Human activity recognition (HAR) is a very active yet challenging and demanding area of
computer science. Due to the articulated nature of human motion, it is not trivial to detect …

This paper presents a survey on the latest methods of moving object detection in video
sequences captured by a moving camera. Although many researches and excellent works …

Recently dense trajectories were shown to be an efficient video representation for action
recognition and achieved state-of-the-art results on a variety of datasets. This paper …

This paper introduces a video representation based on dense trajectories and motion
boundary descriptors. Trajectories capture the local motion information of the video. A dense …

We present a new descriptor for activity recognition from videos acquired by a depth sensor.
Previous descriptors mostly compute shape and motion features independently; thus, they …

Vision-based human action and activity recognition has an increasing importance among
the computer vision community with applications to visual surveillance, video retrieval and …

We address action recognition in videos by modeling the spatial-temporal structures of
human poses. We start by improving a state of the art method for estimating human joint …

This paper introduces a state-of-the-art video representation and applies it to efficient action
recognition and detection. We first propose to improve the popular dense trajectory features …

Several recent works on action recognition have attested the importance of explicitly
integrating motion characteristics in the video description. This paper establishes that …

Recognizing human actions from unknown and unseen (novel) views is a challenging
problem. We propose a Robust Non-Linear Knowledge Transfer Model (R-NKTM) for human …