Benchmark:

MOT16 |

Short name:

OVBT

Detector:

Public

Description:

An online variational
Bayesian model for multiple-person tracking is proposed. This yields a
variational expectation-maximization (VEM) algorithm. The computa-
tional efficiency of the proposed method is due to closed-form expressions
for both the posterior distributions of the latent variables and for the es-
timation of the model parameters. A stochastic process that handles
person birth and person death enables the tracker to handle a varying
number of persons over long periods of time.

Reference:

Y. Ban, S. Ba, X. Alameda-Pineda, R. Horaud. Tracking Multiple Persons Based on a Variational Bayesian Model. In BMTT 2016, .

Last submitted:

August 16, 2016 (7 years ago)

Published:

July 16, 2016 at 12:07:44 CET

Submissions:

3

Project page / code:

n/a

Open source:

No

Hardware:

2.53GHz

Runtime:

0.3 Hz

Benchmark performance:

Detailed performance:

Raw data:

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