Patents by Inventor Mostafa Parchami
Mostafa Parchami 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).
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Patent number: 11783707Abstract: A computing system can receive, in a vehicle, moving object information is determined by processing lidar sensor data acquired by a stationary lidar sensor. The moving object information can be determined using typicality and eccentricity data analysis (TEDA) on the lidar sensor data. The vehicle can be operated based on the moving object information.Type: GrantFiled: October 9, 2018Date of Patent: October 10, 2023Assignee: Ford Global Technologies, LLCInventors: Mostafa Parchami, Juan Enrique Castorena Martinez, Enrique Corona, Bruno Sielly Jales Costa, Gintaras Vincent Puskorius
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Patent number: 11754415Abstract: A system includes a computer including a processor and a memory storing instructions executable by the processor to identify a location and an orientation of a vehicle on a map. The instructions include instructions to determine a location of an infrastructure sensor on the map based on the location and the orientation of the vehicle, data from a vehicle sensor, and data from the infrastructure sensor.Type: GrantFiled: September 6, 2019Date of Patent: September 12, 2023Assignee: Ford Global Technologies, LLCInventors: Juan Enrique Castorena Martinez, Mostafa Parchami, Codrin Cionca, Siddharth Agarwal, Gintaras Vincent Puskorius
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Publication number: 20230267719Abstract: A deep neural network (DNN) can be trained based on a first training dataset that includes first images including annotated first objects. The DNN can be tested based on the first training dataset to determine first object predictions including first uncertainties. The DNN can be tested by inputting a second training dataset and outputting first object predictions including second uncertainties, wherein the second training dataset includes second images including unannotated second objects. A subset of images included in the second training dataset can be selected based on the second uncertainties, The second objects in the selected subset of images included in the second training dataset can be annotated. The DNN can be trained based on the selected subset of images included in the second training dataset including the annotated second objects.Type: ApplicationFiled: February 21, 2022Publication date: August 24, 2023Applicants: Ford Global Technologies, LLC, GEORGIA TECH RESEARCH CORPORATIONInventors: Mostafa Parchami, Enrique Corona, Ghassan AlRegib, Mohit Prabhushankar, Ryan Benkert
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Publication number: 20230267640Abstract: A two-dimensional image segment that includes an outline of an object can be determined in a top-down fisheye image. A six degree of freedom (DoF) pose for the object can be determined based on determining a three-dimensional bounding box determined by one or more of (1) an axis of the two-dimensional image segment in a ground plane included in the top-down fisheye image and a three-dimensional model of the object and (2) inputting the two-dimensional image segment to a deep neural network trained to determine a three-dimensional bounding box for the object.Type: ApplicationFiled: February 21, 2022Publication date: August 24, 2023Applicant: Ford Global Technologies, LLCInventors: Punarjay Chakravarty, Subodh Mishra, Mostafa Parchami, Gaurav Pandey, Shubham Shrivastava
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Patent number: 11709227Abstract: A sensor system is disclosed. The sensor system may comprise a housing; an emitter, carried by the housing, that emits a beam comprising depth-data signals; a beam-distribution adjustment system; and a processor programmed to control the adjustment system by selectively changing an angular distribution of the depth-data signals emitted from the housing.Type: GrantFiled: April 2, 2019Date of Patent: July 25, 2023Assignee: Ford Global Technologies, LLCInventors: Codrin Cionca, Juan Enrique Castorena Martinez, Mostafa Parchami, Linjun Zhang, Zhen Zhao
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Publication number: 20230177842Abstract: A segmentation mask can be determined that includes at least one moving object in a plurality of images based on determining eccentricity for each pixel location in the plurality of images. A first image included in the plurality of images can be segmented by applying the segmentation mask to the image. The segmented first image can be transformed to a compressed dense matrix which includes pixel values for non-zero portions of the segmented first image. The compressed dense matrix can be input to a sparse convolutional neural network trained to detect objects. A detected object corresponding to the at least one moving object included in the first image can be output from the sparse convolutional neural network.Type: ApplicationFiled: December 7, 2021Publication date: June 8, 2023Applicant: Ford Global Technologies, LLCInventors: Mostafa Parchami, Xiaomin Li, Enrique Corona, Kunjan Singh
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Publication number: 20230145701Abstract: A camera is positioned to obtain an image of an object. The image is input to a neural network that outputs a three-dimensional (3D) bounding box for the object relative to a pixel coordinate system and object parameters. Then a center of a bottom face of the 3D bounding box is determined in pixel coordinates. The bottom face of the 3D bounding box is located in a ground plane in the image. Based on calibration parameters for the camera that transform pixel coordinates into real-world coordinates, a) a distance from the center of the bottom face of the 3D bounding box to the camera relative to a real-world coordinate system and b) an angle between a line extending from the camera to the center of the bottom face of the 3D bounding box and an optical axis of the camera are determined. The calibration parameters include a camera height relative to the ground plane, a camera focal distance, and a camera tilt relative to the ground plane.Type: ApplicationFiled: September 24, 2021Publication date: May 11, 2023Applicant: Ford Global Technologies, LLCInventors: Mostafa Parchami, Enrique Corona, Kunjan Singh, Gaurav Pandey
