δLTA: Decoupling Camera Sampling from Processing to Avoid Redundant Computations in the Vision Pipeline

Continuous Vision (CV) systems are essential for emerging applications like Autonomous Driving (AD) and Augmented/Virtual Reality (AR/VR). A standard CV System-on-a-Chip (SoC) pipeline includes a frontend for image capture and a backend for executing vision algorithms. The frontend typically captures successive similar images with gradual positional and orientational variations. As a result, many regions between consecutive frames yield nearly identical results when processed in the backend. Despite this, current systems process every image region at the camera’s sampling rate, overlooking the fact that the actual rate of change in these regions could be significantly lower.