  With the development of depth cameras such as Kinect and Intel Realsense,
RGB-D based human detection receives continuous research attention due to its
usage in a variety of applications. In this paper, we propose a new
Multi-Glimpse LSTM (MG-LSTM) network, in which multi-scale contextual
information is sequentially integrated to promote the human detection
performance. Furthermore, we propose a feature fusion strategy based on our
MG-LSTM network to better incorporate the RGB and depth information. To the
best of our knowledge, this is the first attempt to utilize LSTM structure for
RGB-D based human detection. Our method achieves superior performance on two
publicly available datasets.