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Publication number: 20230136871Abstract: A first plurality of center points of first two-dimensional bounding boxes corresponding to a vehicle occurring in a first plurality of images acquired by a first camera can be determined. A second plurality of center points of second two-dimensional bounding boxes corresponding to the vehicle occurring in a second plurality of images acquired by a second camera can also be determined. A plurality of non-linear equations based on the locations of the first and second pluralities of center points and first and second camera parameters corresponding to the first and second cameras can be determined. The plurality of non-linear equations can be solved simultaneously for the locations of the vehicle with respect to the first and second cameras and the six degree of freedom pose of the second camera with respect to the first camera. Real-world coordinates of the six degree of freedom pose of the second camera can be determined based on real-world coordinates of a six degree of freedom pose of the first camera.Type: ApplicationFiled: November 1, 2021Publication date: May 4, 2023Applicant: Ford Global Technologies, LLCInventors: Punarjay Chakravarty, Shubham Shrivastava, Bhushan Ghadge, Mostafa Parchami, Gaurav Pandey
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Patent number: 11637754Abstract: A set of first candidate topologies of first candidate roadside infrastructure nodes at respective mounting locations in a geographic area is randomly generated. For each of the first candidate topologies, first simulations, including detection of objects according to selected sensor parameters, installation parameters, and environment parameters for the candidate nodes at the respective mounting locations, are executed. First fitness scores are determined for each of the first candidate topologies by comparing results of the first simulations to ground truth data. Upon identifying one of the first fitness scores as exceeding a threshold, the candidate topology associated with the identified first fitness score is identified for deployment.Type: GrantFiled: January 15, 2021Date of Patent: April 25, 2023Assignee: FORD GLOBAL TECHNOLOGIES, LLCInventors: Gaurav Pandey, Jeffrey Thomas Remillard, Mostafa Parchami, Helen E. Kourous-Harrigan, John Anthony Lockwood
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Patent number: 11500104Abstract: A reference pose of an object in a coordinate system of a map of an area is determined. The reference pose is based on a three-dimensional (3D) reference model representing the object. A first pose of the object is determined as the object moves with respect to the coordinate system. The first pose is determined based on the reference pose and sensor data collected by the sensor at a first time. A second pose of the object is determined as the object continues to move with respect to the coordinate system. The second pose is determined based on the reference pose, the first pose, and sensor data collected by the sensor at a second time consecutive to the first time.Type: GrantFiled: August 16, 2019Date of Patent: November 15, 2022Assignee: FORD GLOBAL TECHNOLOGIES, LLCInventors: Siddharth Agarwal, Faizan Shaik, Ankit Girish Vora, Sangjin Lee, Mostafa Parchami
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Patent number: 11495125Abstract: A system comprises a computer including a processor, and a memory. The memory stores instructions such that the processor is programmed to determine two or more clusters of vehicle operating parameter values from each of a plurality of vehicles at a location within a time. Determining the two or more clusters includes clustering data from the plurality of vehicles based on proximity to two or more respective means. The processor is further programmed to determine a reportable condition when a mean for a cluster representing a greatest number of vehicles varies from a baseline by more than a threshold.Type: GrantFiled: March 1, 2019Date of Patent: November 8, 2022Assignee: Ford Global Technologies, LLCInventors: Linjun Zhang, Juan Enrique Castorena Martinez, Codrin Cionca, Mostafa Parchami
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Patent number: 11460851Abstract: A system, comprising a computer that includes a processor and a memory, the memory storing instructions executable by the processor to input a red-green-blue (RGB) image and an eccentricity image to a neural network which outputs a located object based on combining the RGB image and the eccentricity image, wherein the eccentricity image is based on a per-pixel rolling average and a per-pixel rolling variance over a moving window of k video frames. The memory can further include instructions executable by the processor to receive the located object at a computing device included in one or more of a vehicle or a traffic information system.Type: GrantFiled: May 24, 2019Date of Patent: October 4, 2022Assignee: Ford Global Technologies, LLCInventors: Mostafa Parchami, Chandana Neerukonda, Gintaras Vincent Puskorius, Enrique Corona, Kunjan Singh
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Patent number: 11423576Abstract: A system includes a camera, a visual target including a GPS receiver, and a processor. The camera images the visual target at a plurality of locations to obtain a plurality of images. The processor receives GPS coordinates for each respective location. Also, the processor determines a 3D location of the visual target in a camera reference frame for each of the images. The processor derives a plurality of estimated GPS camera locations for each of the plurality of images and mitigates an error associated with each of the derived estimated GPS camera locations to derive an average GPS camera location. This location is used to determine and store a transformation usable to describe objects viewed by the camera in the camera reference frame in terms of the GPS reference frame.Type: GrantFiled: July 23, 2021Date of Patent: August 23, 2022Assignee: Ford Global Technologies, LLCInventors: Enrique Corona, Mostafa Parchami, Gaurav Pandey
