Mobile Influenced Markets – Evolution of Camera and Display Uses (Lattice)
Abstract: Low-cost and low-power FPGAs with CSI2/DSI interfaces have been enabling customers to leverage mobile image sensors, displays and processors for innovative applications in mobile-influenced markets, including consumer, medical, industrial, and automotive. This presentation will highlight the evolution of these types of applications, including the unique issues faced by system and software developers in mobile-influenced markets. Most mobile components are designed for specific use cases such as smartphones, tablets and laptops. As such, the mobile system integration is generally straightforward. However, for innovative mobile-influenced applications (i.e., AR/VR and drones), the mobile components don’t always fit together nicely. For example, a drone might need many more cameras than can be directly accommodated by the mobile application processors (APs). In addition, these cameras have different resolutions and frame rates, e.g., high-frame rate and resolution for videography, and lower resolution for collision avoidance. Within these mobile-influenced use cases, there are common trends such as interfacing of consumer, industrial and automotive grade image sensors to a mobile AP, synchronizing and aggregating multiple image sensors, interfacing to multiple displays, multiplexing between display sources, and interfacing to specialty displays. Connectivity and some video processing through programmable FPGAs often aid in the development of these systems, where the functionality was unforeseen or previously couldn’t be realized. Examples of end applications and extrapolated architectural trends for several use cases will also be explored.
Tom Watzka is the Technical Mobile Solutions Architect at Lattice Semiconductor with over 20 years of experience in developing embedded products, including 7 years developing consumer mobile solutions. Currently, Watzka is the Marketing Product Manager for the CrossLink video bridge product line, focused on mobile and mobile influenced markets. He received his BS degree from the Rochester Institute of Technology, MS degree from Pennsylvania State University, and conducted his Master’s Thesis on FFT algorithms.