Action recognition has very high academic research value, potential commercial value and
wide market application prospect in computer vision. In order to improve the action …

Action recognition in video is widely applied in video indexing, intelligent surveillance,
multimedia understanding, and other fields. A typical human action contains the …

Motion representation plays a vital role in human action recognition in videos. In this study,
we introduce a novel compact motion representation for video action recognition, named …

In recent years, significant progress has been made in modeling temporal sequences and
spatial structures in skeleton-based human action recognition. However, existing methods …

Human action recognition from realistic video data constitutes a challenging and relevant
research area. Leading the state of the art we can find those methods based on …

The deep two-stream architecture exhibited excellent performance on video based action
recognition. The most computationally expensive step in this approach comes from the …

Hand-crafted feature functions are usually designed based on the domain knowledge of a
presumably controlled environment and often fail to generalize, as the statistics of real-world …

A few light stimuli coherently distributed in the space and time are the essential input that a
visual system needs to perceive motion. Inspired in such fact, a compact motion descriptor is …

In this paper, a deep learning method for video‐based action recognition is proposed. On
the one hand, boundary compensation on the basis of a deep neural network is performed …

Spatio-temporal representations in frame sequences play an important role in the task of
action recognition. Previously, a method of using optical flow as a temporal information in …