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Patrick M Amihood

from Palo Alto, CA
Age ~46
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Also known as:
Patrick B, Patrick D
Phone and address:
656 Hale St, Palo Alto, CA 94301
Connected to:
Mohamed A Amiin, 33Angel Y Amil, 47Azhar D Amil, 73Mohamed AmilRicardo Amil, 32Jeanty Amilca, 45Fernando Amilibia, 57Robert M Amilibia, 40Mary L Amilicia, 70Venkataramana Amilineni, 94

Patrick Amihood Phones & Addresses

  • 656 Hale St, Palo Alto, CA 94301
  • Carmel, CA
  • San Francisco, CA
  • Denver, CO
  • Sunnyvale, CA
  • Mountain View, CA
  • San Diego, CA
  • La Jolla, CA

Work

Company: Google Aug 2014 Position: Staff hardware engineer, soli

Education

Degree: Bachelors, Bachelor of Arts School / High School: Cornell University 1996 to 2000 Specialities: Physics

Skills

Algorithms • Python • Mobile Devices • Wireless • System Architecture • Software Engineering • Software Development • Product Development • Digital Signal Processors • C++ • Wireless Technologies

Languages

English

Industries

Computer Software

Resumes

Resumes

Patrick Amihood Photo 1

Staff Hardware Engineer, Soli

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Location:
656 Hale St, Palo Alto, CA 94301
Industry:
Computer Software
Work:
Google
Staff Hardware Engineer, Soli
Chattag Aug 2013 - Jul 2014
Founder
Rallycause Jan 2012 - Aug 2013
Founder
Broadcom Jul 2011 - Jan 2012
Senior Staff Scientist
Telegent Systems Jul 2009 - Jul 2011
Engineer
Education:
Cornell University 1996 - 2000
Bachelors, Bachelor of Arts, Physics Uc San Diego 1988 - 1990
Doctorates, Doctor of Philosophy, Electrical Engineering
Skills:
Algorithms
Python
Mobile Devices
Wireless
System Architecture
Software Engineering
Software Development
Product Development
Digital Signal Processors
C++
Wireless Technologies
Languages:
English

Publications

Us Patents

Smartphone-Based Radar System For Determining User Intention In A Lower-Power Mode

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US Patent:
20220269329, Aug 25, 2022
Filed:
Feb 9, 2022
Appl. No.:
17/650488
Inventors:
- Mountain View CA, US
Ivan Poupyrev - Sunnyvale CA, US
Eiji Hayashi - Cupertino CA, US
Patrick M. Amihood - Palo Alto CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06F 1/3231
G01S 7/35
G01S 13/04
G06F 1/3287
G06F 3/01
Abstract:
This document describes techniques and systems that enable a smartphone-based radar system for determining user intention in a lower-power mode. The techniques and systems use a radar field to enable the smartphone to accurately determine the presence or absence of a user and further determine the intention of the user to interact with the smartphone. Using these techniques, the smartphone can account for the user's nonverbal communication cues to determine and maintain an awareness of users in its environment, and only respond to direct interactions once a user has demonstrated an intention to interact, which preserves battery power. The smartphone may determine the user's intention by recognizing various cues from the user, such as a change in position relative to the smartphone, a change in posture, or by an explicit action, such as a gesture.