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Patent number: 11403856Abstract: A system, including a processor and a memory, the memory including instructions to be executed by the processor to identify first object features from sensor data acquired by a stationary sensor at a first time step, determine second object features at a second time step. The instructions can include further instructions to determine one or more object clusters of first object features by determining distances measured in pixels between the first object features and corresponding second object features and comparing the distances to one or more mean distances and determine one or more object groups of inlier first object features in the one or more object clusters by determining a plurality of similarity transformations for a plurality of random samples of first object features and determining inlier first object features based on maximizing the number of first object features included in a similarity transformation.Type: GrantFiled: August 26, 2020Date of Patent: August 2, 2022Assignee: FORD GLOBAL TECHNOLOGIES, LLCInventors: Mostafa Parchami, Faizan Shaik, Stephen Giardinelli, Gintaras Vincent Puskorius, Enrique Corona, Kunjan Singh
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Publication number: 20220231919Abstract: A set of first candidate topologies of first candidate roadside infrastructure nodes at respective mounting locations in a geographic area is randomly generated. For each of the first candidate topologies, first simulations, including detection of objects according to selected sensor parameters, installation parameters, and environment parameters for the candidate nodes at the respective mounting locations, are executed. First fitness scores are determined for each of the first candidate topologies by comparing results of the first simulations to ground truth data. Upon identifying one of the first fitness scores as exceeding a threshold, the candidate topology associated with the identified first fitness score is identified for deployment.Type: ApplicationFiled: January 15, 2021Publication date: July 21, 2022Applicant: Ford Global Technologies, LLCInventors: Gaurav Pandey, Jeffrey Thomas Remillard, Mostafa Parchami, Helen E. Kourous-Harrigan, John Anthony Lockwood
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Patent number: 11391574Abstract: A system includes a Lidar sensor and a processor. The processor is programmed to detect, using Lidar sensor data, a low-density area comprising a plurality of Lidar beam reflections less than a threshold, to determine dimensions of the area, and to determine that the area represents a physical object based on the detection and determination.Type: GrantFiled: January 18, 2019Date of Patent: July 19, 2022Assignee: FORD GLOBAL TECHNOLOGIES, LLCInventors: Mostafa Parchami, Codrin Cionca, Juan Enrique Castorena Martinez
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Patent number: 11288901Abstract: Detection of an impact to a vehicle is based on data received from one of (a) one or more infrastructure sensors included in an infrastructure element or (b) the vehicle. Verification of the impact is determined by determining that data received from the other of the infrastructure sensors or the vehicle (a) detects the impact and is verified or (b) does not detect the impact and is unverified. A message is transmitted to the vehicle including the verification of the impact and one of (a) a request to operate to a predetermined location based on the impact being verified or (b) a notification to continue a current operation based on the impact being unverified.Type: GrantFiled: October 24, 2019Date of Patent: March 29, 2022Assignee: FORD GLOBL TECHNOLOGIES, LLCInventors: Chandana Neerukonda, Mostafa Parchami, Krithika Swaminathan, Mahrdad Damsaz
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Publication number: 20220067407Abstract: A system, including a processor and a memory, the memory including instructions to be executed by the processor to identify first object features from sensor data acquired by a stationary sensor at a first time step, determine second object features at a second time step.Type: ApplicationFiled: August 26, 2020Publication date: March 3, 2022Applicant: Ford Global Technologies, LLCInventors: Mostafa Parchami, Faizan Shaik, Stephen Giardinelli, Gintaras Vincent Puskorius, Enrique Corona, Kunjan Singh
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Publication number: 20210284180Abstract: A system includes a shaft extendable from a vehicle roof, a sensor mount mounted to the shaft, a plurality of sensors supported by the sensor mount, and a computer communicatively coupled with one or more of the sensors to receive data from the one or more of the sensors, the computer including a processor and a memory. The memory stores instructions executable by the processor to extend the shaft to position the sensor mount to a specified height above the roof.Type: ApplicationFiled: March 5, 2021Publication date: September 16, 2021Applicant: Ford Global Technologies, LLCInventors: Mostafa Parchami, Stephen Giardinelli, John Anthony Lockwood
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Patent number: 11035679Abstract: A computer includes a processor and a memory. The memory stores instructions executable by the processor to receive, in a vehicle, object data from an external node, and upon identifying a point, in the received object data, that is within a volume defined based on vehicle position data received from a vehicle sensor, to determine an adjusted vehicle position based on the identified point and the vehicle position data.Type: GrantFiled: January 4, 2019Date of Patent: June 15, 2021Assignee: FORD GLOBAL TECHNOLOGIES, LLCInventors: Codrin Cionca, Juan Enrique Castorena Martinez, Mostafa Parchami