Localization of a user device in a mixed reality environment in which the user device obtains at least one keyframe from a server, which can reside on the user device, displays at least one of the keyframes on a screen, captures by a camera an image of the environment, and obtains a localization result based on at least one feature of at least one keyframe and the image.

A scratchpad creation method and an electronic device are disclosed. The method includes: receiving a first input performed by a user on a target identifier, where the target identifier is associated with a first video file; and displaying a first scratchpad in response to the first input, where the first scratchpad is a scratchpad created based on content of the first video file, the first scratchpad includes at least one video identifier and at least one progress identifier, the video identifier is used to indicate a video clip in the first video file, and the progress identifier is used to indicate completion progress of an operation corresponding to the video clip.

The presented invention includes the generation of cloud points, the identification of objects in the cloud points, and, in this case, finding the positions of objects in cloud points. In addition, the invention includes capturing images, data streaming, and digital image processing in different points of the system, and calculation of the position of objects. The invention includes the usage of cameras of mobile smart devices, smart glasses, 3D cameras, but not necessarily. The data streaming provides video streaming and sensor data streaming from mobile smart devices. The presented invention further includes cloud points of buildings in which the positioning of separated objects could be implemented. It also consists of the database of cloud points of isolated objects which help to calculate the position in the building. Finally, the invention comprises the method of objects feature extraction, comparing in the cloud points and position calculation.

Systems, computer-readable media, methods, and approaches described herein may identify delivery and/or pickup of packages. For example, packages may be identified within the areas captured by images and/or video. Based on the identification of the packages, it may be determined whether the package was delivered or picked up. A notification may be initiated that indicates that a package has been delivered and/or picked up.

One or more highlights of a video stream may be identified. The highlights may be segments of a video stream, such as a broadcast of a sporting event, that are of particular interest to one or more users. According to one method, at least a portion of the video stream may be stored. The portion of the video stream may be compared with templates of a template database to identify the one or more highlights. Each highlight may be a subset of the video stream that is deemed likely to match the one or more templates. The highlights, an identifier that identifies each of the highlights within the video stream, and/or metadata pertaining particularly to the one or more highlights may be stored to facilitate playback of the highlights for the users.

An electronic apparatus is provided. The electronic apparatus includes: a camera; a processor configured to control the camera; and a memory configured to be electrically connected to the processor and to store a network model trained to determine a degree of matching between an input image frame and predetermined feature information, wherein the memory stores at least one instruction, and wherein the processor is configured, by executing the at least one instruction, to: identify a representative image frame based on a degree of matching obtained by applying image frames, selected from among a plurality of image frames, to the trained network model, while the plurality of image frames are captured through the camera, identify a best image frame based on a degree of matching obtained by applying image frames within a specific section including the identified representative image frame, to the trained network model, from among the plurality of image frames, and provide the identified best image frame.

A server includes a processor programmed to: acquire first metadata of a first media file recorded by a first mobile device; acquire second metadata of a second media file recorded by a second mobile device; determine that the first media file and the second medial file are likely recordings of the same event when a similarity exceeds a first threshold. The processor is further programmed to, when the first media file and the second medial file are likely recordings of the same event: determine, based on a comparison between the first media file and the second media file, which of the first media file and the second media file is a higher quality recording of the same event; and when the first media file is the higher quality recording, send a link to the first media file to the second mobile device.

An information processing apparatus acquires editing target image data including video image data, acquires first display image data of a plurality of frames, generates second display image data of a plurality of frames determined in accordance with the number of frames of the first display image data from the editing target image data, and displays display images of a plurality of frames indicated by the second display image data of the plurality of frames on a display. The editing target image data and the first display image data of the plurality of frames are image data having a common attribute. The second display image data of the plurality of frames includes second display image data for video images of a plurality of frames corresponding to still image data of a plurality of frames constituting at least a part of the video image data.

The disclosure relates to a method for warehouse storage-location monitoring, a computer device, and a storage medium. The method includes the following. Video data of a warehouse storage-location area is obtained, and a target image corresponding to the warehouse storage-location area is obtained based on the video data, where the warehouse storage-location area includes an area of a storage-location and an area around the storage-location. The target image is detected based on a category detection model, to determine a category of each object appearing in the target image, where the category includes at least one of: human, vehicle, or goods. A detection result is obtained by detecting a status of each object based on the category of each object, where the detection result includes at least one of: whether the human enters the warehouse storage-location area, vehicle status information, or storage-location inventory information. The detection result is transmitted to a warehouse scheduling system, where the detection result is used for the warehouse scheduling system to monitor the warehouse storage-location area.

A quantum computing based video alert system converts captured video and audio signals, in real time, into a sequence of video qubits and a sequence of audio qubits. An entanglement score is generated based on a comparison of the video qubits to historical video qubits that are verified to show malicious activity. A second entanglement score is generated based on a comparison of the audio qubits to historical audio qubits that are verified to show malicious activity. A probability score is generated for each segment of the video qubit sequence and for each segment of the audio qubit sequence. If the probability score for the video qubit sequence, the audio qubit sequence, or a combination of probability scores for both the video qubit sequence and the audio qubit sequence meet a threshold, then an alert is generated to identify possible malicious activity at the location of a CCTV camera capturing the real-time data.