公开(公告)号：US20240290118A1

公开(公告)日：2024-08-29

申请号：US18175993

申请日：2023-02-28

Applicant: Verizon Patent and Licensing Inc.

Inventor： Niccolo BELLACCINI ,  Matteo SIMONCINI ,  Douglas COIMBRA DE ANDRADE ,  Francesco SAMBO

IPC: G06V20/70 ,  G06F16/51 ,  G06F16/53 ,  G06F16/58 ,  G06F40/186 ,  G06F40/279 ,  G06V10/40 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06V20/70 ,  G06F16/51 ,  G06F16/53 ,  G06F16/5866 ,  G06F40/186 ,  G06F40/279 ,  G06V10/40 ,  G06V10/764 ,  G06V10/82

Abstract: A device may receive a plurality of narratives associated with a plurality of scenes and an image identifying a scene not included in the plurality of scenes, and may process the image, with a classifier model, to detect a plurality of features in the image. The device may replace keywords in the plurality of narratives, with tags, to generate a plurality of sentences, and may group similar sentences of the plurality of sentences, based on a defined measure of dissimilarity, into clusters of templates. The device may select a candidate template from each of the clusters to generate a set of candidate templates, and may select a template from the set of candidate templates. The device may populate tags of the template with the plurality of features detected in the image to generate an image caption, and may provide the image and the image caption for display.

公开(公告)号：US20230274555A1

公开(公告)日：2023-08-31

申请号：US17682610

申请日：2022-02-28

Applicant: Verizon Patent and Licensing Inc.

Inventor： Matteo SIMONCINI ,  Douglas COIMBRA DE ANDRADE ,  Leonardo TACCARI ,  Leonardo SARTI ,  Francesco SAMBO ,  Fabio SCHOEN ,  Niccolo BELLACCINI

IPC: G06V20/58 ,  G06V10/40 ,  G06V10/82 ,  G06N3/04

CPC classification number: G06V20/58 ,  G06V10/40 ,  G06V10/82 ,  G06N3/0454 ,  G06N3/0445

Abstract: A device may receive a video and corresponding sensor information associated with a vehicle, and may extract feature vectors associated with the corresponding sensor information and an appearance and a geometry of another vehicle captured in the video. The device may generate a tensor based on the feature vectors, and may process the tensor, with a convolutional neural network model, to generate a modified tensor. The device may select a decoder model from a plurality of decoder models, and may process the modified tensor, with the decoder model, to generate a caption for the video based on attributes associated with the video. The device may perform one or more actions based on the caption for the video.

公开(公告)号：US20250085109A1

公开(公告)日：2025-03-13

申请号：US18464003

申请日：2023-09-08

Applicant: Verizon Patent and Licensing Inc.

Inventor： Matteo SIMONCINI ,  Tommaso BIANCONCINI ,  Luca BRAVI ,  Leonardo SARTI ,  Leonardo TACCARI ,  Douglas COIMBRA DE ANDRADE ,  Francesco SAMBO

IPC: G01C21/16 ,  B60W40/09 ,  G01S19/47

Abstract: A device may receive video data and corresponding GPS data and IMU data associated with a vehicle, and may process the video data, with an object detector model, to identify objects and to generate a first feature vector. The device may process the GPS data and the IMU data, with a first CNN model, to generate a second feature vector, and may process the objects and the video data, with a tracking model, to identify positions and classes of the objects and to generate a third feature vector. The device may utilize a second CNN model to generate a matrix of object features based on the first, second, and third feature vectors, and may utilize a spatiotemporal attention selector model or a max pooled model with the matrix of object features to identify a classification of a maneuver of the vehicle. The device may perform actions based on the classification.

公开(公告)号：US20240096056A1

公开(公告)日：2024-03-21

申请号：US17933247

申请日：2022-09-19

Applicant: Verizon Patent and Licensing Inc.

Inventor： Matteo SIMONCINI ,  Stefano CAPRASECCA ,  Leonardo SARTI

IPC: G06V10/764 ,  G06V20/40 ,  G06V20/56

CPC classification number: G06V10/764 ,  G06V20/41 ,  G06V20/56

Abstract: A device may receive video data identifying videos associated with one or more unsafe driving events by a driver of a vehicle, and may process the video data, with a machine learning model, to determine classifications for the videos. The device may assign tags to the videos based on the classifications, and may calculate event severity scores based on the classifications. The device may calculate tag scores based on the tags assigned to the videos, and may calculate time-to-contact scores, box cross scores, day/night scores, weather scores, and road condition scores based on the video data. The device may calculate video risk scores for the videos based on the event severity scores, the tag scores, the time-to-contact scores, the box cross scores, the day/night scores, the weather scores, and the road condition scores, and may provide one or more of the video risk scores for display.

公开(公告)号：US20240257535A1

公开(公告)日：2024-08-01

申请号：US18162838

申请日：2023-02-01

Applicant: Verizon Patent and Licensing Inc.

Inventor： Douglas COIMBRA DE ANDRADE ,  Francesco SAMBO ,  Matteo SIMONCINI ,  Andrea BENERICETTI ,  Leonardo TACCARI

IPC: G06V20/58 ,  B60W50/14 ,  G06F3/01 ,  G06T7/70 ,  G06T17/20 ,  G06V10/74 ,  G06V20/59

CPC classification number: G06V20/582 ,  B60W50/14 ,  G06F3/013 ,  G06T7/70 ,  G06T17/20 ,  G06V10/761 ,  G06V20/59 ,  G06T2207/10048 ,  G06T2207/20081 ,  G06V2201/07

Abstract: A device may receive driver facing video data associated with a driver of a vehicle and forward facing video data associated with the vehicle, and may process the driver facing video data, with a face model, to identify driver head orientation and driver gaze. The device may generate a first transformation matrix mapping the driver facing video data, the driver head orientation, and the driver gaze, and may generate a second transformation matrix mapping the driver facing video data and the forward facing video data. The device may utilize the first transformation matrix and the second transformation matrix to estimate image coordinates, and may aggregate the image coordinates to generate aggregated coordinates. The device may generate heat maps based on the aggregated coordinates, may train machine learning model, with the heat maps, to generate a trained machine learning model, and may perform actions based on the trained machine learning model.

公开(公告)号：US20240242510A1

公开(公告)日：2024-07-18

申请号：US18155435

申请日：2023-01-17

Applicant: Verizon Patent and Licensing Inc.

Inventor： Niccolo BELLACCINI ,  Matteo SIMONCINI ,  Andrea BENERICETTI ,  Henrique Pineiro MONTEAGUDO ,  Francesco SAMBO

IPC: G06V20/56 ,  B60W50/14 ,  G06T3/40 ,  G06T7/13 ,  G06T7/20

CPC classification number: G06V20/588 ,  B60W50/14 ,  G06T3/40 ,  G06T7/13 ,  G06T7/20 ,  G06T2207/20084 ,  G06T2207/30256

Abstract: In some implementations, a video system may receive, from a camera mounted to a vehicle, a video of a portion of a road on which the vehicle is traveling. The video system may extract, from each frame of a plurality of frames associated with the video of the road, a frame strip to form a plurality of frame strips, wherein each frame strip extends a predetermined width in a horizontal direction and a predetermined height in a vertical direction. The video system may form, from each frame strip, a single-pixel strip, to form a plurality of single-pixel strips. The video system may compile the plurality of single-pixel strips to form a motion profile. The video system may determine, using machine learning, one of: at least one driving maneuver associated with the vehicle based on the motion profile, or that no driving maneuvers are present in the motion profile.