Robust Radar-Based Gesture-Recognition By User Equipment

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US Patent:
20220261084, Aug 18, 2022
Filed:
Apr 29, 2022
Appl. No.:
17/661494
Inventors:
- Mountain View CA, US
Patrick M. Amihood - Palo Alto CA, US
John David Jacobs - San Diego CA, US
Abel Seleshi Mengistu - Mountain View CA, US
Leonardo Giusti - San Francisco CA, US
Vignesh Sachidanandam - Redwood City CA, US
Devon James O'Reilley Stern - Oakland CA, US
Ivan Poupyrev - Los Altos CA, US
Brandon Barbello - Mountain View CA, US
Tyler Reed Kugler - Palo Alto CA, US
Johan Prag - Mountain View CA, US
Artur Tsurkan - San Francisco CA, US
Alok Chandel - Mountain View CA, US
Lucas Dupin Moreira Costa - Mountain View CA, US
Selim Flavio Cinek - Los Angeles CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06F 3/01
G06V 40/20
Abstract:
Systems and techniques are described for robust radar-based gesture-recognition. A radar system detects radar-based gestures on behalf of application subscribers. A state machine transitions between multiple states based on inertial sensor data. A no-gating state enables the radar system to output radar-based gestures to application subscribers. The state machine also includes a soft-gating state that prevents the radar system from outputting the radar-based gestures to the application subscribers. A hard-gating state prevents the radar system from detecting radar-based gestures altogether. The techniques and systems enable the radar system to determine when not to perform gesture-recognition, enabling user equipment to automatically reconfigure the radar system to meet user demand. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

Face Authentication Anti-Spoofing Using Interferometry-Based Coherence

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US Patent:
20230125564, Apr 27, 2023
Filed:
Sep 6, 2022
Appl. No.:
17/930016
Inventors:
- Mountain View CA, US
Anton Heistser - Munich, DE
Patrick M. Amihood - Palo Alto CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06V 40/16
G06V 10/25
G01S 15/89
Abstract:
Techniques and apparatuses are described that implement face authentication anti-spoofing using interferometry-based coherence. In particular, a face-authentication system uses ultrasound to distinguish between a real human face and a presentation attack that uses instruments to present a version of a human face. The face-authentication system includes or communicates with an ultrasonic sensor, which can detect a presentation attack and notify the face-authentication system. In general, the ultrasonic sensor uses interferometry to evaluate an amount of coherence (or similarity) between reflections observed by two or more transducers. In this way, the ultrasonic sensor can prevent unauthorized actors from using the presentation attack to gain access to a user's account or information.

Face Authentication Anti-Spoofing Using Ultrasound

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US Patent:
20230126062, Apr 27, 2023
Filed:
Sep 6, 2022
Appl. No.:
17/929991
Inventors:
- Mountain View CA, US
Patrick M. Amihood - Palo Alto CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06F 21/32
G06V 10/25
G06V 10/44
G06V 10/74
G06V 40/16
G06V 40/40
G06T 7/20
G06T 7/70
Abstract:
Techniques and apparatuses are described that implement face authentication anti-spoofing using ultrasound. In particular, a face-authentication system uses ultrasound to distinguish between a real human face and a presentation attack that uses instruments to present a version of a human face. The face-authentication system includes or communicates with an ultrasonic sensor, which can detect a presentation attack and notify the face-authentication system. In general, the ultrasonic sensor analyzes characteristics of a presented object and determines whether the object represents a human face or a presentation attack instrument. In this way, the ultrasonic sensor can prevent unauthorized actors from using the presentation attack to gain access to a user's account or information.

Face Authentication Anti-Spoofing Using Power-Spectra-Based Variance

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US Patent:
20230129068, Apr 27, 2023
Filed:
Sep 6, 2022
Appl. No.:
17/930026
Inventors:
- Mountain View CA, US
Anton Heistser - Munich, DE
Patrick M. Amihood - Palo Alto CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06V 40/16
G01S 15/89
Abstract:
Techniques and apparatuses are described that implement face authentication anti-spoofing using ultrasound. In particular, a face-authentication system uses ultrasound to distinguish between a real human face and a presentation attack that uses instruments to present a version of a human face. The face-authentication system includes or communicates with an ultrasonic sensor, which can detect a presentation attack and notify the face-authentication system. In general, the ultrasonic sensor uses power-spectra to evaluate an amount of variance observed over time within at least one receive channel. In this way, the ultrasonic sensor can prevent unauthorized actors from using the presentation attack to gain access to a user's account or information.

