Patents by Inventor Matteo Simoncini

Matteo Simoncini has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20240290118
    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.
    Type: Application
    Filed: February 28, 2023
    Publication date: August 29, 2024
    Applicant: Verizon Patent and Licensing Inc.
    Inventors: Niccolo BELLACCINI, Matteo SIMONCINI, Douglas COIMBRA DE ANDRADE, Francesco SAMBO
  • Publication number: 20240257535
    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.
    Type: Application
    Filed: February 1, 2023
    Publication date: August 1, 2024
    Applicant: Verizon Patent and Licensing Inc.
    Inventors: Douglas COIMBRA DE ANDRADE, Francesco SAMBO, Matteo SIMONCINI, Andrea BENERICETTI, Leonardo TACCARI
  • Publication number: 20240242510
    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.
    Type: Application
    Filed: January 17, 2023
    Publication date: July 18, 2024
    Applicant: Verizon Patent and Licensing Inc.
    Inventors: Niccolo BELLACCINI, Matteo SIMONCINI, Andrea BENERICETTI, Henrique Pineiro MONTEAGUDO, Francesco SAMBO
  • Publication number: 20240221358
    Abstract: A system may determine, for each frame of a plurality of frames of image data associated with a vehicle, a probability that each frame of the plurality of frames that includes an image of a stop sign is relevant to the vehicle. The system may determine a longest sequence of consecutive frames of the plurality of frames for which the probability satisfies a probability threshold. The system may determine a maximum probability associated with a frame included in the longest sequence of consecutive frames. The system may determine a time window based on a time associated with the frame associated with the maximum probability. The system may determine location data and sensor data for the vehicle based on the time window. The system may determine an occurrence of a stop sign violation based on the location data and the sensor data.
    Type: Application
    Filed: January 12, 2024
    Publication date: July 4, 2024
    Applicant: Verizon Connect Development Limited
    Inventors: Luca BRAVI, Luca KUBIN, Leonardo TACCARI, Francesco SAMBO, Matteo SIMONCINI, Douglas COIMBRA DE ANDRADE, Stefano CAPRASECCA
  • Patent number: 11966236
    Abstract: A device can receive a request for a schedule that assigns a fleet of vehicles to a set of deliveries. The device can determine that a parameter is not included in the request that is needed to generate a new schedule or that is needed to generate an existing schedule. The device can obtain the parameter using a historical user request, a historical schedule, or a scheduling template. The device can generate or obtain the schedule based on information included in the request and the obtained parameter. The device can provide the schedule to a user device and/or to one or more devices associated with the fleet of vehicles carrying out the set of deliveries. The device can modify the schedule based on a trigger. The device can provide the modified schedule to the user device and/or to the one or more devices associated with the fleet of vehicles.
    Type: Grant
    Filed: November 25, 2020
    Date of Patent: April 23, 2024
    Assignee: Verizon Connect Development Limited
    Inventors: Valerio Arena, Francesco Sambo, Leonardo Sarti, Matteo Simoncini, Nicola Tommasi
  • Publication number: 20240096056
    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.
    Type: Application
    Filed: September 19, 2022
    Publication date: March 21, 2024
    Applicant: Verizon Patent and Licensing Inc.
    Inventors: Matteo SIMONCINI, Stefano CAPRASECCA, Leonardo SARTI
  • Patent number: 11922651
    Abstract: A device may receive a first image. The device may process the first image to identify an object in the first image and a location of the object within the first image. The device may extract a second image from the first image based on the location of the object within the first image. The device may process the second image to determine at least one of a coarse-grained viewpoint estimate or a fine-grained viewpoint estimate associated with the object. The device may determine an object viewpoint associated with the second vehicle based on the at least one of the coarse-grained viewpoint estimate or the fine-grained viewpoint estimate. The device may perform one or more actions based on the object viewpoint.
