Abstract: Aspects of the present disclosure include a method, a system, and/or a non-transitory computer readable medium for receiving a plurality of images of a parking facility, receiving one or more natural language inputs from a client for operating the parking facility, generating one or more natural language follow-up questions based on the one or more natural language inputs, providing the one or more natural language follow-up questions to the client, receiving, in response to the one or more natural language follow-up questions, one or more natural language answers, and performing one or more actions associated with the parking facility based on at least one of the one or more natural language inputs and at least one of the one or more natural language answers.

Abstract: Aspects of the present disclosure include a method, a system, and/or a non-transitory computer readable medium for identifying an event, comprising receiving a plurality of images, receiving a natural language question from a client to identify the event, and generating one or more natural language follow-up questions based on the natural language question. The method, system, and/or non-transitory computer readable medium further comprises providing the one or more natural language follow-up questions to the client, and receiving, in response to the one or more natural language follow-up questions, one or more natural language answers. The method, system, and/or non-transitory computer readable medium further comprises identifying the event from the plurality of images based on at least one of the one or more natural language answers.

Abstract: Example implementations include a method, apparatus and computer-readable medium in a video surveillance system for tracking an of-interest (OI) object, comprising receiving, from a user interface, a request to track an object in a first video stream from a plurality of video streams captured from a first camera of a plurality of cameras installed in an environment. The implementations further include extracting at least one image of the object from the first video stream. Additionally, the implementations further include generating a unique biometric identifier of the object based on the at least one image. Additionally, the implementations further include detecting, using the unique biometric identifier, the object in a second video stream captured from a second camera of the plurality of cameras, and outputting, on the user interface, the second video stream in response to detecting the object in the second video stream.

Abstract: Example implementations include a method, apparatus and computer-readable medium in a video surveillance system for tracking an of-interest (OI) object, comprising receiving, from a user interface, a request to track an object in a first video stream from a plurality of video streams captured from a first camera of a plurality of cameras installed in an environment. The implementations further include extracting at least one image of the object from the first video stream. Additionally, the implementations further include generating a unique biometric identifier of the object based on the at least one image. Additionally, the implementations further include detecting, using the unique biometric identifier, the object in a second video stream captured from a second camera of the plurality of cameras, and outputting, on the user interface, the second video stream in response to detecting the object in the second video stream.