Embedded Vision Solutions
Advanced with AMD Technology

Embedded Vision

AMD speeds the development of embedded vision
applications in markets where systems must be highly
differentiated, extremely responsive, and able to immediately
adapt to the latest algorithms and image sensors.
Only with AMD

Market Context

Embedded Vision is one of the most exciting fields in technology today. AMD sees embedded vision as a key and pervasive megatrend that is shaping the future of the electronics industry.

Providing machines the ability to see, sense, and immediately respond to the world creates unique opportunities for system differentiation; however, this also creates challenges in how designers create next-generation architectures and bring them to market. Integrating disparate sub-systems including video and vision I/O with multiple image processing pipelines, and enabling these embedded-vision systems to perform vision-based analytics in real time is a complex task that requires tight coordination between hardware and software teams. To remain timely and relevant in the market, leading development teams are exploiting AMD devices in their next-generation systems to take advantage of the devices’ programmable hardware, software, and I/O capabilities.

AMD Solutions for Embedded Vision

AMD provides embedded vision developers with a suite of technologies that support both hardware and software design. AMD devices include FPGAs, SoCs and MPSoCs.

The AMD Vivado HLx design environment supports both hardware and platform developers developing the latest embedded-vision hardware. These tools include support for the industry’s latest high-bandwidth sensor interfaces. AMD SDx tools including SDSoC allows software and algorithm developers to develop in familiar Eclipse-based environments in familiar languages like C, C++ and OpenCL.

The AMD reVISION Stack builds upon the SDx concept to include support for OpenCV and machine learning inference, including support for the most popular neural networks such as AlexNet, GoogLeNet, SqueezeNet, SSD, and FCN as well as the functional elements required to build custom neural networks (CNNs/DNNs) while permitting design teams to leverage pre-defined and optimized CNN implementations for network layers. This is complemented by a broad set of acceleration-enabled OpenCV functions for computer vision processing.

Designed to Fit Your Needs

SDSoC Environment

Familiar embedded C/C++ application environment to rapidly develop Zynq SoCs

Zynq UltraScale+ MPSoC

Industry's first multi-processing SoC with the highest levels of security and safety

Zynq 7000 SoC

ARM® based processor with the hardware programmability of an FPGA ideal for high-bandwidth video/vision applications

Video Processing

Video system reference design for multi-channel HD and 4K

Intellectual Property

Get to market even faster with world class intellectual property for video and vision from AMD and its Partner Program

Boards and Kits

Video system development out-of-the-box with AMD and Partner Program boards and kits


CAGR growth in commercial
drones from 2015 to 2020

Source: Business Insider

1 million

units of virtual reality
devices will grow to 38
million units in 2020


of the whole Internet will
be online video in 5 years