    Type: Grant
    Filed: December 2, 2022
    Date of Patent: March 5, 2024
    Assignee: Verizon Connect Development Limited
    Inventors: Simone Magistri, Francesco Sambo, Douglas Coimbra De Andrade, Fabio Schoen, Matteo Simoncini, Luca Bravi, Stefano Caprasecca, Luca Kubin, Leonardo Taccari
  • Patent number: 11900657
    Abstract: A violation detection platform may obtain image data, location data, and sensor data associated with a vehicle. The violation detection platform may determine a probability that a frame of the image data includes an image of a stop sign. The violation detection platform may determine that the probability satisfies a probability threshold. The violation detection platform may identify location data and sensor data associated with the frame of the image data based on the probability satisfying the probability threshold. The violation detection platform may determine an occurrence of a type of a stop sign violation based on the probability, the location data, and the sensor data. The violation detection platform may perform one or more actions based on determining the occurrence of the type of the stop sign violation.
    Type: Grant
    Filed: August 24, 2020
    Date of Patent: February 13, 2024
    Assignee: Verizon Connect Development Limited
    Inventors: Luca Bravi, Luca Kubin, Leonardo Taccari, Francesco Sambo, Matteo Simoncini, Douglas Coimbra De Andrade, Stefano Caprasecca
  • Publication number: 20230274555
    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.
    Type: Application
    Filed: February 28, 2022
    Publication date: August 31, 2023
    Applicant: Verizon Patent and Licensing Inc.
    Inventors: Matteo SIMONCINI, Douglas COIMBRA DE ANDRADE, Leonardo TACCARI, Leonardo SARTI, Francesco SAMBO, Fabio SCHOEN, Niccolo BELLACCINI
  • Patent number: 11710082
    Abstract: A device may receive vehicle operation data associated with operation of a plurality of vehicles, and may process the vehicle operation data to generate processed vehicle operation data. The device may extract multiple features from the processed vehicle operation data, and may train machine learning models, with the multiple features, to generate trained machine learning models that provide model outputs. The device may process the multiple features, with a feature selection model and based on the model outputs, to select sets of features from the plurality of features, and may process the sets of features, with the trained machine learning models, to generate indications of driving behavior and reliabilities of the indications. The device may select a set of features, from the sets of features, based on the indications and the reliabilities, where the set of features may be calculated by a device associated with a particular vehicle.
    Type: Grant
    Filed: April 12, 2021
    Date of Patent: July 25, 2023
    Assignee: Verizon Connect Development Limited
    Inventors: Matteo Simoncini, Aurel Pjetri, Francesco Sambo, Alessandro Lori, Fabio Schoen
  • Patent number: 11654924
    Abstract: A maneuver classification platform may obtain video data and telematic data that are associated with a driving event involving a vehicle. The maneuver classification platform may analyze the video data to identify a path of the vehicle along a roadway during the driving event, and based on markings of a plurality of roadways. The maneuver classification platform may analyze the video data to determine a type of a vehicle maneuver performed by the vehicle during the driving event. The maneuver classification platform may determine a maneuver score of the driving event based on the type of the vehicle maneuver, the path of the vehicle, and the telematic data. The maneuver classification platform may send a message associated with the maneuver score and a vehicle identifier of the vehicle to a client device to permit the client device to use the maneuver score.
    Type: Grant
    Filed: August 18, 2022
    Date of Patent: May 23, 2023
    Assignee: Verizon Connect Development Limited
    Inventors: Matteo Simoncini, Douglas Coimbra De Andrade, Samuele Salti, Leonardo Taccari, Fabio Schoen, Francesco Sambo, Leonardo Sarti
  • Patent number: 11639857
    Abstract: A rating platform can identify a point of interest (POI) among a first plurality of POIs included in a stop cluster. The rating platform can generate a plurality of unweighted user scores for the POI. Respective unweighted user scores, of the plurality of unweighted user scores is associated, can be associated with respective users of a plurality of users. The rating platform can generate a plurality of weighted user scores for the POI based on the plurality of unweighted user scores and respective weights assigned to respective users of the plurality of users. The rating platform can generate a POI score for the POI based on the plurality of weighted user scores. The rating platform can transmit, based on the POI score, an instruction to display, on the client device, information associated with the POI.
