Human action recognition (HAR) refers to the process in which computers analyze and
process video data to obtain the categories of action presented in the video. It has a wide …

Recent methods including CoViAR and DMC-Net provide a new paradigm for action
recognition since they are directly targeted at compressed videos (eg, MPEG4 files). It …

Practically, action recognition using deep learning approaches are slow because of high
temporal redundancy and large size of the raw video data. One of the solutions for boosting …

Compressed domain human action recognition algorithms are extremely efficient, because
they only require a partial decoding of the video bit stream. However, the question what …

Compressed video action recognition is an action recognition approach that can achieve
efficient inference by directly classifying video data obtained from multiple features stored in …

Human action recognition has become one of the most active field of research in computer
vision due to its wide range of applications, like surveillance, medical, industrial …

Recent years have witnessed a growing interest in compressed video action recognition due
to the rapid growth of online videos. It remarkably reduces the storage by replacing raw …

Compressed video action recognition offers the advantage of reducing decoding and
inference time compared to the RGB domain. However, the compressed domain poses …

This paper discusses a novel high-speed approach for human action recognition in H.
264/AVC compressed domain. The proposed algorithm utilizes cues from quantization …

In video action recognition, motion is a very crucial clue, which is usually represented by
optical flow. However, optical flow is computationally expensive to obtain, which becomes …