A system for monitoring a switchgear includes an infrared camera; a processing unit; and an output unit. The infrared camera acquires a first infrared image having a first number of pixels, and the processing unit determines a pixel in the first infrared image with a maximum temperature. The processing unit utilizes a second number less than the first number to determine a temperature interval for the first infrared image equal to a difference between the maximum temperature in the first infrared image and a threshold temperature in the first infrared image. The processing unit is configured to determine that a hot spot exists in the switchgear using the temperature interval for the first infrared image.

Systems, methods, and computer program products for recursive modifications are provided. An example imaging system includes a first infrared (IR) imaging device that generates first IR image data of a first field of view of the first IR imaging device at a first time and a computing device operably connected with the first IR imaging device. The computing device receives the first IR image data from the first IR imaging device and determines a first set of pixels and a second set of pixels from amongst a plurality of pixels associated with the first IR image data. The computing device further determines a first modification protocol for the first set of pixels and determines a second modification protocol for the second set of pixels. In response, the computing device generates a recursive modification input based upon the first and second modification protocols.

A method and apparatus for monitoring a human or animal subject in a room using video imaging of the subject and analysis of the video image to detect and quantify movement of the subject and to derive an estimate of vital signs such as heart rate or breathing rate. The method includes techniques for de-correlating global intensity variations such as sunlight changes, compensating for noise, eliminating areas not of interest in the image, and quickly and automatically finding regions of interest for detecting subject movement and estimating vital signs. A logic machine is used for interpreting detected movement of the subject, and an artificial neural network is used to calculate a confidence measure for the vital signs estimates from signal quality indices. The confidence measure may be used with a normal density filter to output estimates of the vital signs.

A method for using an object key to deprioritize processing of relative regions of images of an object includes capturing an image of an object to be tracked and selecting an object key of the object. The object key includes a portion of the object, the object key is attached to the object and is recognizable by an image capture device. The method includes calculating a relative size of the object key with respect to a size of the object and a location of the object key with respect to the object, and tracking one or more locations of the object from the relative size and location of the object with respect to the object key and by capturing a plurality of images of the object key at a resolution sufficient for tracking movement of the object key.

An illuminated sensor target includes a light source. Actuating the light source illuminates the sensor target. The illuminated sensor target is recognized by one or more sensors of a vehicle during a calibration process, and is used to calibrate the one or more sensors of the vehicle during the calibration process. The illuminated sensor target is illuminated during at least part of the calibration process, which may involve rotation of the vehicle about a turntable, with the illuminated sensor target positioned within a range of the turntable along with other sensors targets, which may also be illuminated.

A method for generating a multi-modal video dataset with pixel-wise hand segmentation is disclosed. To address the challenges of conventional dataset creation, the method advantageously utilizes multi-modal image data that includes thermal images of the hands, which enables efficient pixel-wise hand segmentation of the image data. By using the thermal images, the method is not affected by fingertip and joint occlusions and does not require hand pose ground truth. Accordingly, the method can produce more accurate pixel-wise hand segmentation in an automated manner, with less human effort. The method can thus be utilized to generate a large multi-modal hand activity video dataset having hand segmentation labels, which is useful for training machine learning models, such as deep neural networks.

A system for detecting an hotspots can include: at least one infrared imaging sensor; and an imaging analysis computer operably coupled with the at least one infrared imaging sensor. The imaging analysis computer can be configured to control any infrared imaging sensor and acquire infrared images therefrom at any rate and in any duration. The imaging analysis computer can be configured to analyze the infrared images in order to detect temperatures and identify hotspots. The temperature and hotspot information can be used to control a cooling system that can spray water on and around hotspots for temperature control.

A defect inspection device includes an ultrasonic probe, an image acquirer, a calculator, and a corrector. The ultrasonic probe acquires an ultrasonic image of an inspection object or a simulated inspection object. The image acquirer acquires an infrared image including a first region of the simulated inspection object or a second region of the inspection object. The calculator calculates a first correction value for correcting a coordinate deviation of the first region in the ultrasonic image and the infrared image with respect to a designed coordinate of the first region, or calculate a second correction value for correcting a coordinate deviation of the second region in the infrared image with respect to a designed coordinate of the second region. The corrector performs coordinate correction with the calculated first or second correction value for the ultrasonic image of the inspection object.

A radiometric camera having internal black body components and a method for calibrating a radiometric camera having internal black body components. A radiometric camera includes a detector, the detector further including a thermal detector configured to capture thermal images, wherein the thermal detector is pointed in a direction, wherein the radiometric camera is adapted to receive at least one black body element in front of the detector with respect to the direction of the thermal detector, the thermal detector having a plurality of portions including at least one first portion, wherein the at least one black body element affects radiation readings by the at least one first portion of a plurality of portions of the thermal detector when disposed in the radiometric camera.

An apparatus for analyzing a payload being transported in a load carrying container of a vehicle is disclosed. The apparatus includes a camera disposed to successively capture images of vehicles traversing a field of view of the camera. The apparatus also includes at least one processor in communication with the camera, the at least one processor being operably configured to select at least one image from the successively captured images in response to a likelihood of a vehicle and load carrying container being within the field of view in the at least one image, and image data associated with the least one image meeting a suitability criterion for further processing. The further processing includes causing the at least one processor to process the selected image to identify a payload region of interest within the image and to generate a payload analysis within the identified payload region of interest based the image data associated with the least one image.