Abstract
This paper addresses the problem of segmenting low
level partial feature point tracks belonging to multiple motions.
We show that the local velocity vectors at each instant
of the trajectory are an effective basis for motion segmentation.
We decompose the velocity profiles of point tracks
into different motion components and corresponding nonnegative
weights using non-negative matrix factorization
(NNMF). We then segment the different motions using spectral
clustering on the derived weights. We test our algorithm
on the Hopkins 155 benchmarking database and several
new sequences, demonstrating that the proposed algorithm
can accurately segment multiple motions at a speed
of a few seconds per frame. We show that our algorithm is
particularly successful on low-level tracks from real-world
video that are fragmented, noisy and inaccurate