A system for monitoring vehicle traffic may include a camera positioned to capture images within a license plate detection zone, the images may represent license plates of vehicles. The system may include an electronic device identification sensor that detects and stores electronic device identifiers of electronic devices located within an electronic device detection zone, and a computing system that detects, using the images, a license plate ID of a vehicle, compare the license plate ID of the vehicle to a database of trusted vehicle license plate IDs, identifies the vehicle as a suspicious vehicle, the identification based at least in part on the comparison of the license plate ID of the vehicle to the database of trusted vehicle license plate IDs, and correlates the license plate ID of the vehicle with at least one of the plurality of stored electronic device identifiers.

The technology provides a sign detection and classification methodology. A unified pipeline approach incorporates generic sign detection with a robust parallel classification strategy. Sensor information such as camera imagery and lidar depth, intensity and height (elevation) information are applied to a sign detector module. This enables the system to detect the presence of a sign in a vehicle's externa environment. A modular classification approach is applied to the detected sign. This includes selective application of one or more trained machine learning classifiers, as well as a text and symbol detector. Annotations help to tie the classification information together and to address any conflicts with different the outputs from different classifiers. Identification of where the sign is in the vehicle's surrounding environment can provide contextual details. Identified signage can be associated with other objects in the vehicle's driving environment, which can be used to aid the vehicle in autonomous driving.

In one embodiment, a method includes receiving, by a XR display device, a gesture-based input from a first user of the XR display device, processing, using a gesture-detection model, the gesture-based input to identify a first gesture, receiving, by the XR display device, an audio input from the first user, where the audio input includes a first voice command, processing, using a natural-language model, the audio input to identify one or more intents or one or more slots associated with the first voice command, determining whether the identified first gesture matches the first voice command, and executing, responsive to the identified first gesture matching the first voice command and by the XR display device, a first task corresponding to the first voice command based on the identified first gesture and the identified one or more intents or one or more slots.

Systems and methods of processing crowdsourced navigation information for use in autonomous vehicle navigation are disclosed. A method may include processing, by a mapping server, crowdsourced navigation information from a plurality of vehicles obtained by sensors coupled to the plurality of vehicles, wherein the navigation information describes road lanes of a road segment; collecting data about landmarks identified proximate to the road segment, the landmarking including a traffic sign; generating, by the mapping server, an autonomous vehicle map for the road segment, wherein the autonomous vehicle map includes a spline corresponding to a lane in the road segment and the landmarks identified proximate to the road segment; and distributing, by the mapping server, the autonomous vehicle map to an autonomous vehicle for use in autonomous navigation over the road segment.

This invention identifies vehicles on arrival, and matches exiting vehicles to their corresponding entry event. The matching process uses primarily optical inputs. The system uses at least one camera to capture not only the vehicle license plate but also the visual features. A “signature” formed out of the optical features of the vehicle is compared against the pre-generated signatures of vehicles in a whitelist, and the best match is identified. The “signature” for each exiting vehicle is compared against all signatures of vehicles that entered the garage. A plurality of filters reduce the possible matching candidates based on factors like license plate based edit distance, location information of vehicle owner. Synchronizing a database in each local processing unit (LPU) with a central database enables signature from images from sites that have good license plate reads, to assist in authentication in other sites where the reads are lower quality.

A method of price text detection by an imaging controller comprises obtaining, by the imaging controller, an image of a shelf supporting labels bearing price text, generating, by the imaging controller, a plurality of text regions containing candidate text elements from the image, assigning, by the imaging controller, a classification to each of the text regions, selected from a price text classification and a non-price text classification. The imaging controller, within each of a subset of the text regions having the price text classification: detects a price text sub-region and generates a price text string by applying character recognition to the price text sub-region. The method further includes presenting, by the imaging controller, the locations of the subset of text regions, in association with the corresponding price text strings.

A system and method for sending an image to a user device based on the context of a user of the device are provided. An image to be sent to a user device may be obtained. The context of the user may be determined. The image may be analyzed to detect and prioritize objects in the image based on the context of the user. The image may be encoded such that objects are rendered on the user device in an order based on the prioritization. The encoded image may be sent to the user device.

The present application discloses an image processing method, apparatus, electronic device and computer readable storage medium. The image processing method comprises detecting a text region in an image to be processed, recognizing the text region to obtain a text recognition result. In this application, the text recognition in the image to be processed is realized, the recognition manner for the text in the image is simplified, and the recognition effect for the text is improved.

A system capable of determining which recognition algorithms should be applied to regions of interest within digital representations is presented. A preprocessing module utilizes one or more feature identification algorithms to determine regions of interest based on feature density. The preprocessing modules leverages the feature density signature for each region to determine which of a plurality of diverse recognition modules should operate on the region of interest. A specific embodiment that focuses on structured documents is also presented. Further, the disclosed approach can be enhanced by addition of an object classifier that classifies types of objects found in the regions of interest.

An information processing apparatus includes a control unit configured to generate display control information used as information regarding display control of a display image corresponding to scene information indicating a scene of a seminar.