Apple Inc.

Plato Systems, Inc.

Leland Stanford Junior University

Hao Nan

Mohammad Amin Arbabian

Chaohao Wang

Paolo Sacchetto

Guy Cote

Brijesh Tripathi

Marc Albrecht

Sandro Hermann Pintz

David S Zalatimo

Christopher Philip Alan Tann

Mashhour Solh

Akbar Ghasemi

Zhibing Ge

Upamanyu Madhow

Babak Mamandipoor

Alex Gilbert

Matthew Thornton

Matt Thornton

Seyed Miaad Seyed Aliroteh

A system is provided that learns a radar scene's background and that filters radar tracks determined to be in the radar scene background; The system including processing circuitry configured with executable instructions to accesses radar tracks that include radar measurements; to use the measurements to determine a persistent radar object in a radar scene background; and to subsequently filter accessed radar tracks having locations within the radar scene background.

Spatial sensor system with background scene subtraction

An imaging system is provided comprising: a memory storing instructions which, when executed by processing circuitry, cause the processing circuitry to perform operations comprising: determining multiple image regions of interest (ROIs) within a camera image plane that correspond to one or more three-dimensional (3D) world object images; determining multiple radar ROIs that correspond to one or more 3D world objects; determining 3D world distances corresponding to the radar ROIs; determining multiple co-registered ROI pairs by co-registering individual image ROIs with individual radar ROIs corresponding to common 3D world objects; adjusting one or more parameters associated with the camera, based upon the co-registered ROI pairs.

Method and apparatus for camera calibration

An electronic device may generate content that is to be displayed on a display. The display may have an array of liquid crystal display pixels for displaying image frames of the content. The image frames may be displayed with positive and negative polarities to help reduce charge accumulation effects. A charge accumulation tracker may analyze the image frames to determine when there is a risk of excess charge accumulation. The charge accumulation tracker may analyze information on gray levels, frame duration, and frame polarity. The charge accumulation tracker may compute a charge accumulation metric for entire image frames or may process subregions of each frame separately. When subregions are processed separately, each subregion may be individually monitored for a risk of excess charge accumulation.

Electronic device display with charge accumulation tracker

A thermoacoustic imaging device is provided having a transmitter configured to provide an electromagnetic transmit signal (e.g. a continuous sinusoidal signal) to an object being imaged. The transmit signal is a modulated continuous-wave signal based on a carrier frequency signal fmodulated at a modulation frequency at or near f. The detector is further configured to receive an acoustic signal from the object being imaged, and is responsive to acoustic frequencies at or near 2f. A non-linear thermoacoustic effect in the object being imaged generates the acoustic signal from the object being imaged. Spectroscopic maps could be generated and imaged object could be analyzed. The device enhances signal-to-noise ratio of the reconstructed image and reduces the requirement of peak power in thermoacoustic imaging systems. In addition, the generated pressure of the imaged object is separated from microwave leakage and feedthrough in frequency through the nonlinear thermoacoustic effect.

Coherent frequency-domain microwave-induced thermoacoustic imaging

Systems and methods for labeling radar tracks for machine learning are disclosed. According to some aspects, a machine accesses data from radar unit(s), the data from the radar unit(s) comprising radar tracks, each radar track comprising one or more of the following: Doppler and micro-Doppler measurement(s), range measurement(s), and angle measurement(s). The machine accesses data from computer vision device(s), the data from the computer vision device(s) comprising image(s), the data from the computer vision device(s) being associated with a common geographic region and a common time period with the data from the radar unit(s). The machine labels, using an image recognition module, objects in the image(s). The machine determines, based on the common geographic region and the common time period, that labeled object(s) in the image(s) map to radar track(s). The machine labels the radar track(s) based on labels of the labeled objects.

Radar data collection and labeling for machine learning

An electronic device may generate content that is to be displayed on a display. The display may have an array of liquid crystal display pixels for displaying image frames of the content. A charge accumulation tracker may analyze the image frames to determine when there is a risk of excess charge accumulation. The charge accumulation tracker may implement a physically derived circuit model of the pixels. A charge accumulation input response matrix and a charge accumulation state response matrix for the model may be stored in look-up table circuitry and used in computing a current charge accumulation state based on current pixel voltage information and previous state information. The impact of temperature, backlight illumination level, frame duration, and other factors may be taken into account in evaluating the current charge accumulation state.

Display with physically modeled charge accumulation tracking

Improved thermoacoustic imaging is provided by ensuring directional uniformity of the microwave excitation provided to the target being imaged. This directional uniformity can be quantified in terms of the eccentricity e of the polarization ellipse of the microwave excitation. We have e&#x2264;0.87, preferably e&#x2264;0.71, and more preferably e&#x2264;0.32. Optical excitation can be provided in addition to the microwave excitation. Excitation can be performed at multiple optical wavelengths and/or microwave frequencies to improve depth uniformity. In addition, the employment of excitation cells with optimized spacing and geometry provides the uniformity in another two degrees of freedom. One potential application is to detect blood vessel in user's finger for biometric authentication.

Mapping of blood vessels for biometric authentication

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Stanford, CA, United States of America

Hao Nan