Described herein are heating, ventilation, air conditioning, and refrigeration (HVACR) systems and methods directed to indoor air quality. HVACR systems and methods are based on dynamic people modeling to simulate and/or to monitor airflow impact on pathogen spread in an indoor space. HVACR systems and methods model an indoor space with pathogen killing technology to deploy the pathogen killing technology. HVACR systems and methods are directed to control administration of a pathogen killing technology to an indoor space based on factors that impact airflow including from dynamic analytics, a known input, and/or detection.

Systems and methods are described for using data collected by unmanned aerial vehicles (UAVs) to generate insurance claim estimates that an insured individual may quickly review, approve, or modify. When an insurance-related event occurs, such as a vehicle collision, crash, or disaster, one or more UAVs are dispatched to the scene of the event to collect various data, including data related to vehicle or real property (insured asset) damage. With the insured's permission or consent, the data collected by the UAVs may then be analyzed to generate an estimated insurance claim for the insured. The estimated insurance claim may be sent to the insured individual, such as to their mobile device via wireless communication or data transmission, for subsequent review and approval. As a result, insurance claim handling and/or the online customer experience may be enhanced.

Systems and methods are provided for identifying a key instrument in an event. One example method includes receiving a capture of the event and identifying, at a first computing device, the event. The key instrument is identified at the first computing device. An indicator to apply to and/or around the identified key instrument is generated for display.

An image processing method is provided. The method includes acquiring a video. The method includes using an object detection engine to detect a person in the video. The object detection engine is integrated with an image signal processing pipeline. The method includes transmitting the video over a network. The method includes determining that the detected person has moved less than a pre-set distance. The method includes, responsive to the determining, pausing transmission of the video. An embedded image processor including an object detection engine is also provided.

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.

A spatial indexing system receives a video that is a sequence of frames depicting an environment, such as a floor of a construction site, and performs a spatial indexing process to automatically identify the spatial locations at which each of the images were captured. The spatial indexing system also generates an immersive model of the environment and provides a visualization interface that allows a user to view each of the images at its corresponding location within the model.

Disclosed herein are systems and methods for presenting an audio signal associated with presentation of a virtual object colliding with a surface. The virtual object and the surface may be associated with a mixed reality environment. Generation of the audio signal may be based on at least one of an audio stream from a microphone and a video stream form a sensor. In some embodiments, the collision between the virtual object and the surface is associated with a footstep on the surface.

The present invention provides a processing apparatus (10) including: an object region detection unit (11) that detects, from an image, an object region being a region including an object; a reliability computation unit (12) that computes, for each product, reliability in which each of the products is included in an image of the object region; an image parameter computation unit (13) that computes an image parameter related to an image of the object region; a threshold value setting unit (14) that sets a threshold value of the reliability, based on the image parameter; and a product determination unit (15) that determines, based on the reliability of each of the products and the threshold value, the product included in an image of the object region.

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 recording system includes a recording data acquisition unit, an analysis unit, a learning unit, and a determination unit. The recording data acquisition unit acquires recording data in which a surrounding situation of a vehicle is recorded. The analysis unit performs image analysis processing on video data included in the recording data to create information regarding a transition of a color component in the video data. The learning unit learns the transition of the color component using artificial intelligence to create a trained model used to determine an occurrence of an event. The determination unit determines whether an event occurs using the trained model on a basis of the recording data. When the determination unit determines the occurrence of the event, the event recording control unit causes a recording unit to record, as event recording data, the recording data including a time point upon the occurrence of the event.