Abstract: Systems, methods, and non-transitory computer-readable media can access a plurality of parameter-based encodings providing a structured representation of an environment captured by one or more sensors associated with a plurality of vehicles traveling through the environment. A given parameter-based encoding of the environment identifies one or more agents that were detected by a vehicle within the environment and respective location information for the one or more agents within the environment. The plurality of parameter-based encodings can be clustered into one or more clusters of parameter-based encodings. At least one scenario associated with the environment can be determined based at least in part on the one or more clusters of parameter-based encodings.

Abstract: Systems, methods, and non-transitory computer-readable media can access a plurality of parameter-based encodings providing a structured representation of an environment captured by one or more sensors associated with a plurality of vehicles traveling through the environment. A given parameter-based encoding of the environment identifies one or more agents that were detected by a vehicle within the environment and respective location information for the one or more agents within the environment. The plurality of parameter-based encodings can be clustered into one or more clusters of parameter-based encodings. At least one scenario associated with the environment can be determined based at least in part on the one or more clusters of parameter-based encodings.

Abstract: Systems, methods, and non-transitory computer-readable media can receive a query specifying at least one example scenario. At least one image representation of the at least one example scenario can be encoded based on the query to produce at least one encoded representation. An embedding of the at least one representation of the at least one example scenario can be generated based on the at least one encoded representation. At least one scenario that is similar to the at least one example scenario can be identified based at least in part on the embedding of the at least one representation of the at least one example scenario and an embedding representing the at least one scenario. Information describing the at least one identified scenario can be provided in response to the query.

Abstract: Systems, methods, and non-transitory computer-readable media can access a plurality of parameter-based encodings providing a structured representation of an environment captured by one or more sensors associated with a plurality of vehicles traveling through the environment. A given parameter-based encoding of the environment identifies one or more agents that were detected by a vehicle within the environment and respective location information for the one or more agents within the environment. The plurality of parameter-based encodings can be clustered into one or more clusters of parameter-based encodings. At least one scenario associated with the environment can be determined based at least in part on the one or more clusters of parameter-based encodings.

Abstract: Systems, methods, and non-transitory computer-readable media can determine sensor data captured by at least one sensor of a vehicle while navigating an environment over a period of time. Information describing one or more agents associated with the environment during the period of time can be determined based at least in part on the captured sensor data. A parameter-based encoding describing the one or more agents associated with the environment during the period of time can be generated based at least in part on the determined information and a scenario schema, wherein the parameter-based encoding provides a structured representation of the information describing the one or more agents associated with the environment. A scenario represented by the parameter-based encoding can be determined based at least in part on a cluster of parameter-based encodings to which the parameter-based encoding is assigned.

Abstract: A page layout module receives a page image displaying text in an unknown script and unknown orientation, determines a text section in the received image and transmits the text section to an orientation and script module. The orientation and script module comprises a training module, a classifier and a recognition module. The training module trains the classifier to identify connected components that include a connected portion of one or more characters of text. The recognition module uses the trained classifier to identify in the received text section a set of connected components. The recognition determines the likely orientation and script for the connected components and then uses the determined information to determine the orientation and script for the text section. The determined orientation and script for the text section is transmitted to the OCR module. The OCR module uses the determined orientation and script to recognize text in the text section.

Abstract: A security device for identifying a person makes two images of a person to detect spoofing. The first image is a conventional visible image and the second image is an infrared image. Both images are analyzed to determine whether they represent a real person or not. If a placard or active display device is presented to the security device to spoof the real person, the infrared image of the placard or display device is recognized not to have the same characteristics as the infrared image of a real person.