Abstract: Systems, devices and methods provide, implement, and use vision-based methods of sequence inference for a device affixed to a vehicle.

Abstract: A method implemented in an ophthalmic laser system to perform iris registration based on two iris images taken with the patient at upright and supine positions, respectively. For each iris image, the iris region is transformed into a rectangular rubbersheet, with the radial and angular coordinates of the iris image respectively mapped to vertical and horizontal coordinates of the rubbersheet. A horizontal one-dimensional log-Gabor transform is applied to the rubbersheet line-by-line. The transformed rubbersheet is binarized line-by-line. The two binary rubbersheets are compared at a series of relative horizontal shifts to determine the horizontal shift value that produces the lowest Hamming distance between the two binary rubbersheets, and the cyclotorsion rotation of the eye between the upright and supine positions is calculated accordingly.

Abstract: Apparatus to treat an eye with an ophthalmic laser system comprises a patient interface having an annular retention structure to couple to an anterior surface of the eye. The retention structure is coupled to a suction line to couple the retention structure to the eye with suction. Liquid is added above the eye to act as a transmissive medium. A coupling sensor is coupled to the suction line to determine coupling of the retention structure to the eye. A separate pressure monitoring circuit having a much smaller volume than the suction line is connected to the annular retention structure to measure suction pressure therein. A system processor coupled to the monitoring pressure sensor includes instructions to interrupt firing of a laser when the pressure measured with a monitoring pressure sensor rises above a threshold amount.

Abstract: Systems and methods are provided for recording video of a driver in a vehicle and a surrounding visual field of the driver. The system includes a detachable body coupled to a windshield of a vehicle. The system further includes three or more cameras coupled to the detachable body. The three or more cameras are configured to capture surrounding views from the detachable body. One of the three or more cameras faces a driver seat of the vehicle in response to the detachable body being coupled to the windshield of the vehicle. The video may be processed by the system, the cloud, or a combination of them.

Abstract: Systems and methods are provided for determining cause of atypical traffic events and/or encouraging good driving behavior. The systems and methods may involve a camera sensor and/or inertial sensors to detect traffic events, as well analytical methods that may attribute a cause to the traffic event. The systems and methods include a processor that is configured to determine an occurrence of an atypical traffic event at or near a monitored vehicle; and determine a cause of the atypical traffic event based on data collected at the monitored vehicle, wherein the cause of the atypical traffic event is at least one of: a driver or control system of the monitored vehicle; a second driver or second control system of a second vehicle; and a road condition.

Abstract: Systems and methods are provided for distributed video storage and search with edge computing. The method may comprise caching a first portion of data on a first device. The method may further comprise determining, at a second device, whether the first device has the first portion of data. The determining may be based on whether the first piece of data satisfies a specified criterion. The method may further comprise sending the data, or a portion of the data, and/or a representation of the data from the first device to a third device.

Abstract: Systems and methods for curating video and other driving-related data for use in driver coaching, which may include selecting or ranking driving behaviors for coaching, selecting or ranking drivers for coaching, selecting or ranking video and other data to be used in coaching, preparing for, scheduling, and summarizing coaching sessions, matching the format of coaching to the behavior or person being coached, preventing unsafe driving situations, influencing job dispatch decisions based on safety scores, and/or reducing data bandwidth usage based on a determined coaching effectiveness of video data.

Abstract: Systems and methods for curating video and other driving-related data for use in driver coaching, which may include selecting or ranking driving behaviors for coaching, selecting or ranking drivers for coaching, selecting or ranking video and other data to be used in coaching, preparing for, scheduling, and summarizing coaching sessions, matching the format of coaching to the behavior or person being coached, preventing unsafe driving situations, influencing job dispatch decisions based on safety scores, and/or reducing data bandwidth usage based on a determined coaching effectiveness of video data.

Abstract: The present disclosure provides devices, systems and methods for mapping of traffic boundaries.

Abstract: Apparatus to treat an eye with an ophthalmic laser system comprises a patient interface having an annular retention structure to couple to an anterior surface of the eye. The retention structure is coupled to a suction line to couple the retention structure to the eye with suction. Liquid is added above the eye to act as a transmissive medium. A coupling sensor is coupled to the suction line to determine coupling of the retention structure to the eye. A separate pressure monitoring circuit having a much smaller volume than the suction line is connected to the annular retention structure to measure suction pressure therein. A system processor coupled to the monitoring pressure sensor includes instructions to interrupt firing of a laser when the pressure measured with a monitoring pressure sensor rises above a threshold amount.

