  Junctions reflect the important geometrical structure information of the
image, and are of primary significance to applications such as image matching
and motion analysis. Previous event-based feature extraction methods are mainly
focused on corners, which mainly find their locations, however, ignoring the
geometrical structure information like orientations and scales of edges. This
paper adapts the frame-based a-contrario junction detector(ACJ) to event data,
proposing the event-based a-contrario junction detector(e-ACJ), which yields
junctions' locations while giving the scales and orientations of their
branches. The proposed method relies on an a-contrario model and can operate on
asynchronous events directly without generating synthesized event frames. We
evaluate the performance on public event datasets. The result shows our method
successfully finds the orientations and scales of branches, while maintaining
high accuracy in junction's location.
