Inferring Tracklets for Multi-Object Tracking
- Recent algorithms solve the tracking problem hierarchically: first find short tracks (tracklets), then iteratively extend into longer tracks
- How to optimally determine tracklets?
- Consider object detections in a sliding window of frames (4-8 seconds)
- Build an association graph (DAG), or detection graph (representing all possible associations over a sliding window), for each detection in the first frame of the sliding window
- Label detections in this graph as valid (consistent with the initial detection) or invalid (inconsistent)
- MAP inference in a Bayesian network
- Generate track(s) from the resulting sequence of valid detections
J. Prokaj , M. Duchaineau, G. Medioni . Inferring Tracklets for Multi-Object Tracking. In Workshop of Aerial Video Processing joint with IEEE CVPR , pages 37-44, 2011.
[PDF] [DOI] [Slides]
J. Prokaj . Exploitation of Wide Area Motion Imagery . Ph.D. thesis, University of Southern California, 2013.
J. Prokaj , M. Duchaineau. Detection and Tracking of Vehicles in Aerial Imagery . Lawrence Livermore National Lab internship, 2009.