Title: Optical flow estimation as distributed optimization problem - an aVLSI implementation


Author: Alan Stocker


I present a new focal-plane analog VLSI sensor that estimates optical flow in two
visual dimensions. The chip significantly improves previous approaches both with
respect to the applied model of optical flow estimation as well as the actual
hardware implementation. Its distributed computational architecture consists of 
an array of locally connected motion units that collectively solve for the unique 
optimal optical flow estimate. The novel gradient-based motion model assumes 
visual motion to be translational, smooth and biased. The model guarantees that 
the estimation problem is computationally well-posed regardless of the visual 
input. Model parameters can be globally adjusted, leading to a rich output 
behavior. Varying the smoothness strength, for example, can provide a continuous 
spectrum of motion estimates, ranging from normal to global optical flow. Unlike 
approaches that rely on the explicit matching of brightness edges in space or time, 
the applied gradient-based model assures spatiotemporal continuity on visual 
information. The non-linear coupling of the individual motion units improves the 
resulting optical flow estimate because it reduces spatial smoothing across large 
velocity differences. Extended measures of a 30x30 array prototype sensor under 
real-world conditions demonstrate the validity of the model and the robustness and 
functionality of the implementation.