Apple Inc.

Amazon Technologies, Inc.

Vaughn Todd Arnold

Sushma Shrikant Trivedi

Jack Benkual

Joseph P Bratt

Jerome Francis Duluk, Jr

Richard E Hessel

Stephen L Dodgen

Emerson S Fang

Hengwei Hsu

George Cuan

Jason Rupert Redgrave

Sidong Li

Matthew N Papakipos

Sam Ng

Nathan D Tuck

Zhaoyu Gong

Thomas Y Ho

Tuan Anh Nguyen

Shun Wai Go

Abbas Rashid

Abraham Mammen

Bo Hong

Joseph P Grass

Lindy Fung

Albert Suan-Wei Tsay

Keith Alan Cox

Gaurav Kapoor

Derek Fujio Iwamoto

Venkatesh Balasubramanian

Guy Cote

Peter F Holland

William C Athas

Brijesh Tripathi

Sumit Chawla

David B Townsley

Bradley David Urban

Steven Todd Weybrew

Albert C Kuo

David Ligon

Yutaka Takahashi

Jason Chen

Thomas Y Yo

Subject matter disclosed herein relates to arrangements and techniques that provide for identifying objects within an image such as the face position of a user of a portable electronic device. An application specific integrated circuit (ASIC) is configured to locate objects within images. The ASIC includes an image node configured to process an image and a search node configured to search the image for an object in the image. The ASIC also includes an ensemble node configured to confirm the presence of the object in the image. The ensemble node progressively compares, using computational engines that include accumulators, the pixel values of a template with pixel values of a region of interest in the image to create comparison result values.

Detecting objects in multiple images using integral images

Subject matter disclosed herein relates to arrangements and techniques that provide for identifying objects within an image such as the face position of a user of a portable electronic device. An application specific integrated circuit (ASIC) is configured to locate objects within images. The ASIC includes an image node configured to process an image and a search node configured to search the image for an object in the image. The ASIC also includes an ensemble node configured to confirm the presence of the object in the image. The ensemble node compares the pixel values of a template with pixel values of a region of interest in the image to create comparison result values and normalize the comparison result values.

Subject matter disclosed herein relates to arrangements and techniques that provide for identifying objects within an image such as the face position of a user of a portable electronic device. An application specific integrated circuit (ASIC) is configured to locate objects within images. The ASIC includes an image node configured to process an image and a search node configured to search the image for an object in the image. The search node includes an integral image generation unit configured to generate an integral image of the image and a Haar feature evaluation unit configured to evaluate search windows of the integral image with respect to Haar-like features. The ASIC also includes an ensemble node configured to confirm the presence of the object in the image.

Analyzing integral images with respect to HAAR features

Analyzing integral images with respect to Haar features

Methods and apparatuses are disclosed to estimate temperature at one or more critical points in a data processing system comprising modeling a steady state temperature portion of a thermal model at the one or more critical points using regression analysis; modeling the transient temperature portion of the thermal model at the one or more critical points using a filtering algorithm; and generating a thermal model at the one or more critical points by combining the steady state temperature portion of the thermal model with the transient temperature portion of the thermal model. The thermal model may then be used to estimate an instantaneous temperature at the one or more critical points or to predict a future temperature at the one or more critical points.

Method for estimating temperature at a critical point

Each of one or more temperature sensors of a computing system can measure and provide a temperature value (e.g., provide temperature data) to the system. In some embodiments, the system can apply an offset value, a time-based filter, and a weighting factor to each temperature value received from the one or more temperature sensors of the system. Based, at least in part, on the offsetting, filtering, and/or weighting, the computing system can determine (e.g., calculate, estimate, predict, etc.,) a temperature value representative of an enclosure temperature of the system. In some embodiments, based on the determined temperature value that is representative of the enclosure temperature, the computing system can perform appropriate subsequent processing in accordance with thermal management of the system.