Radar-Enabled Sensor Fusion

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US Patent:
20210365124, Nov 25, 2021
Filed:
Aug 4, 2021
Appl. No.:
17/394241
Inventors:
- Mountain View CA, US
Carsten C. Schwesig - San Francisco CA, US
Jaime Lien - Mountain View CA, US
Patrick M. Amihood - San Francisco CA, US
Ivan Poupyrev - Sunnyvale CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06F 3/01
G01S 7/41
G01S 13/56
G01S 13/86
H04Q 9/00
G06K 9/00
G06K 9/62
G01S 13/88
G06F 21/32
G06F 3/0481
G01S 7/40
H04W 4/80
G06N 20/00
H04W 16/28
G01S 13/90
G06F 16/245
G06F 21/62
A63F 13/21
A63F 13/24
G01S 13/66
Abstract:
This document describes apparatuses and techniques for radar-enabled sensor fusion. In some aspects, a radar field is provided and reflection signals that correspond to a target in the radar field are received. The reflection signals are transformed to provide radar data, from which a radar feature indicating a physical characteristic of the target is extracted. Based on the radar features, a sensor is activated to provide supplemental sensor data associated with the physical characteristic. The radar feature is then augmented with the supplemental sensor data to enhance the radar feature, such as by increasing an accuracy or resolution of the radar feature. By so doing, performance of sensor-based applications, which rely on the enhanced radar features, can be improved.

Context-Sensitive Control Of Radar-Based Gesture-Recognition

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US Patent:
20210342008, Nov 4, 2021
Filed:
Sep 27, 2019
Appl. No.:
16/965735
Inventors:
- Mountain View CA, US
Ivan Poupyrev - Los Altos CA, US
Leonardo Giusti - San Francisco CA, US
Devon James O'Reilley Stern - Oakland CA, US
Jung Ook Hong - Sunnyvale CA, US
Patrick M. Amihood - Palo Alto CA, US
John David Jacobs - San Diego CA, US
Abel Seleshi Mengistu - Mountain View CA, US
Brandon Barbello - Mountain View CA, US
Tyler Reed Kugler - Palo Alto CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06F 3/01
G01S 7/41
G01S 13/06
Abstract:
This document describes techniques and systems for radar-based gesture-recognition with context-sensitive gating and other context-sensitive controls. Sensor data from a proximity sensor () and/or a movement sensor () produces a context of a user equipment (). The techniques and systems enable the user equipment () to recognize contexts when a radar system () can be unreliable and should not be used for gesture-recognition, enabling the user equipment () to automatically disable or “gate” the output from the radar system () according to context. The user equipment () prevents the radar system () from transitioning to a high-power state () to perform gesture-recognition in contexts where radar data detected by the radar system () is likely due to unintentional input. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

User-Customizable Machine-Learning In Radar-Based Gesture Detection

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US Patent:
20210326642, Oct 21, 2021
Filed:
Jun 29, 2021
Appl. No.:
17/361824
Inventors:
- Mountain View CA, US
Jaime Lien - Mountain View CA, US
Patrick M. Amihood - Palo Alto CA, US
Ivan Poupyrev - Los Altos CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06K 9/62
G06K 9/00
G06F 3/01
Abstract:
Various embodiments dynamically learn user-customizable input gestures. A user can transition a radar-based gesture detection system into a gesture-learning mode. In turn, the radar-based gesture detection system emits a radar field configured to detect a gesture new to the radar-based gesture detection system. The radar-based gesture detection system receives incoming radio frequency (RF) signals generated by the outgoing RF signal reflecting off the gesture, and analyzes the incoming RF signals to learn one or more identifying characteristics about the gesture. Upon learning the identifying characteristics, the radar-based gesture detection system reconfigures a corresponding input identification system to detect the gesture when the one or more identifying characteristics are next identified, and transitions out of the gesture-learning mode.
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Patrick M Amihood from Palo Alto, CA, age ~46 Get Report