Northrop Grumman Systems Corporation

Vioptix, Inc.

Schlumberger Technologies, Inc.

Wink Robotics

Schlumberger Systems & Services, Inc.

Alara, Inc.

Other

Intel Corporation

Autodesk, Inc.

Faurecia Automotive Seating, LLC

Skybox Imaging, Inc.

Northrop Grumman Systems Corporatiom

H Keith Nishihara

Shi-Ping Hsu

Kate LeeAnn Bechtel

Bran Ferren

P A Crossley

Adrian Kaehler

Neil D Hunt

Nathan H Harding

Kurt Amundson

Brian Patrick Wilfley

William Daniel Hillis

Michael Muller

Lars Jangaard

Eric J Shrader

Sung Hoon Kim

Cedric Ketels

M Dirk Robinson

Chwen-Yuan Ku

James Theodore Hotary

Kenneth Wagner Aull

Perry Q Anderson

Neil Gilbert Siegel

Dale J Frye

Donald G Lariviere

William Friederich Witt

Kjerstin Irja Williams

Russell B Ford

Houstin Lichtenwalner

Gary Cantu

Douglas A Reim

Wayne Evans

Rudy K Yukich

Chris Hassapis

J Martin Tenenbaum

Eric Gradman

Catherine Lu

Julie Raymond

Ron Smith

James Olef Jensen

Heather Klaubert

Donald G Larivière

A method for determining oxygen saturation includes emitting light from sources into tissue; detecting the light by detectors subsequent to reflection; and generating reflectance data based on detecting the light. The method includes determining a first subset of simulated reflectance curves from a set of simulated reflectance curves stored in a tissue oximetry device for a coarse grid; and fitting the reflectance data points to the first subset of simulated reflectance curves to determine a closest fitting one of the simulated reflectance curves. The method includes determining a second subset of simulated reflectance curves for a fine grid based on the closest fitting one of the simulated reflectance curves; determining a peak of absorption and reflection coefficients from the fine grid; and determining an absorption and a reflectance coefficient for the reflectance data points by performing a weighted average of the absorption coefficients and reflection coefficients from the peak.

Determining tissue oxygen saturation using monte carlo and iterative techniques

A device for automating the process of installing eyelash extensions onto the natural eyelashes of a subject. In some embodiments, the placing of extensions is carried out by a robotic mechanism utilizing computer vision. In some embodiments, the same device may be used for extending eyebrows rather than eyelashes, as eyebrows have rather similar properties to eyelashes.

Method and device for evaluation of eye hairs

Using monte carlo and iterative techniques to determine tissue oxygen saturation

A device for ensuring safe operation of a robot used for cosmetics applications, including the retrofitting of robots not originally design for such applications. In some embodiments, the robot is used for the automatic placement of eyelash extensions onto the natural eyelashes of a subject. In some embodiments, a safety barrier is provided by a physical barrier or light curtain. In other embodiments, readily deformable end effectors are used.

Deformable end effectors for cosmetic robotics

Tissue oximeter with stored simulated reflectance curves

A device for automating the process of installing eyelash extensions onto the natural eyelashes of a subject. In some embodiments, the placing of extensions is carried out by a robotic mechanism utilizing computer vision.

Method and device for evaluation of eyelashes

Using Monte Carlo and iterative techniques to determine tissue oxygen saturation

An occupant support adapted for use in a vehicle includes a sensory system and a control system. The sensor system is configured to generate signals indicative of at least one of a physiological characteristic of the occupant.

Vehicle seat

Determining tissue oxygen saturation using Monte Carlo and iterative techniques

One embodiment of the invention includes a method of providing device inputs. The method includes illuminating hand gestures performed via a bare hand of a user in a foreground of a background surface with at least one infrared (IR) light source. The method also includes generating a first plurality of silhouette images associated with the bare hand based on an IR light contrast between the bare hand and the background surface and generating a second plurality of silhouette images associated with the bare hand based on an IR light contrast between the bare hand and the background surface. The method also includes determining a plurality of three-dimensional features of the bare hand relative to the background surface based on a parallax separation of the bare hand in the first plurality of silhouette images relative to the second plurality of silhouette images. The method also includes determining a provided input gesture based on the plurality of three-dimensional features of the bare hand and comparing the provided input gesture with a plurality of predefined gesture inputs in a gesture library. The method further includes providing at least one device input corresponding to interaction with displayed visual content based on the provided input gesture corresponding to one of the plurality of predefined gesture inputs.

Hand-gesture recognition method

One embodiment of the invention includes a computer interface system. The system comprises a user interface screen configured to display visual content and an input system configured to detect a presence of an input object within a threshold distance along a normal axis of the user interface screen. The system further comprises a graphical controller configured to magnify a portion of the visual content that is located at an approximate location of a base of the normal axis on the user interface screen.

Image magnification system for computer interface

A system and method is provided for a gesture recognition interface system. The system comprises a projector configured to project colorless light and visible images onto a background surface. The projection of the colorless light can be interleaved with the projection of the visible images. The system also comprises at least one camera configured to receive a plurality of images based on a reflected light contrast difference between the background surface and a sensorless input object during projection of the colorless light. The system further comprises a controller configured to determine a given input gesture based on changes in relative locations of the sensorless input object in the plurality of images, and being further configured to initiate a device input associated with the given input gesture.

Gesture recognition light and video image projector

Examples of systems and methods to provide estimates of dark current for pixels of a photosensor as a function of the temperature of the sensor and the gain applied to the photosensor are described. In various implementations, the dark current estimated for each pixel can depend at least partly on a global scale factor and a global bias that depend on temperature and gain and a temperature-independent and gain-independent offset value for each pixel. The scale, bias, and offsets may be determined from multiple dark field images taken by the sensor over a range of operating temperatures. In some cases, the scale and bias can be determined using a subset of less than all the image pixels. Scale and bias derived for a particular sensor can be used in the calibration of different sensors.

Sensor dark pixel offset estimation

Monte carlo and iterative methods for determination of tissue oxygen saturation

Growing community of inventors

Los Altos, CA, United States of America

H Keith Nishihara