  We present a general framework and method for simultaneous detection and
segmentation of an object in a video that moves (or comes into view of the
camera) at some unknown time in the video. The method is an online approach
based on motion segmentation, and it operates under dynamic backgrounds caused
by a moving camera or moving nuisances. The goal of the method is to detect and
segment the object as soon as it moves. Due to stochastic variability in the
video and unreliability of the motion signal, several frames are needed to
reliably detect the object. The method is designed to detect and segment with
minimum delay subject to a constraint on the false alarm rate. The method is
derived as a problem of Quickest Change Detection. Experiments on a dataset
show the effectiveness of our method in minimizing detection delay subject to
false alarm constraints.
