Re-Identification of physical objects in an image background is made possible by the use of temporary data objects (i.e., video cookies). Image data including an image object representing a physical object in at least one of a plurality of backgrounds is pre-stored in a database. Identification data for the image object and image background data is extracted from the image object and a comparison is made to determine if the identification data matches identification data in the database. In the event no match is found, a temporary data object is created and stored in the database that links the identification data and the image background data. If an identification data match is found, it is determined whether a temporary data object exists in the database. If no temporary data object exists, one is created and stored in the database. If a temporary data object is determined to exist in the database, it is determined whether the temporary data object fulfills a predetermined condition(s). If the predetermined condition(s) is not fulfilled, a default action is executed and if the predetermined condition(s) are fulfilled, a specific action is executed.

A video recommendation method is provided, including: inputting a video to a first feature extraction network, performing feature extraction on at least one consecutive video frame in the video, and outputting a video feature of the video; inputting user data of a user to a second feature extraction network, performing feature extraction on the discrete user data, and outputting a user feature of the user; performing feature fusion based on the video feature and the user feature, and obtaining a recommendation probability of recommending the video to the user; and determining, according to the recommendation probability, whether to recommend the video to the user.

A computer system for verifying information relating to an event. The computer system includes a network interface and a processor to receive a media feed containing information related to a potential event, identify the potential event and determine a location of the potential event from the information in the media feed, and solicit verification of information relating to the potential event from a set of responder devices of a plurality of responder devices. Each responder device of the set of responder devices has a location-tracking device, and each responder device of the set of responder devices is selected from a pool of responder devices in a vicinity of the potential event. The processor is further to determine whether information in the media feed is verified by verification solicited from the set of responder devices and output the determination.

A computer vision card reader and/or point of sale device is described. The device is configured to sense when a user inserts a card into a card reader and to determine when a user departs or is about to depart from the device without retrieving the card. The device may issue an audible or visible alert to the user, reminding the user to retrieve the card. The device may additionally send a notification to a mobile device associated with the user that reminds the user that he has left a card at the point of sale. In some embodiments, message sent to the user contains a code and, upon entry of the code, the point of sale or card reader device returns the card to the user.

A method for intelligently measuring vehicle speed based on a binocular stereo vision system includes: training a Single Shot Multibox Detector neural network to obtain a license plate recognition model; calibrating the binocular stereo vision system to acquire parameters of two cameras; detecting the license plates in the captured video frames with the license plate recognition model, locating the license plate position; performing feature point extraction and stereo matching by a feature-based matching algorithm; screening and eliminating the matching point pairs, and reserving the coordinates of the matching point pair closest to the license plate center; performing stereo measurement on the screened matching point pair to get the spatial coordinates of the position; calculating and obtaining the speed of the target vehicle. The present invention is easy to install and adjust, could simultaneously recognize multiple trained features automatically, and better suit the intelligent transportation networks and IoT (Internet of Things).

A computer-implemented method can include receiving, by a computing system including one or more computing devices, data describing a media content item that includes a plurality of image frames for sequential display. The method can include inputting, by the computing system, the data describing the media content item into a machine-learned temporal analysis model that is configured to receive the data describing the media content item, and in response to receiving the data describing the media content item, output temporal analysis data that describes temporal information associated with sequentially viewing the plurality of image frames of the media content item. The method can include receiving, by the computing system and as an output of the machine-learned temporal analysis model, the temporal analysis data.

Provided are an alarm method and apparatus for a tabletop game, an electronic device and a storage medium. The method includes that: at least one frame of game tabletop image collected in a prop operation stage of a game is acquired; for each frame, a placement position of a preset identity object in the game tabletop image is detected, a tabletop of the game including a placement region corresponding to each game party, and the preset identity object being configured to identify a first game party allowed to operate a game prop; a second game party corresponding to the placement position of the preset identity object is determined according to the placement region corresponding to each game party; and in a case where the first game party is inconsistent with the second game party, alarm information for characterizing a placement error of the preset identity object is output.

A method includes: aggregating information from a corresponding combination of all of multi-scale first dimensional receptive fields and each of multi-scale second dimensional receptive fields, so that information from multi-scale first and second dimensional receptive fields corresponding to the multi-scale second dimensional receptive fields is obtained; wherein the multi-scale first dimensional receptive fields being first dimensional is being one of spatial and temporal, and the multi-scale second dimensional receptive fields being second dimensional is being the other of spatial and temporal; wherein a corresponding first convolutional neural network operation set provides each of the multi-scale second dimensional receptive fields and each operation of the first convolutional neural network operation set has a corresponding first dimensional local to local constraint; and aggregating the information from the multi-scale first and second dimensional receptive fields to obtain aggregated multi-scale first and second dimensional receptive field information.

This application provides a video information generation method, apparatus, and system and a storage medium. The video information generation method includes: obtaining a plurality of temporally consecutive target images; obtaining first information of a target object in the target images; and associating first information of a same target object located in different target images to generate target information. In the video information generation method provided in this application, the first information of the target object in the target images is obtained, and the first information of the same target object located in different target images is associated. In this way, target information with a relatively small amount of data can be obtained, thereby improving the efficiency of remotely viewing a video by a user.

Embodiments of the present application provide an object information association method and apparatus, a device and a storage medium. The method includes that: based on a video stream of an object operation region, a first object and a second object that are mutually associated are detected in the object operation region; first object information of the first object is determined; the second object is matched with a preset second object in a preset second object library; in a case where the second object fails to be matched with the preset second object, a request for acquiring second object information of the second object is sent; and in a case where the second object information sent in response to the request is received, the first object information is associated with the received second object information.