Abstract: Systems and methods are provided for recording video of a driver in a vehicle and a surrounding visual field of the driver. The system includes a detachable body coupled to a windshield of a vehicle. The system further includes three or more cameras coupled to the detachable body. The three or more cameras are configured to capture surrounding views from the detachable body. One of the three or more cameras faces a driver seat of the vehicle in response to the detachable body being coupled to the windshield of the vehicle. The video may be processed by the system, the cloud, or a combination of them.

Abstract: Systems, devices and methods provide, implement, and use vision-based methods of sequence inference for a device affixed to a vehicle.

Abstract: Apparatus to treat an eye with an ophthalmic laser system comprises a patient interface having an annular retention structure to couple to an anterior surface of the eye. The retention structure is coupled to a suction line to couple the retention structure to the eye with suction. Liquid is added above the eye to act as a transmissive medium. A coupling sensor is coupled to the suction line to determine coupling of the retention structure to the eye. A separate pressure monitoring circuit having a much smaller volume than the suction line is connected to the annular retention structure to measure suction pressure therein. A system processor coupled to the monitoring pressure sensor includes instructions to interrupt firing of a laser when the pressure measured with a monitoring pressure sensor rises above a threshold amount.

Abstract: A neural network is configured to process image data captured by a vehicle-mounted camera. The neural network includes common processing layers (a trunk) and separate, parallelizable processing layers (branches). An object detection branch of the neural network is trained to detect objects that may be visible from the vehicle-mounted camera, such as cars, trucks, and traffic signs. A curve determination branch is trained to detect and parameterize salient curves, such as lane boundaries and road boundaries. The curve determination branch itself is configured with a trunk and branch architecture, having both common and separate processing layers. A first branch computes a likelihood that a curve is present in a given location of the image data and a second branch further localizes the curve within the given location if such a curve is present. Training of the different branches of the neural network may be decoupled.

Abstract: Systems and methods for curating video and other driving-related data for use in driver coaching, which may include selecting or ranking driving behaviors for coaching, selecting or ranking drivers for coaching, selecting or ranking video and other data to be used in coaching, preparing for, scheduling, and summarizing coaching sessions, matching the format of coaching to the behavior or person being coached, preventing unsafe driving situations, influencing job dispatch decisions based on safety scores, and/or reducing data bandwidth usage based on a determined coaching effectiveness of video data.

Abstract: Systems and methods are provided for recording video of a driver in a vehicle and a surrounding visual field of the driver. The system includes a detachable body coupled to a windshield of a vehicle. The system further includes three or more cameras coupled to the detachable body. The three or more cameras are configured to capture surrounding views from the detachable body. One of the three or more cameras faces a driver seat of the vehicle in response to the detachable body being coupled to the windshield of the vehicle. The video may be processed by the system, the cloud, or a combination of them.

Abstract: Systems and methods are provided for detecting a driving action that mitigates risk.

Abstract: A neural network is configured to process image data captured by a vehicle-mounted camera. The neural network includes common processing layers (a trunk) and separate, parallelizable processing layers (branches). An object detection branch of the neural network is trained to detect objects that may be visible from the vehicle-mounted camera, such as cars, trucks, and traffic signs. A curve determination branch is trained to detect and parameterize salient curves, such as lane boundaries and road boundaries. The curve determination branch itself is configured with a trunk and branch architecture, having both common and separate processing layers. A first branch computes a likelihood that a curve is present in a given location of the image data and a second branch further localizes the curve within the given location if such a curve is present. Training of the different branches of the neural network may be decoupled.

Abstract: Systems and methods are provided for determining cause of atypical traffic events and/or encouraging good driving behavior. The systems and methods may involve a camera sensor and/or inertial sensors to detect traffic events, as well analytical methods that may attribute a cause to the traffic event. The systems and methods include a processor that is configured to determine an occurrence of an atypical traffic event at or near a monitored vehicle; and determine a cause of the atypical traffic event based on data collected at the monitored vehicle, wherein the cause of the atypical traffic event is at least one of: a driver or control system of the monitored vehicle; a second driver or second control system of a second vehicle; and a road condition.

Abstract: Systems and methods are provided for detecting a driving action that mitigates risk.