Intelligent Vision & Video
Computer vision and video capabilities (formerly found only in laboratory settings) are now available: from compact, low-cost, energy-efficient embedded vision systems for automotive, industrial and commercial applications all the way to high-performance computing systems for data center applications.
Machine vision applications include
- Automotive Driver Assistance
- Factory machine Vision systems
- Video Surveillance
- Broadcast
- Medical Imaging
Xilinx and Intel FPGA Advantage at Each Step of the Video / Vision Pipeline
- Both Intel and Xilinx FPGAs offer performance, cost, flexibility, and integration advantages at each step of the video / vision pipeline.
Flexible Sensor Interfaces
Image sensor suppliers often have proprietary interfaces, and the sensor interfaces keep evolving to keep up with improved sensor capabilities. Intel FPGAs enable designers to adopt new sensor interfaces easily without changing the rest of the design. In contrast, Application Specific Standard Products (ASSPs) require designers to adopt a new ASSP and redesign the camera board.
High Performance Video and Image Signal Processing
Intel FPGAs enable designers todesign high performance video and signal processing systems quickly and flexibly. IP cores such as Intel’s Video and Image Processing (VIP) Suite allow designers to pick and choose video processing functionalities as needed, while the high performance FPGA fabric can be leveraged to accelerate video pre-processing of high resolution videos.
Real-Time Analytics
Intelligent, real-time video analytics are key functions in many vision applications such as automotive driver assistance systems, surveillance, and industrial machine vision, and require complex algorithms such as motion detection, facial recognition, and object detection. With Intel® SoC FPGAs, designers can take advantage of the combined power of the FPGA fabric and the dual-core ARM® Cortex®-A9 hard processor system (HPS) in a single chip. By offloading the computation-intensive functions from the HPS to the FPGA fabric, designers can optimize the implementation of these complex algorithms, thereby improving system performance.
