network to generate a predicted action score for the current frame of the video, feeding one or more of the features and the predicted action score to an action transition model to generate a potential subsequent action, feeding the potential subsequent action and the predicted action score to a hybrid segmentation model to generate a predicted sequence of actions from a first frame of the video to the current frame of the video, and segmenting or labeling one or more frames of the video based on the predicted sequence of actions from the first frame of the video to the current frame of the video.

公开(公告)号：US20220414887A1

公开(公告)日：2022-12-29

申请号：US17710807

申请日：2022-03-31

Applicant: Honda Motor Co., Ltd.

Inventor： Isht DWIVEDI ,  Yi-Ting CHEN ,  Behzad DARIUSH

IPC: G06T7/10 ,  G06V10/77 ,  G06V10/82 ,  G06T7/50 ,  G06V10/774 ,  G06T17/05

Abstract: Systems and methods for bird's eye view (BEV) segmentation are provided. In one embodiment, a method includes receiving an input image from an image sensor on an agent. The input image is a perspective space image defined relative to the position and viewing direction of the agent. The method includes extracting features from the input image. The method includes estimating a depth map that includes depth values for pixels of the plurality of pixels of the input image. The method includes generating a 3D point map including points corresponding to the pixels of the input image. The method includes generating a voxel grid by voxelizing the 3D point map into a plurality voxels. The method includes generating a feature map by extracting feature vectors for pixels based on the points included in the voxels of the plurality of voxels and generating a BEV segmentation based on the feature map.

公开(公告)号：US20200324781A1

公开(公告)日：2020-10-15

申请号：US16380586

申请日：2019-04-10

Applicant: HONDA MOTOR CO., LTD.

Inventor： Jun HAYAKAWA ,  Behzad DARIUSH

IPC: B60W40/105 ,  G06T7/246

Abstract: Systems and methods for estimating velocity of an autonomous vehicle and state information of a surrounding vehicle are provided. In some aspects, the system includes a memory that stores instructions for executing processes for estimating velocity of an autonomous vehicle and state information of the surrounding vehicle and a processor configured to execute the instructions. In various aspects, the processes include: receiving image data from an image capturing device; performing a ground plane estimation by predicting a depth of points on a road surface based on an estimated pixel-level depth; determining a three-dimensional (3D) bounding box of the surrounding vehicle; determining the state information of the surrounding vehicle based on the ground plane estimation and the 3D bounding box; and determining the velocity of the autonomous vehicle based on an immovable object relative to the autonomous vehicle. In some aspects, an operation of the autonomous vehicle may be controlled based on at least one of the state information or the velocity of the autonomous vehicles.

公开(公告)号：US20250074445A1

公开(公告)日：2025-03-06

申请号：US18618444

申请日：2024-03-27

Applicant: Honda Motor Co., Ltd.

Inventor： Aolin XU ,  Chenran LI ,  Enna SACHDEVA ,  Teruhisa MISU ,  Behzad DARIUSH ,  Kentaro YAMADA ,  Kikuo Fujimura

IPC: B60W50/14 ,  B60W30/095 ,  B60W40/09 ,  B60W50/00

Abstract: A vehicle includes a ranged sensor that generates time-series data indicating positions of objects in an environment surrounding the vehicle, a user interface configured to warn the driver of a predicted collision between the vehicle and one of the objects in the environment, and at least one processor including an ECU operatively connected to the ranged sensor and the user interface. The processor records control inputs by the driver driving the vehicle, and develops a driver behavior model associated with the driver driving the vehicle based on the control inputs. The processor also predicts trajectories of the objects and the vehicle based on the time-series data and the driver behavior model, and predicts a collision between the vehicle and one of the objects based on the predicted trajectories. The processor also generates a warning indicating the predicted collision to the driver.

公开(公告)号：US20230081247A1

公开(公告)日：2023-03-16

申请号：US17988361

申请日：2022-11-16

Applicant: Honda Motor Co., Ltd.

Inventor： Srikanth MALLA ,  Chiho CHOI ,  Behzad DARIUSH

IPC: B60W60/00 ,  G06T7/70 ,  G06V20/58

Abstract: A system and method for future forecasting using action priors that include receiving image data associated with a surrounding environment of an ego vehicle and dynamic data associated with dynamic operation of the ego vehicle. The system and method also include analyzing the image data to classify dynamic objects as agents and to detect and annotate actions that are completed by the agents that are located within the surrounding environment of the ego vehicle and analyzing the dynamic data to process an ego motion history that is associated with the ego vehicle that includes vehicle dynamic parameters during a predetermined period of time. The system and method further include predicting future trajectories of the agents located within the surrounding environment of the ego vehicle and a future ego motion of the ego vehicle within the surrounding environment of the ego vehicle based on the annotated actions.

公开(公告)号：US20220215661A1

公开(公告)日：2022-07-07

申请号：US17704324

申请日：2022-03-25

Applicant: Honda Motor Co., Ltd.

Inventor： Yi-Ting CHEN ,  Behzad DARIUSH ,  Nakul AGARWAL ,  Ming-Hsuan YANG

IPC: G06V20/40 ,  G06K9/62 ,  G06N3/08 ,  G06V20/56

Abstract: A system and method for providing unsupervised domain adaption for spatio-temporal action localization that includes receiving video data associated with a source domain and a target domain that are associated with a surrounding environment of a vehicle. The system and method also include analyzing the video data associated with the source domain and the target domain and determining a key frame of the source domain and a key frame of the target domain. The system and method additionally include completing an action localization model to model a temporal context of actions occurring within the key frame of the source domain and the key frame of the target domain and completing an action adaption model to localize individuals and their actions and to classify the actions based on the video data. The system and method further include combining losses to complete spatio-temporal action localization of individuals and actions.