Government, municipalities, financial institutions, and businesses are using video surveillance for more than image recording and after-the-fact analysis. Artificial intelligence (AI) is providing real-time, automated, and actionable insights for multiple live camera streams. These advances are powering innovation beyond crime prevention/security into new market business models such as retail asset management and more efficient industrial smart factories.
The challenge for camera manufacturers is where to insert the “smart/analytics” functions within the end-to-end video solution. Some 'simple' intelligence can be implemented in smart Internet Protocol (IP) cameras at low power and with low price points. More complex analytic functions can be implemented 'near the edge' with on-premise gateways or Network Video Recorders (NVRs) supporting multiple, live camera streams. Enterprise class analytics can be implemented using widely available cloud-based computing resources. In general, digital high-definition (HD) IP surveillance cameras are replacing analog cameras because of lower installation costs, scalability, and the ability to add intelligence. Intel® Vision Products provide solutions ranging from the camera to the cloud and include the latest in AI deep learning-based analytics.
Intel FPGAs play a key role in these next-generation HD IP cameras and NVRs:
- Support for AI deep learning frameworks, models, and topologies to implement FPGA-based convolutional neural network (CNN) inferencing accelerators (read about the Intel FPGA Deep Learning Acceleration Suite)
- Flexibility to interface to many types of image sensors
- Fast processing to incorporate a full image sensor pipeline (ISP) intellectual property (IP) that includes techniques, such as defect pixel correction, gamma correction, dynamic range correction, and noise reduction
- Cost-effective solution that can incorporate functions, such as sensor interfacing, image compression, and even pan-tilt-zoom (PTZ) control