Intel's aspirations to evolve the means by which we interact with computers beyond the conventional keyboard, mouse and trackpad, specifically extending the "vision" (pun intended) to capabilities such as gestures, gaze tracking and face recognition, are well documented at this point.
As a recently published article authored by the Alliance notes, modern smartphones provide abundant imaging-related hardware resources and corresponding operating system and application capabilities that, while they might have been originally intended for still and video photography and videoconferencing purposes, are equally applicable to a variety of embedded vision applications.
Earlier this month, I passed along word of the teardown of the Leap Motion gesture interface peripheral, one of the better-known recent embedded vision examples by virtue of its consumer electronics focus and consequent extensive potential-customer interest and press coverage.
As past presentations and documentation have hopefully already made clear, Xilinx views its Zynq-7000 All Programmable SoCs (combining "soft" FPGA fabric and dual ARM Cortex-A9 "hard" cores) as ideal processing platforms for implementing embedded vision designs.
As those of you who've been monitoring the upcoming events page on the Alliance website (or who saw a previous news post) already know, Embedded Vision Alliance founder Jeff Bier spoke at Alliance member company National Instruments' NIWeek Conference earlier today.
Next Tuesday, July 30, at 10AM Pacific Time (1PM Eastern Time), Anatoly Baksheev, OpenCV GPU Module Team Leader at Itseez, will present a free webinar on "Getting Started with GPU-accelerated Computer Vision using OpenCV and CUDA." From the event page:
Back in March of last year, I discussed Nokia's just-introduced PureView 808 cameraphone, containing a revolutionary 41 Mpixel image sensor. The sensor's extraordinarily high pixel count was used by the handset in part to implement a high-quality digital zoom function; multiple pixels' data could also combined to generate lower-resolution images with enhanced low-light performance.