A device, method and system for estimating elevation in images from camera devices is provided. The device detects humans at respective positions in images from a camera device, the camera device having a fixed orientation and fixed focal length. The device estimates, for the humans in the images, respective elevations of the humans, relative to the camera device, at the respective positions based at least on camera device parameters defining the fixed orientation and the fixed focal length. The device associates the respective elevations with the respective positions in the images. The device determines, using the respective elevations associated with the respective positions, a function that estimates elevation in an image from the camera device, using a respective image position coordinate as an input. The device provides the function to a video analytics engine to determine relative real-world positions in subsequent images from the camera device.

A method, computer program product, and computing system for proactive encounter scanning is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is proactively processed to determine if the encounter information is indicative of one or more medical conditions and to generate one or more result set. The one or more result sets are provided to the user.

Apparatus and methods are disclosed for detecting motion between two subassemblies, for example in or near a litter box. A first subassembly includes a first frame adapted for supporting a receptacle. A second subassembly includes a second frame adapted for resting on a steady surface. Connecting members connect the subassemblies such that relative movement between them can occur. At least a first position indicating member is attached to one the subassemblies and at least a first detector is attached to the other of the subassemblies. The detector is positioned proximate the first position indicating member so that changes in relative position are detected. Preferably, the device includes a second position indicating member and a second detector for detecting more precise changes in relative position. It is also preferred for each position indicating member to include a patterned marker.

A computer-readable medium storing contents configured to cause a computing device to obtain image data describing a subject, measure the subject based on the obtained image data to obtain one or more spatial dimensions, and access data describing a wearable item based on the spatial dimensions of the subject.

Systems and methods for improved operations of ski lifts increase skier safety at on-boarding and off-boarding locations by providing an always-on, always-alert system that “watches” these locations, identifies developing problem situations, and initiates mitigation actions. One or more video cameras feed live video to a video processing module. The video processing module feeds resulting sequences of images to an artificial intelligence (AI) engine. The AI engine makes an inference regarding existence of a potential problem situation based on the sequence of images. This inference is fed to an inference processing module, which determines if the inference processing module should send an alert or interact with the lift motor controller to slow or stop the lift.

There is provided an image processing system and method for identifying a user. The system comprises a processor configured to identify a first user in an image, determine a plurality of characteristic vectors associated with the first user, compare the characteristic vectors associated with the first user with a plurality of predetermined characteristic vectors associated with a plurality of users including the first user, and identify the first user based on the comparison.

Provided are a device and a method which enable easy analysis and evaluation of work efficiency of a worker without burdensome tasks and easy determination of a worker's skill level by comparing the worker's work efficiency status with that of another worker or a past record of the same worker, wherein analytical information is produced by estimating the worker's joint positions based on a video; acquiring time series data on joint positions; determining work efficiency based on the time series data; acquiring a target range (part of a work process with low work efficiency); output an image of the target range overlaid on a graph of the time series data; and output a posture image of the worker overlaid on the video. The analytical information may include information on a working activity to be analyzed and information on a chosen model working activity with high work efficiency.

Present disclosure provides a method for determining if an event relates to an unauthorized subject, the method comprising: determining a likelihood of how the event is similar to at least one of: (i) at least one event of a list of events relating to the unauthorized subject and (ii) at least one of a list of events relating to an authorized subject, each event of the list of events comprising data identifying the unauthorized subject, the determination of likelihood being based on the data identifying the unauthorized subject; and determining the event to relate to the unauthorized subject in response to the determination of the likelihood.

A monitoring device is configured to include an image data acquiring unit, a detecting unit, and a notifying unit. The image data acquiring unit acquires image data obtained by imaging a work area, and information relating to the position in which the image data were captured. The detecting unit detects, from the image data, at least either an unsafe behavior of a worker in the work area, or an unsafe environment around the worker, as an unsafe condition. The notifying unit notifies a terminal of the unsafe condition detected by the detecting unit, and the information relating to the position in which the unsafe condition is detected.

Example systems perform complex optimization tasks with improved efficiency via neural meta-optimization of experts. In particular, provided is a machine learning framework in which a meta-optimization neural network can learn to fuse a collection of experts to provide a predicted solution. Specifically, the meta-optimization neural network can learn to predict the output of a complex optimization process which optimizes over outputs from the collection of experts to produce an optimized output. In such fashion, the meta-optimization neural network can, after training, be used in place of the complex optimization process to produce a synthesized solution from the experts, leading to orders of magnitude faster and computationally more efficient prediction or problem solution.