Teledyne Flir Commercial Systems, Inc.

Teledyne Flir, LLC

James Klingshirn

Pierre M Boulanger

Louis Tremblay

Justin Muncaster

Nicholas Högasten

Theodore R Hoelter

Katrin Strandemar

Austin A Richards

Jeremy P Walker

Giovanni Lepore

John C Day

Dylan M Rodriguez

Hugo Hedberg

Kedar Babu Madineni

Tien Nguyen

Robert Proebstel

Brower A Dimond, Jr

Rasmus Loman

Fredrik Gihl

Karl Rydqvist

Eugene Pochapsky

Systems and methods include an image capture component configured to capture infrared images of a scene, and a logic device configured to identify a target in the images, acquire temperature data associated with the target based on the images, evaluate the temperature data and determine a corresponding temperature classification, and process the identified target in accordance with the temperature classification. The logic device identifies a person and tracks the person across a subset of the images, identify a measurement location for the target in a subset of the images based on target feature points identified by a neural network, and measure a temperature of the location using corresponding values from one or more captured thermal images. The logic device is further configured calculate a core body temperature of the target using the temperature data to determine whether the target has a fever and calibrate using one or more black bodies.

Non-contact temperature measurement in thermal imaging systems and methods

High resolution image target classification systems and methods include a proposal component configured to receive a first set data associated with a scene, the first set of data including at least one image of the scene, a multistage neural network comprising a plurality of neural networks, each neural network trained to receive a region of interest and output an object classification in accordance with an associated resource allocation, and an attention coordinator configured to determine regions of interest in the image and allocate each determined region to one of the plurality of neural networks from the multi-scale neural network, in accordance with available system resources. The system may be configured to optimize a probability of detecting objects in the image, while minimizing a number of pixels processed through the multi-scale neural network.

Neural network and classifier selection systems and methods

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Goleta, CA, United States of America

James Klingshirn