Online Multi-Target Tracking Using Recurrent Neural Networks

Understand

We present a novel approach to online multi-target tracking based on recurrent neural networks (RNNs).

• Tracking multiple objects in real-world scenes involves many challenges, including a) an a-priori unknown and time-varying number of targets, b) a continuous state estimation of all present targets, and c) a discrete combinatorial problem of data association.
• Most previous methods involve complex models that require tedious tuning of parameters.
• Here, we propose for the first time, an end-to-end learning approach for online multi-target tracking.