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Us Patents
Visual Sign Language Translation Training Device And Method
Methods, devices and systems for training a pattern recognition system are described. In one example, a method for training a sign language translation system includes generating a three-dimensional (3D) scene that includes a 3D model simulating a gesture that represents a letter, a word, or a phrase in a sign language. The method includes obtaining a value indicative of a total number of training images to be generated, using the value indicative of the total number of training images to determine a plurality of variations of the 3D scene for generating of the training images, applying each of plurality of variations to the 3D scene to produce a plurality of modified 3D scenes, and capturing an image of each of the plurality of modified 3D scenes to form the training images for a neural network of the sign language translation system.
Automated Sign Language Translation And Communication Using Multiple Input And Output Modalities
Methods, apparatus and systems for recognizing sign language movements using multiple input and output modalities. One example method includes capturing a movement associated with the sign language using a set of visual sensing devices, the set of visual sensing devices comprising multiple apertures oriented with respect to the subject to receive optical signals corresponding to the movement from multiple angles, generating digital information corresponding to the movement based on the optical signals from the multiple angles, collecting depth information corresponding to the movement in one or more planes perpendicular to an image plane captured by the set of visual sensing devices, producing a reduced set of digital information by removing at least some of the digital information based on the depth information, generating a composite digital representation by aligning at least a portion of the reduced set of digital information, and recognizing the movement based on the composite digital representation.
Real-Time Gesture Recognition Method And Apparatus
Disclosed are methods, apparatus and systems for real-time gesture recognition. One exemplary method for the real-time identification of a gesture communicated by a subject includes receiving, by a first thread of the one or more multi-threaded processors, a first set of image frames associated with the gesture, the first set of image frames captured during a first time interval, performing, by the first thread, pose estimation on each frame of the first set of image frames including eliminating background information from each frame to obtain one or more areas of interest, storing information representative of the one or more areas of interest in a shared memory accessible to the one or more multi-threaded processors, and performing, by a second thread of the one or more multi-threaded processors, a gesture recognition operation on a second set of image frames associated with the gesture.
Automated Gesture Identification Using Neural Networks
Disclosed are methods, apparatus and systems for gesture recognition based on neural network processing. One exemplary method for identifying a gesture communicated by a subject includes receiving a plurality of images associated with the gesture, providing the plurality of images to a first 3-dimensional convolutional neural network (3D CNN) and a second 3D CNN, where the first 3D CNN is operable to produce motion information, where the second 3D CNN is operable to produce pose and color information, and where the first 3D CNN is operable to implement an optical flow algorithm to detect the gesture, fusing the motion information and the pose and color information to produce an identification of the gesture, and determining whether the identification corresponds to a singular gesture across the plurality of images using a recurrent neural network that comprises one or more long short-term memory units.
Automated Sign Language Translation And Communication Using Multiple Input And Output Modalities
Methods, apparatus and systems for recognizing sign language movements using multiple input and output modalities. One example method includes capturing a movement associated with the sign language using a set of visual sensing devices, the set of visual sensing devices comprising multiple apertures oriented with respect to the subject to receive optical signals corresponding to the movement from multiple angles, generating digital information corresponding to the movement based on the optical signals from the multiple angles, collecting depth information corresponding to the movement in one or more planes perpendicular to an image plane captured by the set of visual sensing devices, producing a reduced set of digital information by removing at least some of the digital information based on the depth information, generating a composite digital representation by aligning at least a portion of the reduced set of digital information, and recognizing the movement based on the composite digital representation.
Visual Sign Language Translation Training Device And Method
Methods, devices and systems for training a pattern recognition system are described. In one example, a method for training a sign language translation system includes generating a three-dimensional (3D) scene that includes a 3D model simulating a gesture that represents a letter, a word, or a phrase in a sign language. The method includes obtaining a value indicative of a total number of training images to be generated, using the value indicative of the total number of training images to determine a plurality of variations of the 3D scene for generating of the training images, applying each of plurality of variations to the 3D scene to produce a plurality of modified 3D scenes, and capturing an image of each of the plurality of modified 3D scenes to form the training images for a neural network of the sign language translation system.
Data Processing Architecture For Improved Data Flow
Disclosed are methods, apparatus and systems for improving data management and workload distribution in pattern recognition systems. An example method of managing data for a sign language translation system includes receiving multiple sets of data acquired by one or more data acquisition devices. Each set of data including an image frame that illustrates at least a part of a gesture. The method includes determining, for each of the multiple sets of data, a plurality of attribute values defined by a customized template. The method includes accessing the multiple sets of data, by a plurality of processing units, based on a location indicated by the attributes for recognizing the at least a part of a gesture.
Automated Sign Language Translation And Communication Using Multiple Input And Output Modalities
Methods, apparatus and systems for recognizing sign language movements using multiple input and output modalities. One example method includes capturing a movement associated with the sign language using a set of visual sensing devices, the set of visual sensing devices comprising multiple apertures oriented with respect to the subject to receive optical signals corresponding to the movement from multiple angles, generating digital information corresponding to the movement based on the optical signals from the multiple angles, collecting depth information corresponding to the movement in one or more planes perpendicular to an image plane captured by the set of visual sensing devices, producing a reduced set of digital information by removing at least some of the digital information based on the depth information, generating a composite digital representation by aligning at least a portion of the reduced set of digital information, and recognizing the movement based on the composite digital representation.
Elite Venue Systems Mar 2014 - Feb 2015
Interim Managing Director
Blue Ocean Enterprises, Inc. Jan 2012 - Feb 2014
Chief Innovation and Technology Officer Then and Senior Fellow For Technology R and D
Various Start-Up Ventures Jan 2005 - Dec 2011
Inventor, Co-Founder, Interim and Fractional Technical Executive Service
Lomos Jan 1988 - Dec 2005
Ceo, Chief Technology Officer Lomos, Ltd
Evaltec and Evaltec Global Jan 1988 - Dec 2005
Founder and Chief Executive Officer
Skills:
Strategic Planning Business Development Management Strategy Project Management Entrepreneurship Integration Start Ups Leadership Program Management Business Strategy Wireless Nonprofits Product Management Executive Management Training Public Speaking Control Theory Software Sensors Government Algorithms Wireless Technologies International Business Development Globalization Global Trends Security Sustainability Technology R&D Non Profits Technical Security Business Intelligence Global Business Development Asian Business Digital Imaging Satellite Communications Big Data Geolocation Augmented Reality Predictive Analytics Social Analytics Robotics Telepresence Iot Telemedicine Machine Learning Machine Vision
Interests:
Multi Spectral Imagery Adaptive Man Machine Interfaces Health Micro Enterprise In Developing Countries Photography Science and Technology Languages and Natural Language Systems Additive Manufacturing Cognitive Systems Advanced Intelligent Analytics Disaster and Humanitarian Relief Drone Development and Detection Anti Surveillance Technology Conformal Intelligent Materials Micro Enterprise For Developing Areas Social Services Elder Care For Developing Nations Economic Empowerment Adaptive Intelligent Social Interfaces Surveillance Tele Transportation
Languages:
English Spanish Mandarin German Portuguese Hebrew Afrikaans Russian Lao