Videos

“Designing and Selecting Instruction Sets for Vision,” a Presentation From Cadence

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Chris Rowen, Fellow at Cadence, presents the "Designing and Selecting Instruction Sets for Vision" tutorial at the May 2015 Embedded Vision Summit. Two critical technical trends have reached important inflection points: the massive compute demands of vision processing and the capabilities of specialized vision processors. But what how do you actually select (or even build) […]

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“Choosing a Processor for Embedded Vision: Options and Trends,” a Presentation From BDTI

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Jeff Bier, President of Berkeley Design Technology, Inc. (BDTI) and Founder of the Embedded Vision Alliance, presents the "Choosing a Processor for Embedded Vision: Options and Trends" tutorial at the May 2015 Embedded Vision Summit. Computer vision applications typically demand lots of processor performance. These applications also tend to be complex and fast-changing, so developers

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“Implementing Eye Tracking for Medical, Automotive and Headset Applications,” a Presentation From Xilinx and EyeTech Digital Systems

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Dan Isaacs, Director of Smarter Connected Systems at Xilinx, and Robert Chappell, Founder of EyeTech Digital Systems, co-present the "Implementing Eye Tracking for Medical, Automotive and Headset Applications" tutorial at the May 2015 Embedded Vision Summit. When humans communicate with each other, we get important cues from watching each other’s eyes. Similarly, machines can gain

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May 2015 Embedded Vision Summit Technical Presentation: “System-level Design for Embedded Vision with FPGA-based Programmable SoCs,” Mario Bergeron, Avnet Electronics Marketing

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Mario Bergeron, Technical Marketing Engineer at Avnet Electronics Marketing, presents the "System-Level Design for Embedded Vision with FPGA-based Programmable SoCs" tutorial at the May 2015 Embedded Vision Summit. FPGA-based programmable system-on-chip (SoC) devices offer capabilities beyond those found in traditional embedded processors. The programmability and vast parallel processing capabilities of the FPGA fabric allow developers

May 2015 Embedded Vision Summit Technical Presentation: “System-level Design for Embedded Vision with FPGA-based Programmable SoCs,” Mario Bergeron, Avnet Electronics Marketing Read More +

May 2015 Embedded Vision Summit Technical Presentation: “3D from 2D: Theory, Implementation, and Applications of Structure from Motion,” Marco Jacobs, videantis

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Marco Jacobs, Vice President of Marketing at videantis, presents the "3D from 2D: Theory, Implementation, and Applications of Structure from Motion" tutorial at the May 2015 Embedded Vision Summit. Structure from motion uses a unique combination of algorithms that extract depth information using a single 2D moving camera. Using a calibrated camera, feature detection, and

May 2015 Embedded Vision Summit Technical Presentation: “3D from 2D: Theory, Implementation, and Applications of Structure from Motion,” Marco Jacobs, videantis Read More +

“ICIP 2016 and the Visual Technology Innovator Award,” a Presentation from the IEEE

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Lina Karam, Ph.D., IEEE Fellow and Director of the Image, Video & Usability (IVU) Lab at Arizona State University, delivers the presentation "ICIP 2016 and the Visual Technology Innovator Award" at the May 2015 Embedded Vision Alliance Member Meeting. Lina, the General Chair of the upcoming IEEE ICIP 2016 conference, describes the objectives and details

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May 2015 Embedded Vision Summit Technical Presentation: “Low-power Embedded Vision: A Face Tracker Case Study,” Pierre Paulin, Synopsys

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Pierre Paulin, R&D Director for Embedded Vision at Synopsys, presents the "Low-power Embedded Vision: A Face Tracker Case Study" tutorial at the May 2015 Embedded Vision Summit. The ability to reliably detect and track individual objects or people has numerous applications, for example in the video-surveillance and home entertainment fields. While this has proven to

May 2015 Embedded Vision Summit Technical Presentation: “Low-power Embedded Vision: A Face Tracker Case Study,” Pierre Paulin, Synopsys Read More +

Texas Instruments Discusses DSPs for Embedded Vision: History, Current Status and Future Trends

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In this video, also found on the company's website and YouTube channel, Texas Instruments employees Mark Nadeski and Arnon Friedmann discuss DSPs and embedded vision. This 4th episode in TI’s DSP Breaktime video series covers topics such as the following: Why are DSPs good for embedded vision? The Embedded Vision Alliance and TI's role in

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“Tailoring Convolutional Neural Networks for Low-Cost, Low-Power Implementation,” a Presentation From Synopsys

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Bruno Lavigueur, Project Leader for Embedded Vision at Synopsys, presents the "Tailoring Convolutional Neural Networks for Low-Cost, Low-Power Implementation" tutorial at the May 2015 Embedded Vision Summit. Deep learning-based object detection using convolutional neural networks (CNN) has recently emerged as one of the leading approaches for achieving state-of-the-art detection accuracy for a wide range of

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NVIDIA Demonstration of its Drive PX ADAS Platform for Surround Vision

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David Anderson, Senior Automotive Solutions Architect at NVIDIA, demonstrates the company's latest embedded vision technologies and products at the January 2015 Consumer Electronics Show. Specifically, Anderson demonstrates a Surround Vision application running on the company's Drive PX ADAS platform, based on the Tegra X1 SoC.

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Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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