Towards an Embedded Real-Time High Resolution Vision System

This paper proposes an approach to image processing for high performance vision systems. Focus is on achieving a scalable method for real-time disparity estimation which can support high resolution images and large disparity ranges. The presented implementation is a non-local matching approach building on the innate qualities of the processing platform which, through utilization of a heterogeneous system, combines low-complexity approaches into performing a high-complexity task. The complementary platform composition allows for the FPGA to reduce the amount of data to the CPU while at the same time promoting the available informational content, thus both reducing the workload as well as raising the level of abstraction. Together with the low resource utilization, this allows for the approach to be designed to support advanced functionality in order to qualify as part of unified image processing in an embedded system.