Abstract: Systems, apparatus, articles of manufacture, and methods are disclosed to process images using segmentation. An example apparatus includes interface circuitry, machine readable instructions, and programmable circuitry to at least one of instantiate or execute the machine readable instructions to generate a scaled frame from an input video frame, segment, with a neural network, the scaled frame to generate a scaled segmentation map based on the scaled frame, the scaled segmentation map to associate pixels of the scaled frame with ones of a plurality of segments in the scaled frame, and generate an output video frame based on the input video frame and an upscaled version of the scaled segmentation map.

Abstract: A high-level understanding of the scene captured by a camera allows for the use of scene-level understanding in the processing of the captured image. A downscaled image of a captured scene is generated and used as a basis for artificial intelligence analysis before the full image of the captured scene is processed. The downscaled image is generated concurrently with the capturing of the raw image at the image sensor and before full image signal processor (ISP) processing. Neural networks and other AI algorithms can be applied directly to the downscaled image to perform high-level understanding using minimal resources. The processing of the full scale captured image can be adapted to specific scenarios based on the understanding rather than undergoing all-purpose processing. The high-level understanding is provided to the full image processing pipe for enhancements in image quality, video conferencing, face detection, and other user experiences.

Abstract: Systems and methods for real-time, efficient, monocular gaze position determination that can be performed in real-time on a consumer-grade laptop. Gaze tracking can be used for human-computer interactions, such as window selection, user attention on screen information, gaming, augmented reality, and virtual reality. Gaze position estimation from a monocular camera involves estimating the line-of-sight of a user and intersecting the line-of-sight with a two-dimensional (2D) screen. The system uses a neural network to determine gaze position within about four degrees of accuracy while maintaining very low computational complexity. The system can be used to determine gaze position across multiple screens, determining which screen a user is viewing as well as a gaze target area on the screen.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to calibrate a stereo camera. An example apparatus includes means for determining a motion grid between a first image and a second image captured by the stereo camera; means for determining a calibration value to calibrate the stereo camera based on a prior calibration value, a relative orientation between the first image and the second image based on the motion grid, and a metric indicative of calibration improvement; and means for estimating a depth based on the calibration value.

Abstract: A method, system, and article of highly efficient neural network video image processing uses temporal correlations.

Abstract: Methods, apparatuses and systems may provide for operating a machine learning device by obtaining training image data, conducting an offline prediction analysis of the training image data with respect to one or more real-time parameters of an image capture device, and generating one or more parameter detection models based on the offline prediction analysis. Additionally, methods, apparatuses and systems may provide for operating the image capture device by obtaining a candidate image associated with the image capture device, determining that the candidate image corresponds to a particular type of scene represented in a parameter prediction model, and adjusting one or more real-time parameters of the image capture device based at least in part on one or more parameter values associated with the particular type of scene.

Abstract: Methods, apparatuses and systems may provide for operating a machine learning device by obtaining training image data, conducting an offline prediction analysis of the training image data with respect to one or more real-time parameters of an image capture device, and generating one or more parameter detection models based on the offline prediction analysis. Additionally, methods, apparatuses and systems may provide for operating the image capture device by obtaining a candidate image associated with the image capture device, determining that the candidate image corresponds to a particular type of scene represented in a parameter prediction model, and adjusting one or more real-time parameters of the image capture device based at least in part on one or more parameter values associated with the particular type of scene.

Abstract: Disclosed is a system and method for image processing and image subject matching. A circuit and system may be used for matching/correlating an object/subject or person present (i.e. visible within) within two or more images. An object or person present within a first image or a first series of images (e.g. a video sequence) may be characterized and the characterization information (i.e. one or a set of parameters) relating to the person or object may be stored in a database, random access memory or cache for subsequent comparison to characterization information derived from other images.

Abstract: Methods, apparatus, and articles of manufacture control a device or system that has an operational limit related to the rate or frequency of operation. The frequency of operation is controlled at a variable rate calculated to maximize the system or apparatus performance over a calculated period of time short enough that a controlling factor, such as power consumption, does not vary significantly during the period. Known system parameters, such as thermal resistance and capacitance of an integrated circuit (IC) and its package, and measured values, such as current junction temperature in an IC, are used to calculate a time-dependent frequency of operation for the upcoming time period that results in the best overall performance without exceeding the operational limit, such as the junction temperature.

Abstract: The operating rate of an electronic system is maximized without exceeding a thermal constraint, such as a maximum junction temperature of an integrated circuit (IC) or other portion of the electronic system. An operating parameter of the system that controls the thermal output of the system is calculated for an upcoming time period based upon the previously measured thermal performance relationship to the operating parameter level. If the predicted thermal performance will exceed a maximum allowable level of the thermal constraint, then the operating parameter is reduced by an amount calculated to keep the thermal constraint at a level just below the maximum allowable level, thus resulting in an optimal control approach to maximizing the system performance while not exceeding the thermal constraint.

Abstract: The operating rate of an electronic system is maximized without exceeding a thermal constraint, such as a maximum junction temperature of an integrated circuit (IC) or other portion of the electronic system. An operating parameter of the system that controls the thermal output of the system is calculated for an upcoming time period based upon the previously measured thermal performance relationship to the operating parameter level. If the predicted thermal performance will exceed a maximum allowable level of the thermal constraint, then the operating parameter is reduced by an amount calculated to keep the thermal constraint at a level just below the maximum allowable level, thus resulting in an optimal control approach to maximizing the system performance while not exceeding the thermal constraint.

Abstract: Methods, apparatus, and articles of manufacture control a device or system that has an operational limit related to the rate or frequency of operation. The frequency of operation is controlled at a variable rate calculated to maximize the system or apparatus performance over a calculated period of time short enough that a controlling factor, such as power consumption, does not vary significantly during the period. Known system parameters, such as thermal resistance and capacitance of an integrated circuit (IC) and its package, and measured values, such as current junction temperature in an IC, are used to calculate a time-dependent frequency of operation for the upcoming time period that results in the best overall performance without exceeding the operational limit, such as the junction temperature.

Abstract: Methods, apparatus, and articles of manufacture control a device or system that has an operational limit related to the rate or frequency of operation. The frequency of operation is controlled at a variable rate calculated to maximize the system or apparatus performance over a calculated period of time short enough that a controlling factor, such as power consumption, does not vary significantly during the period. Known system parameters, such as thermal resistance and capacitance of an integrated circuit (IC) and its package, and measured values, such as current junction temperature in an IC, are used to calculate a time-dependent frequency of operation for the upcoming time period that results in the best overall performance without exceeding the operational limit, such as the junction temperature.

Abstract: Methods, apparatus, and articles of manufacture control a device or system that has an operational limit related to the rate or frequency of operation. The frequency of operation is controlled at a variable rate calculated to maximize the system or apparatus performance over a calculated period of time short enough that a controlling factor, such as power consumption, does not vary significantly during the period. Known system parameters, such as thermal resistance and capacitance of an integrated circuit (IC) and its package, and measured values, such as current junction temperature in an IC, are used to calculate a time-dependent frequency of operation for the upcoming time period that results in the best overall performance without exceeding the operational limit, such as the junction temperature.