Yu Wang*
Journal on Artificial Intelligence, Vol.3, No.2, pp. 63-72, 2021, DOI:10.32604/jai.2021.010455
Abstract Visual tracking is a classical computer vision problem with many
applications. Efficient convolution operators (ECO) is one of the most outstanding
visual tracking algorithms in recent years, it has shown great performance using
discriminative correlation filter (DCF) together with HOG, color maps and
VGGNet features. Inspired by new deep learning models, this paper propose a
hybrid efficient convolution operators integrating fully convolution network (FCN)
and residual network (ResNet) for visual tracking, where FCN and ResNet are
introduced in our proposed method to segment the objects from backgrounds and
extract hierarchical feature maps of objects, respectively. Compared with the
traditional VGGNet,… More >
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