Determining temperature using multiple sensors

In an embodiment, hardware implementing a transcendental or other non-linear function is based on a series expansion of the function. For example, a Taylor series expansion may be used as the basis. One or more of the initial terms of the Taylor series may be used, and may be implemented in hardware. In some embodiments, modifications to the Taylor series expansion may be used to increase the accuracy of the result. In one embodiment, a variety of bit widths for the function operands may be acceptable for use in a given implementation. A methodology for building a library of series-approximated components for use in integrated circuit design is provided which synthesizes the acceptable implementations and tests the results for accuracy. A smallest (area-wise) implementation which produces a desired level of accuracy may be selected as the library element.

Transcendental and non-linear components using series expansion

A blend unit in a display pipe for processing pixels of video and/or image frames may include multiple blend stages, where each blend stage may include multiple levels for blending pixels according to a blend equation. The blending operation includes blending pixel color values and Alpha values. A multiplication may be performed at each blend level, necessitating Alpha value normalizations in the form of divisions to obtain pixel color values having a specified bit-length. Color value normalizations are not needed when the desired result is an actual color value. In order to reduce the compounding of errors that may result from the introduction of an error at each division, Alpha value normalizations may not be performed at each blend level, carrying the intermediate results forward in fractional form&#x2014;through one or multiple blend stages&#x2014;until the end of the blending operation. At or after the final blend level&#x2014;in each blend stage, or in a final blend stage&#x2014;a single division may performed, preventing the compounding of errors that would be incurred at each blend level if a division at each blend level were performed.

Blend equation

Methodology for automatically generating series-approximated components

Systems and methods are disclosed for applying spatial filtering to raw image data. For example, a spatial filter may identify an n x n block of pixels from an image frame. The spatial filter has filter taps, each corresponding to one of the pixels of the n x n block. Pixel difference values between the input pixel and each of the neighboring pixels in the n x n block may be determined. Attenuation factors may be determined based on the pixel differences and brightness of the input pixel. Applying the attenuation factors to their respective filtering taps may produce attenuated filtering coefficients that are used to obtain filtered pixel values. By normalizing the sum of the filtered pixel values using the sum of the attenuated filtering coefficients, a spatially filtered output value corresponding to the current input pixel (e.g., located at the center of the n x n block) may be determined.

Spatial filtering for image signal processing

A deferred shading graphics pipeline processor and method are provided encompassing numerous substructures. Embodiments of the processor and method may include one or more of deferred shading, a tiled frame buffer, and multiple?stage hidden surface removal processing. In the deferred shading graphics pipeline, hidden surface removal is completed before pixel coloring is done. The pipeline processor comprises a command fetch and decode unit, a geometry unit, a mode extraction unit, a sort unit, a setup unit, a cull unit, a mode injection unit, a fragment unit, a texture unit, a Phong lighting unit, a pixel unit, and a backend unit.

Deferred shading graphics pipeline processor having advanced features

Methods and apparatuses for computing an absolute difference of two vectors of numbers. In one aspect of the invention, a method for execution by a microprocessor in response to receiving a single instruction includes: receiving a first plurality of numbers and a second plurality of numbers; and generating simultaneously a third plurality of numbers, each of which is an absolute difference between a number in the first plurality of numbers and a number in the second plurality of numbers. The above operations are performed in response to the microprocessor receiving the single instruction.

Method and apparatus for computing vector absolute differences

Methods and apparatuses for a data processing system are described herein. In one aspect of the invention, an exemplary apparatus includes a chip interconnect, a memory controller for controlling the host memory comprising DRAM memory, the memory controller coupled to the chip interconnect, a scalar processing unit coupled the chip interconnect wherein the scalar processing unit is capable of executing instructions to perform scalar data processing, a vector processing unit coupled the chip interconnect wherein the vector processing unit is capable of executing instructions to perform vector data processing, and an input/output (I/O) interface coupled to the chip interconnect wherein the I/O interface receives/transmits data from/to the scalar and/or vector processing units.

Method and apparatus for data processing

Growing community of inventors

Scotts Valley, CA, United States of America

Vaughn Todd Arnold