    Type: Grant
    Filed: February 3, 2021
    Date of Patent: May 2, 2023
    Assignee: Verizon Connect Development Limited
    Inventors: Luca Bravi, Stefano Caprasecca, Matteo Simoncini, Leonardo Sarti
  • Publication number: 20230102113
    Abstract: A device may receive a first image. The device may process the first image to identify an object in the first image and a location of the object within the first image. The device may extract a second image from the first image based on the location of the object within the first image. The device may process the second image to determine at least one of a coarse-grained viewpoint estimate or a fine-grained viewpoint estimate associated with the object. The device may determine an object viewpoint associated with the second vehicle based on the at least one of the coarse-grained viewpoint estimate or the fine-grained viewpoint estimate. The device may perform one or more actions based on the object viewpoint.
    Type: Application
    Filed: December 2, 2022
    Publication date: March 30, 2023
    Applicant: Verizon Connect Ireland Limited
    Inventors: Simone MAGISTRI, Francesco SAMBO, Douglas COIMBRA DE ANDRADE, Fabio SCHOEN, Matteo SIMONCINI, Luca BRAVI, Stefano CAPRASECCA, Luca KUBIN, Leonardo TACCARI
  • Publication number: 20220402505
    Abstract: A maneuver classification platform may obtain video data and telematic data that are associated with a driving event involving a vehicle. The maneuver classification platform may analyze the video data to identify a path of the vehicle along a roadway during the driving event, and based on markings of a plurality of roadways. The maneuver classification platform may analyze the video data to determine a type of a vehicle maneuver performed by the vehicle during the driving event. The maneuver classification platform may determine a maneuver score of the driving event based on the type of the vehicle maneuver, the path of the vehicle, and the telematic data. The maneuver classification platform may send a message associated with the maneuver score and a vehicle identifier of the vehicle to a client device to permit the client device to use the maneuver score.
    Type: Application
    Filed: August 18, 2022
    Publication date: December 22, 2022
    Applicant: Verizon Connect Development Limited
    Inventors: Matteo SIMONCINI, Douglas COIMBRA DE ANDRADE, Samuele SALTI, Leonardo TACCARI, Fabio SCHOEN, Francesco SAMBO, Leonardo SARTI
  • Patent number: 11532096
    Abstract: A device may receive a first image. The device may process the first image to identify an object in the first image and a location of the object within the first image. The device may extract a second image from the first image based on the location of the object within the first image. The device may process the second image to determine at least one of a coarse-grained viewpoint estimate or a fine-grained viewpoint estimate associated with the object. The device may determine an object viewpoint associated with the second vehicle based on the at least one of the coarse-grained viewpoint estimate or the fine-grained viewpoint estimate. The device may perform one or more actions based on the object viewpoint.
    Type: Grant
    Filed: August 24, 2020
    Date of Patent: December 20, 2022
    Assignee: Verizon Connect Development Limited
    Inventors: Simone Magistri, Francesco Sambo, Douglas Coimbra de Andrade, Fabio Schoen, Matteo Simoncini, Luca Bravi, Stefano Caprasecca, Luca Kubin, Leonardo Taccari
  • Patent number: 11440555
    Abstract: A maneuver classification platform may obtain video data and telematic data that are associated with a driving event involving a vehicle. The maneuver classification platform may analyze the video data to identify a path of the vehicle along a roadway during the driving event, and based on markings of a plurality of roadways. The maneuver classification platform may analyze the video data to determine a type of a vehicle maneuver performed by the vehicle during the driving event. The maneuver classification platform may determine a maneuver score of the driving event based on the type of the vehicle maneuver, the path of the vehicle, and the telematic data. The maneuver classification platform may send a message associated with the maneuver score and a vehicle identifier of the vehicle to a client device to permit the client device to use the maneuver score.
