Cameras and Sensors for Embedded Vision
WHILE ANALOG CAMERAS ARE STILL USED IN MANY VISION SYSTEMS, THIS SECTION FOCUSES ON DIGITAL IMAGE SENSORS
While analog cameras are still used in many vision systems, this section focuses on digital image sensors—usually either a CCD or CMOS sensor array that operates with visible light. However, this definition shouldn’t constrain the technology analysis, since many vision systems can also sense other types of energy (IR, sonar, etc.).
The camera housing has become the entire chassis for a vision system, leading to the emergence of “smart cameras” with all of the electronics integrated. By most definitions, a smart camera supports computer vision, since the camera is capable of extracting application-specific information. However, as both wired and wireless networks get faster and cheaper, there still may be reasons to transmit pixel data to a central location for storage or extra processing.
A classic example is cloud computing using the camera on a smartphone. The smartphone could be considered a “smart camera” as well, but sending data to a cloud-based computer may reduce the processing performance required on the mobile device, lowering cost, power, weight, etc. For a dedicated smart camera, some vendors have created chips that integrate all of the required features.
Until recent times, many people would imagine a camera for computer vision as the outdoor security camera shown in this picture. There are countless vendors supplying these products, and many more supplying indoor cameras for industrial applications. Don’t forget about simple USB cameras for PCs. And don’t overlook the billion or so cameras embedded in the mobile phones of the world. These cameras’ speed and quality have risen dramatically—supporting 10+ mega-pixel sensors with sophisticated image processing hardware.
Consider, too, another important factor for cameras—the rapid adoption of 3D imaging using stereo optics, time-of-flight and structured light technologies. Trendsetting cell phones now even offer this technology, as do latest-generation game consoles. Look again at the picture of the outdoor camera and consider how much change is about to happen to computer vision markets as new camera technologies becomes pervasive.
Charge-coupled device (CCD) sensors have some advantages over CMOS image sensors, mainly because the electronic shutter of CCDs traditionally offers better image quality with higher dynamic range and resolution. However, CMOS sensors now account for more 90% of the market, heavily influenced by camera phones and driven by the technology’s lower cost, better integration and speed.
“Edge/Cloud Tradeoffs and Scaling a Consumer Computer Vision Product,” a Presentation from Cocoon Health
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“Selecting the Right Imager for Your Embedded Vision Application,” a Presentation from Capable Robot Components
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“Game Changing Depth Sensing Technique Enables Simpler, More Flexible 3D Solutions,” a Presentation from Magik Eye
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“Machine Learning at the Edge in Smart Factories Using TI Sitara Processors,” a Presentation from Texas Instruments
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Mike Borza, Principal Security Technologist at Synopsys, presents the "Fundamental Security Challenges of Embedded Vision" tutorial at the May 2019 Embedded Vision Summit. As facial recognition, surveillance and smart vehicles become an accepted part of our daily lives, product and chip designers are coming to grips with the business need to secure the data that
Jessica Gehlhar, formerly an imaging engineer at Edmund Optics, presents the "Introduction to Optics for Embedded Vision" tutorial at the May 2019 Embedded Vision Summit. This talk provides an introduction to optics for embedded vision system and algorithm developers. Gehlhar begins by presenting fundamental imaging lens specifications and quality metrics such as MTF. She explains
“Improving the Safety and Performance of Automated Vehicles Through Precision Localization,” a Presentation from VSI Labs
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Gergely Debreczeni, Chief Scientist at AImotive, presents the "Distance Estimation Solutions for ADAS and Automated Driving" tutorial at the May 2019 Embedded Vision Summit. Distance estimation is at the heart of automotive driver assistance systems (ADAS) and automated driving (AD). Simply stated, safe operation of vehicles requires robust distance estimation. Many different types of sensors
Bing Yu, Senior Technical Manager and Architect at MediaTek, presents the "MediaTek’s Approach for Edge Intelligence" tutorial at the May 2019 Embedded Vision Summit. MediaTek has incorporated an AI processing unit (APU) alongside the traditional CPU and GPU in its SoC designs for the next wave of smart client devices (smartphones, cameras, appliances, cars, etc.).