Details

Autor(en) / Beteiligte

• Henriques, J. F.
• Caseiro, R.
• Batista, J.

Titel

Globally optimal solution to multi-object tracking with merged measurements

Ist Teil von

• 2011 International Conference on Computer Vision, 2011, p.2470-2477

Ort / Verlag

IEEE

Erscheinungsjahr

2011

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• Multiple object tracking has been formulated recently as a global optimization problem, and solved efficiently with optimal methods such as the Hungarian Algorithm. A severe limitation is the inability to model multiple objects that are merged into a single measurement, and track them as a group, while retaining optimality. This work presents a new graph structure that encodes these multiple-match events as standard one-to-one matches, allowing computation of the solution in polynomial time. Since identities are lost when objects merge, an efficient method to identify groups is also presented, as a flow circulation problem. The problem of tracking individual objects across groups is then posed as a standard optimal assignment. Experiments show increased performance on the PETS 2006 and 2009 datasets compared to state-of-the-art algorithms.