Automotive vision processing moving into the camera
Advanced driver assistance systems (ADAS) automate, adapt, or enhance automotive vehicles to increase safety and enhance the driving experience. These systems use sensors such as radar, ultrasound, and especially standard digital cameras to capture their surroundings. Video analytics of these images enables the driver with extra information, warnings, or can even autonomously decide to adapt speed and direct the steering wheel.
Market research firm ABI Research forecasts that the market for ADAS will grow from US$11.1 billion in 2014 to US$91.9 billion by 2020, passing the US$200 billion mark by 2024. ADAS packages have long been available as optional extras on luxury and executive vehicles, but recent years have seen the more popular systems penetrating through to affordable family cars.
To read the full article, click here
Related Semiconductor IP
Related Blogs
- Rambus Introduces RT-648: Bringing Arm-Based Root of Trust into the Automotive CSS Ecosystem
- JPEG XS Officially Joins GenICam, The Machine Vision Standard Managed By EMVA
- CogniVue's "Opus" APEX Generation 3: Vision Processing With Implementation Flexibility
- Vision C5 DSP for Standalone Neural Network Processing
Latest Blogs
- Building the engine behind Arm’s silicon shift
- M31 High-Speed and Long-Channel MIPI C/D-PHY Solution on TSMC N3P/N3C
- Understanding security certification and how analog IP can help
- Embedded Security explained: Secure boot for embedded systems
- World's First Standards-Compliant 112G PHY IP for Linear Optics: A Turning Point for AI Interconnects