Jan Prokaj, Ph.D.

Inferring Tracklets for Multi-Object Tracking

Problem

  • Recent algorithms solve the tracking problem hierarchically: first find short tracks (tracklets), then iteratively extend into longer tracks
  • How to optimally determine tracklets?

Approach

Diagram illustrating the construction of the DAG.
  • 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

Results

Data

Code

  • Executables for Linux/Windows:

    2012-05-20 release (recommended) Download

    2012-04-09 release Download

    2011-08-16 release Download

Reference

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]

Related Publications

  • J. Prokaj . Exploitation of Wide Area Motion Imagery . Ph.D. thesis, University of Southern California, 2013.

    [PDF]

  • J. Prokaj , X. Zhao , G. Medioni . Tracking Many Vehicles in Wide Area Aerial Surveillance. In Workshop on Camera Networks and Wide Area Scene Analysis joint with IEEE CVPR , pages 37-43, 2012.

    [PDF] [DOI] [Slides]

  • J. Prokaj , M. Duchaineau. Detection and Tracking of Vehicles in Aerial Imagery . Lawrence Livermore National Lab internship, 2009.

    [Poster]