Ara V Nefian

US Patent:

7089185, Aug 8, 2006

Filed:

Jun 27, 2002

Appl. No.:

10/180042

Inventors:

Ara V Nefian - Santa Clara CA, US

Assignee:

Intel Corporation - Santa Clara CA

International Classification:

G10L 15/14

US Classification:

704256, 7042565

Abstract:

An arrangement is provided for embedded coupled hidden Markov model. To train an embedded coupled hidden Markov model, training data is first segmented into uniform segments at different layers of the embedded coupled hidden Markov model. At each layer, a uniform segment corresponds to a state of a coupled hidden Markov model at that layer. An optimal segmentation is generated at the lower layer based on the uniform segmentation and is then used to update parameters of models associated with the states of coupled hidden Markov models at lower layer. The updated model parameters at the lower layer are then used to update the model parameters associated with states at the super layer.

US Patent:

7165029, Jan 16, 2007

Filed:

May 9, 2002

Appl. No.:

10/142468

Inventors:

Ara V. Nefian - Santa Clara CA, US

Assignee:

Intel Corporation - Santa Clara CA

International Classification:

G10L 15/14
G10L 15/24

US Classification:

704236, 7042561, 7042562

Abstract:

A speech recognition method includes use of synchronous or asynchronous audio and a video data to enhance speech recognition probabilities. A two stream coupled hidden Markov model is trained and used to identify speech. At least one stream is derived from audio data and a second stream is derived from mouth pattern data. Gestural or other suitable data streams can optionally be combined to reduce speech recognition error rates in noisy environments.

US Patent:

7171043, Jan 30, 2007

Filed:

Oct 11, 2002

Appl. No.:

10/269333

Inventors:

Ara V. Nefian - Sunnyvale CA, US

Assignee:

Intel Corporation - Santa Clara CA

International Classification:

G06K 9/62
G06K 9/00
G10L 15/00
G05B 13/02

US Classification:

382159, 382118, 700 47, 7042561

Abstract:

An image processing system useful for facial recognition and security identification obtains an array of observation vectors from a facial image to be identified. A Viterbi algorithm is applied to the observation vectors given the parameters of a hierarchical statistical model for each object, and a face is identified by finding a highest matching score between an observation sequence and the hierarchical statistical model.

US Patent:

7203368, Apr 10, 2007

Filed:

Jan 6, 2003

Appl. No.:

10/269381

Inventors:

Ara V. Nefian - Sunnyvale CA, US

Assignee:

Intel Corporation - Santa Clara CA

International Classification:

G06K 9/62
G06K 9/00
G10L 15/00
G05B 13/02

US Classification:

382228, 382159, 382118, 700 47, 7042561

Abstract:

A pattern recognition procedure forms a hierarchical statistical model using a hidden Markov model and a coupled hidden Markov model. The hierarchical statistical model supports a pa 20 layer having multiple supernodes and a child layer having multiple nodes associated with each supernode of the parent layer. After training, the hierarchical statistical model uses observation vectors extracted from a data set to find a substantially optimal state sequence segmentation.

US Patent:

7209883, Apr 24, 2007

Filed:

May 9, 2002

Appl. No.:

10/142447

Inventors:

Ara V. Nefian - Santa Clara CA, US

Assignee:

Intel Corporation - Santa Clara CA

International Classification:

G10L 15/00
G10L 15/04
G10L 15/14
G06K 9/00

US Classification:

704256, 704251, 7042562, 704244, 382115, 382118

Abstract:

A speech recognition method includes use of synchronous or asynchronous audio and a video data to enhance speech recognition probabilities. A two stream factorial hidden Markov model is trained and used to identify speech. At least one stream is derived from audio data and a second stream is derived from mouth pattern data. Gestural or other suitable data streams can optionally be combined to reduce speech recognition error rates in noisy environments.

US Patent:

7224830, May 29, 2007

Filed:

Feb 4, 2003

Appl. No.:

10/358761

Inventors:

Ara V. Nefian - Fremont CA, US
Robert D. Cavin - Palo Alto CA, US

Assignee:

Intel Corporation - Santa Clara CA

International Classification:

G06K 9/00
H04N 13/00

US Classification:

382154, 382285, 715863, 348 42

Abstract:

Human gestures are detected and/or tracked from a pair of digital video images. The pair of images may be used to provide a set of observation vectors that provide a three dimensional position of a subject's upper body. The likelihood of each observation vector representing an upper body component may be determined. Initialization of the model for detecting and tracking gestures may include a set of assumptions regarding the initial position of the subject in a set of foreground observation vectors.

US Patent:

7274800, Sep 25, 2007

Filed:

Jan 23, 2003

Appl. No.:

10/349872

Inventors:

Ara Victor Nefian - Santa Clara CA, US
Radek Grzesczuk - Menlo Park CA, US
Victor Eruhimov - Nizhny Novgorod, RU

Assignee:

Intel Corporation - Santa Clara CA

International Classification:

G06K 9/00

US Classification:

382103, 382154, 715863, 348169

Abstract:

According to an embodiment, an apparatus and method are disclosed for dynamic gesture recognition from stereo sequences. In an embodiment, a stereo sequence of images of a subject is obtained and a depth disparity map is generated from the stereo sequence. The system is initiated automatically based upon a statistical model of the upper body of the subject. The upper body of the subject is modeled as three planes, representing the torso and arms of the subject, and three Gaussian components, representing the head and hands of the subject. The system tracks the upper body of the subject using the statistical upper body model and extracts three-dimensional features of the gestures performed. The system recognizes the gestures using recognition units, which, under a particular embodiment, utilizes hidden Markov models for the three-dimensional gestures.

US Patent:

7389502, Jun 17, 2008

Filed:

Mar 31, 2004

Appl. No.:

10/815288

Inventors:

Ara V. Nefian - San Jose CA, US
Ali-Reza Adl-Tabatabai - Santa Clara CA, US

Assignee:

Intel Corporation - Santa Clara CA

International Classification:

G06F 9/45

US Classification:

717158, 717153, 717154

Abstract:

A method, apparatus and system including selecting a phase threshold value, receiving a plurality of sequenced buffers, determining a distance between centers of at least two consecutive histogram bins, comparing the distance with the selected threshold value, and determining major execution phases of an executable process based on the comparison.