John Ju Guo

US Patent:

8134449, Mar 13, 2012

Filed:

Oct 22, 2008

Appl. No.:

12/256377

Inventors:

John J. Guo - Oak Park CA, US
Larry Rice - Simi Valley CA, US

Assignee:

Minebea Co., Ltd - Nagano-Ken

International Classification:

G05B 19/00

US Classification:

340 585, 340 554, 713186, 707603

Abstract:

A method for training a computing system using keyboard biometric information. The method includes depressing two or more keys on a keyboard input device for a first sequence of keys. The method then determines a key press time for each of the two or more keys to provide a key press time characteristic in the first sequence of keys. The method also determines a flight time between a first key and a second key to provide a flight time characteristic in the first sequence of keys, the first key being within the two or more keys. The method includes storing the key press time characteristic and the flight time characteristic for the first sequence of keys, and displaying indications associated with the first sequence of keys on a display device provided on a portion of the keyboard input device.

US Patent:

8229370, Jul 24, 2012

Filed:

Mar 10, 2009

Appl. No.:

12/401570

Inventors:

Mario Wu - Alhambra CA, US
Makoto Nakayama - Woodland Hills CA, US
John Guo - Oak Park CA, US
Jack Lieng - Chatsworth CA, US
Walter Lee - Rosemead CA, US

Assignee:

Minebea Co., Ltd. - Nagano-Ken

International Classification:

H04B 17/00
H04B 1/04

US Classification:

455 83, 4551271, 4551151

Abstract:

A method for automatically adjusting signal output power of a ZigBee wireless module. The method includes sending a signal with an output power from a transmitter of a ZigBee module to a receiver. The ZigBee module includes a power amplifier/low noise amplifier (PA/LNA) circuit. The output power can be adjusted between a minimum level and a maximum level. Additionally, the method includes generating a Link Quality Indicator (LQI) by the receiver based on the signal strength and returning the LQI to the ZigBee module. If the LQI is not within a predetermined range between a maximum value and a minimum value, the method includes adjusting the output power for sending next signal. If the output power from the transmitter has reached to the minimum level or the maximum level, the method further includes adjusting the PA/LNA circuit of the ZigBee module for maintaining the LQI within the predetermined range.

US Patent:

20050104853, May 19, 2005

Filed:

Nov 13, 2003

Appl. No.:

10/714095

Inventors:

Chatree Sitalasai - La Crescenta CA, US
Toshisada Takeda - Simi Valley CA, US
Dean Rice - Simi Valley CA, US
John Guo - Oak Park CA, US
Charles Fauble - Queen Creek AZ, US

International Classification:

G09G005/08

US Classification:

345163000, 340686100, 20006145R

Abstract:

A wake-up system for an input device having a circuit board inside it has a motion sensor mounted on the printed circuit board inside the input device. The motion sensor has a motion signal output and the wake-up system further include a detection circuit connected to the motion signal output. The detection circuit has a wake-up signal output. The input device can be an optical wireless mouse. The motion sensor may be a mechanical motion sensor such as a tilt sensor having a ball contact and stationary contacts. The stationary contacts may be printed directly on the printed circuit board. The ball contact and stationary contacts form an electrical switch and are gold-plated. The ball contact is conductive. The motion sensor may be sealed to avoid corrosion. The detection circuit detects a change of state of whether the electrical switch formed by the ball contact and stationary contact is opened or closed. A first embodiment can amplify the motion signal from the motion sensor and a second embodiment can detect a low signal from the motion sensor. Also disclosed is a method of waking up an input device such as a mouse and an input device comprising the wake-up system.

US Patent:

20200413067, Dec 31, 2020

Filed:

Jul 10, 2020

Appl. No.:

16/926089

Inventors:

- Burlington MA, US
Katherine H. Cornog - Medford MA, US
John J. Guo - Arcadia CA, US
Myo Tun - McKinney TX, US
Jeyun Lee - San Jose CA, US
Nigel Lee - Chestnut Hill MA, US

International Classification:

H04N 19/146
H04N 19/124
H04N 19/172
H04N 19/50
G06T 7/00
H04N 19/192
H04N 19/179
H04N 19/115
H04N 19/154

Abstract:

Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling. The methods may also be extended for adaptive bitrate (ABR) applications by applying scaling factors to predicted bitrates at one frame size to determine predicted bitrates at different frame sizes. A dynamic scaling algorithm may be used to determine predicted bitrates at the different frame sizes.

US Patent:

20190289296, Sep 19, 2019

Filed:

May 23, 2019

Appl. No.:

16/420796

Inventors:

- Concord MA, US
Katherine H. Cornog - Medford MA, US
John J. Guo - Arcadia CA, US
Myo Tun - McKinney TX, US
Jeyun Lee - Austin TX, US
Nigel Lee - Chestnut Hill MA, US

International Classification:

H04N 19/146
G06T 7/00
H04N 19/124
H04N 19/50
H04N 19/172

Abstract:

Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling. The methods may also be extended for adaptive bitrate (ABR) applications by applying scaling factors to predicted bitrates at one frame size to determine predicted bitrates at different frame sizes. A dynamic scaling algorithm may be used to determine predicted bitrates at the different frame sizes.

US Patent:

20150256850, Sep 10, 2015

Filed:

Nov 4, 2014

Appl. No.:

14/532947

Inventors:

- Concord MA, US
John J. Guo - Arcadia CA, US
Jeyun Lee - Austin TX, US
Sangseok Park - Flower Mound TX, US
Christopher Weed - Arlington MA, US
Justin Kwan - Brighton MA, US
Nigel Lee - Chestnut Hill MA, US

International Classification:

H04N 19/56
H04N 19/117
H04N 19/517

Abstract:

Continuous block tracking (CBT) tracks macroblock locations over reference frames to produce better inter-predictions than conventional block-based motion estimation/compression. CBT includes frame-to-frame tracking, estimating motion from a frame to a previous frame, and continuous tracking, related frame-to-frame motion vectors to block tracks. Frame-to-frame tracking may include block based or hierarchical motion estimations. CBT combined with enhanced predictive zonal search may create unified motion estimation. Accumulated CBT results may form trajectories for trajectory-based CBT predictions. Metrics measuring continuous track and motion vectors quality can assess relative priority of CBT predictions against non-tracker-based predictions and to modify encoding choices. Continuous tracks can be analyzed for goodness-of-fit to translational motion models, with outliers removed from encoding. Translational motion models can be extended to entire frames in adaptive picture type selection. Outputs from CBT used in look-ahead processing, via look-ahead tracking, may provide rate control and scene change detection for the current frame being encoded.