    Type: Grant
    Filed: August 24, 2020
    Date of Patent: September 13, 2022
    Assignee: Verizon Connect Development Limited
    Inventors: Matteo Simoncini, Douglas Coimbra De Andrade, Samuele Salti, Leonardo Taccari, Fabio Schoen, Francesco Sambo, Leonardo Sarti
  • Publication number: 20220084395
    Abstract: A method and system for classifying a vehicle based on low frequency GPS tracks. The method and system comprise retrieving a low frequency GPS track having a sampling interval of at least 20 seconds; deriving additional data from the low frequency GPS track, the additional data including interval speed and instantaneous acceleration of the vehicle; extracting a plurality of data sets from the low frequency GPS track and the additional data; generating a plurality of features from the extracted data sets; and providing the plurality of generated features to a classifier that classifies the vehicle into a predetermined class.
    Type: Application
    Filed: November 24, 2021
    Publication date: March 17, 2022
    Applicant: VERIZON CONNECT DEVELOPMENT LIMITED
    Inventors: Samuele SALTI, Francesco SAMBO, Leonardo TACCARI, Luca BRAVI, Matteo SIMONCINI, Alessandro LORI
  • Patent number: 11210939
    Abstract: A method and system for classifying a vehicle based on low frequency GPS tracks. The method and system comprise retrieving a low frequency GPS track having a sampling interval of at least 20 seconds; deriving additional data from the low frequency GPS track, the additional data including interval speed and instantaneous acceleration of the vehicle; extracting a plurality of data sets from the low frequency GPS track and the additional data; generating a plurality of features from the extracted data sets; and providing the plurality of generated features to a classifier that classifies the vehicle into a predetermined class.
    Type: Grant
    Filed: December 2, 2016
    Date of Patent: December 28, 2021
    Assignee: Verizon Connect Development Limited
    Inventors: Samuele Salti, Francesco Sambo, Leonardo Taccari, Luca Bravi, Matteo Simoncini, Alessandro Lori
  • Publication number: 20210366144
    Abstract: A device may receive a first image. The device may process the first image to identify an object in the first image and a location of the object within the first image. The device may extract a second image from the first image based on the location of the object within the first image. The device may process the second image to determine at least one of a coarse-grained viewpoint estimate or a fine-grained viewpoint estimate associated with the object. The device may determine an object viewpoint associated with the second vehicle based on the at least one of the coarse-grained viewpoint estimate or the fine-grained viewpoint estimate. The device may perform one or more actions based on the object viewpoint.
    Type: Application
    Filed: August 24, 2020
    Publication date: November 25, 2021
    Applicant: VERIZON CONNECT IRELAND LIMITED
    Inventors: Simone MAGISTRI, Francesco SAMBO, Douglas COIMBRA DE ANDRADE, Fabio SCHOEN, Matteo SIMONCINI, Luca BRAVI, Stefano CAPRASECCA, Luca KUBIN, Leonardo TACCARI
  • Publication number: 20210365700
    Abstract: A violation detection platform may obtain image data, location data, and sensor data associated with a vehicle. The violation detection platform may determine a probability that a frame of the image data includes an image of a stop sign. The violation detection platform may determine that the probability satisfies a probability threshold. The violation detection platform may identify location data and sensor data associated with the frame of the image data based on the probability satisfying the probability threshold. The violation detection platform may determine an occurrence of a type of a stop sign violation based on the probability, the location data, and the sensor data. The violation detection platform may perform one or more actions based on determining the occurrence of the type of the stop sign violation.
    Type: Application
    Filed: August 24, 2020
    Publication date: November 25, 2021
    Applicant: VERIZON CONNECT IRELAND LIMITED
    Inventors: Luca BRAVI, Luca KUBIN, Leonardo TACCARI, Francesco SAMBO, Matteo SIMONCINI, Douglas COIMBRA DE ANDRADE, Stefano CAPRASECCA