Lockheed Martin Corporation

General Electric Company

Lockheed Martin Company

GianFranco Doretto

Peter Henry Tu

Jens Rittscher

Thomas Baby Sebastian

Nils Oliver Krahnstoever

Xiaogang Wang

Christopher Donald Johnson

Jeffrey Michael Ashe

Andrew Day

Kai Erik Thomenius

Xiaoming Liu

Kunter Seref Akbay

Ting Yu

David Toledano

Onur Ilkin Dulgeroglu

John Charles Hill, Jr

Marcia Peterson

Kenneth R Turner

Perera Ambalangoda

A system and method to manage delivery of healthcare via a plurality of resources to a patient is provided. The system and method track and output a signal representative of a location of at least one of a series of resources relative to a control volume associated with the patient, acquire at least one signal representative of detecting ingress or egress of at least one of the plurality of resources relative to the control volume; and output a first signal representative of one of a series of milestones as defined in a predetermined protocol in response to detecting ingress or egress of at least one of the resources relative to the control volume.

System and method to manage delivery of healthcare to a patient

A device and method for processing an image to create appearance and shape labeled images of a person or object captured within the image. The appearance and shape labeled images are unique properties of the person or object and can be used to re-identify the person or object in subsequent images. The appearance labeled image is an aggregate of pre-stored appearance labels that are assigned to image segments of the image based on calculated appearance attributes of each image segment. The shape labeled image is an aggregate of pre-stored shape labels that are assigned to image segments of the image based on calculated shape attributes of each image segment. An identifying descriptor of the person or object can be computed based on both the appearance labeled image and the shape labeled image. The descriptor can be compared with other descriptors of later captured images to re-identify a person or object.

Identifying descriptor for person and object in an image

Identifying descriptor for person or object in an image

Aspects of the disclosure provide a method for crowd segmentation that can globally optimize crowd segmentation of an input image based on local information of the input image. The method can include receiving an input image of a site, initializing a plurality of hypothesis based on the input image, dividing the input image into a plurality of patches, calculating an affinity measure of one or more patches to a hypothesis based on a partial response of the patches to a whole body classifier of the hypothesis that includes a combination of weak classifiers, and optimizing assignments of the plurality of patches to the plurality of hypothesis based on the affinity measures of the plurality of patches to the plurality of hypothesis.

Method and system for crowd segmentation

A system for detecting and tracking targets captured in images, such as people and object targets that are captured in video images from a surveillance network. Targets can be detected by an efficient, geometry-driven approach that determines likely target configuration of the foreground imagery based on estimated geometric information of possible targets. The detected targets can be tracked using a centralized tracking system.

Detecting and tracking targets in images based on estimated target geometry

A device and method for detecting targets of interest in an image, such as people or objects of a certain type. Targets are detected based on an optimized strong classifier descriptor that can be based on a combination of weak classifier descriptors. The weak classifier descriptors can include a user-defined weak classifier descriptor that is defined by a user to represent a shape or appearance attribute that is characteristic of parts of the target of interest. The strong classifier descriptor can be optimized by selecting a subset of weak classifier descriptors that exhibit improved performance in detecting targets in training images.

Device and method for detecting targets in images based on user-defined classifiers

A device and method for efficient computation of statistical information, such as a mean, co-variance, or histogram of the image pixels, over discrete image regions. The computation employs integral computations to determine the statistical information over image regions of arbitrary shape, including irregular polygonal shaped regions. The integral computations are simplified by categorizing corner points of boundaries of image regions. The computation can be applied to calculate descriptors or signatures of persons or objects within an image. The computation also has a low computational cost enabling fast calculation of image statistics.

Device and method for fast computation of region based image features

Embodiments of the invention include a system and a method for determining whether a person is carrying concealed contraband, such as an improvised explosives device or other weapon. The system includes a people tracking video subsystem, a people tracking decisioning subsystem, a concealed contraband detection aiming subsystem, and a concealed contraband detection decisioning subsystem.

Standoff detection systems and methods

A method for re-identifying an image is provided. The method comprises obtaining a plurality of images and generating a correspondence map between the plurality of images. The method further comprises defining a plurality of region signatures for one or more regions comprising the plurality of images and comparing the plurality of images based on the correspondence map and the plurality of region signatures to perform image re-identification.

Growing community of inventors

Albany, NY, United States of America

GianFranco Doretto