RoI Pooling Based Fast Multi Domain Convolutional Neural Networks for Visual Tracking
This paper proposes a fast multi domain convolutional neural networks method (Fast MDNet) for visual tracking. Fast MDNet builds on fast region based convolutional neural networks (Fast R CNN) and MDNet to efficiently track arbitrary objects using deep convolutional networks. We introduce a RoI pooling layer which shares full image convolutional features, thus significantly speed up MDNet. Compared to previous works, Fast MDNet's online tracking rate is 15x faster than MDNet, and it performs favorably against the state of the art methods on large benchmark datasets. Keywords component; visual tracking; Fast MDNet; CNN; RoI