An audio communication system for communication between vehicle occupants in a vehicle, including an image capturing device configured to monitor a first vehicle occupant, a processor configured to receive an image of the first vehicle occupant from the image capturing device and determine whether the first vehicle occupant is attracting attention from a second vehicle occupant, a first microphone associated to the first vehicle occupant configured to receive an audio input from the first vehicle occupant in response to the determination of the first vehicle occupant attracting the second vehicle occupant's attention, and a first speaker associated to the second vehicle occupant configured to activate an audio augmentation of the received audio input in the first speaker and output the augmented audio input.

Autonomous driving system methods and devices which trigger vehicular actions based on the monitoring of one or more occupants of a vehicle are presented. The methods, and corresponding devices, may include identifying a plurality of features in a plurality of subsets of image data detailing the one or more occupants; tracking changes over time of the plurality of features over the plurality of subsets of image data; determining a state, from a plurality of states, of the one or more occupants based on the tracked changes; and triggering the vehicular action based on the determined state.

Systems and methods monitor driver behavior for vehicular fleet management in a fleet of vehicles using driver-facing imaging device. The systems and methods herein relate generally to vehicular fleet management for enhancing safety of the fleet and improving the performance of the fleet drivers, and further relate to monitoring the operation of fleet vehicles using one or more driver-facing imaging devices disposed in the fleet vehicles for recording activities of the fleet drivers and their passengers, storing information relating to the monitored activities, selectively generating warnings related to the monitored activities, and reporting the monitored activities to a central fleet management system for use in enhancing the safety of the vehicles of the fleet and for helping to improve the performance of the fleet drivers.

A system includes an in-cabin sensor, a seatbelt routing zone module, and a seatbelt routing classification module. The in-cabin sensor is operable to generate an image of an occupant in a vehicle seat. The seatbelt routing zone module is configured to generate a seatbelt routing zone based on at least one of a size of the occupant in the image and a shape of the occupant. The seatbelt routing classification module is configured to determine whether a seatbelt is routed properly around the occupant based on whether the seatbelt is at least partially within the seatbelt routing zone.

Systems and methods for viewing, observing, and/or monitoring a second row of seats in a vehicle are provided. A camera can be disposed in the second row of seats, near the rear of the vehicle, and can be forward-facing or generally forward-facing. The camera can provide a live video feed to a display located on the instrument panel in the front row of the vehicle.

A unified imaging device used for detecting and classifying objects in a scene including motion and micro-vibrations by receiving a plurality of images of the scene captured by an imaging sensor of the unified imaging device comprising a light source adapted to project on the scene a predefined structured light pattern constructed of a plurality of diffused light elements, classifying object(s) present in the scene by visually analyzing the image(s), extracting depth data of the object(s) by analyzing position of diffused light element(s) reflected from the object(s), identifying micro-vibration(s) of the object(s) by analyzing a change in a speckle pattern of the reflected diffused light element(s) in at least some consecutive images and outputting the classification, the depth data and data of the one or more micro-vibrations which are derived from the analyses of images captured by the imaging sensor and are hence inherently registered in a common coordinate system.

Location polygons are defined along traffic lanes and parking spaces to facilitate determination of the location of a vehicle relative to features associated with the location polygons. The location polygons are used, in one application, to identity entrance and exit of a special toll lane along a roadway, and to ensure that the vehicle properly enters and exits the tolling lane.

A vehicle monitoring system includes at least one camera, and a server that is communicably connected to the camera and a client terminal. The camera captures an occupant's face of a vehicle entering an angle of view of the camera, and transmits a captured video to the server. The server acquires an analysis results of an attribute of the vehicle, an analysis result of the occupant's face, and an analysis result of the number of occupants based on the captured video, and accumulates the acquired analysis results as analysis results of the captured video, and sends the analysis result to the client terminal in correlation with a snapshot of the captured video.

Systems, methods and apparatuses to detect an item left in a vehicle and to generate an alert about the item. For example, a camera configured in a vehicle can be used to monitor an item associated with a user of the vehicle. The item as in an image from the camera can be identified and recognized using an artificial neural network. In response to a determination that the item recognized in the image is left in the vehicle after the user has exited the vehicle, an alert is generated to indicate that an item is in the vehicle but the user is leaving the vehicle.

A safety belt detection method, apparatus, computer device and computer readable storage medium are disclosed. The safety belt detection method includes the steps as follows. An image to be detected is obtained. The image to be detected is inputted into a detection network which includes a global dichotomous branch network and a grid classification branch network. A dichotomous result, which indicates whether a driver is wearing a safety belt and is output from the global dichotomous branch network, is obtained. A grid classification diagram, which indicates a position information of the safety belt and is output from the grid classification branch network, is obtained based on image classification. A detection result of the safety belt, indicating whether the driver is wearing the safety belt normatively, is obtained based on the dichotomous result and the grid classification diagram.